Today, the threat of misconfigured permissions is significantly greater. Why? Two words: artificial intelligence or AI.

Enterprise organizations have always cared about permissions in order to protect resources, meet compliance rules, and honor customer contracts. A user might be over-permissioned and gain access to [add example]. But once teams catch these mistakes, they quickly rectify them, and business moves on as usual.

Everything changes when you’re using AI. AI agents are accessing data, sending emails, and making changes. But AI agents aren’t humans—they’re faster and riskier. With humans, a mistake is a mistake. With AI, a single mistake can quickly cascade into a litany of mistakes. This is due to three traits:

1. Multi-System. Agents rarely query a single system. They assemble responses by pulling data from CRMs, file stores, and databases in parallel. This includes read and write access. If an agent makes a bad request for one piece of data, it can contaminate multiple data stores. Even worse, with write access an agent can carryout destructive actions, deleting or overwriting data.
2. Scale. An analyst might run five queries in an afternoon. An agent might issue thousands in seconds. We’ve long accepted some over-permissioning of humans, because humans are limited by time. But with an agent, even a little over-permissioning can snowball into a volume of exposure that security teams cannot reasonably review in time.
3. Blind Execution. Once an agent has a token, it keeps going until expiration. It does not ask whether the user has been off-boarded or whether the device posture has changed. The system “just works”. But that seamlessness conceals a gap. Each request may quietly bypass risk signals that a human would recognize.

Given these risks, I’d describe agents as powerful, but precarious entities. They amplify a user’s capacity, but they also accelerate the consequences of bad assumptions. The solution—which is more of a precaution than a cure—is context-aware permissions. Instead of binding an AI agent’s access to a static role, it double-checks every decision to the live state of the request. For example, a conventionally day-time access financial application might gate access if sudden requests are made at 3am.

As a player in the authorization space, we wanted to write a piece on this growing issue. In this article, we’ll take a look at how context-aware models work and what patterns are gaining adoption. Then, we’ll also go over some of the challenges to consider when these practices are implemented at scale.

Understanding the Risk

While context-aware permissions undoubtedly reduce risk in practice, what exactly is the risk? In other words, without these safeguards, what is the worst that can happen? The answer: a lot. Let’s walk through three examples.

Customer Data Exposure

An AI support bot might be tasked to pull information from a CRM to load it into another system (e.g. Snowflake) or dispatch emails. However, if this AI support bot has a stale token and therefore outdated permissions, it might end up sharing customer information that it wasn’t delegated to access. While perhaps benign in theory, this is dangerous in practice because it might violate customer data custody contracts, posing legal risks.

Information Misconfiguration

If an AI agent routinely pulls information from databases, but has mis-scoped access, then it might pull excessive information into a query that wasn’t supposed to be aggregated. For instance, imagine if an AI agent strictly is supposed to pull information about test accounts from a database, but poor access controls enable it to pull information about any accounts. Suddenly, the agent might leak customer data.

Uncontrolled Bulk Actions

An AI agent might be tasked to clean-up accounts that were strictly cataloged for deletion. However, if the agent has too broad access, the agent might accidentally delete every account because of the model’s non-deterministic nature (or, just as likely, a poorly worded prompt). More generally, if teams fail to control an AI agent, it could wipe out terabytes of information in minutes.

Evaluating Access Against Live Signals

Context-aware permissioning evaluates each request against signals. The authorization server draws these signals from the environment surrounding the request. For example, certain signals might mark a managed laptop with recent patches as a lesser risk profile than a personal smartphone on public Wi-Fi.

Network matters too. Traffic over a corporate VPN is treated differently than the same query routed through public wifi. Time, too, can shift risk scores. A lookup at 2 p.m. on a workday looks normal, but a sudden surge of queries at midnight can raise suspicion. In other words, context isn’t fixed. It moves with the user, the device, and the workload.

The responses could be just as dynamic. Instead of a binary yes/no, agents adapt to risk. In a low-risk context, results return in full. The same query, issued from a higher-risk environment, might be trimmed to read-only or have sensitive fields masked.

This adaptability is what keeps resilient AI systems going. Agents can run continuously across multiple sources without pausing for manual checks. Yet, their reach is always bounded by the live signals surrounding the request. Context-aware permissioning doesn’t just check who the user is. It also checks whether the system should grant access in this specific time, place, and condition.

How Teams Put Context-Aware Models into Practice

What makes context-aware permissioning challenging is the trade-offs. Every approach buys security at the cost of latency, complexity, or integration overhead. The patterns below demonstrate some common benefits of context-aware permissioning alongside their caveats.

Conditional Delegation with Context Scoping

Traditional delegations work on a simple premise: The agent inherits a human user’s identity and its scope of access stays fixed until the token expires. While a good start, this approach doesn’t factor the risk of human error or a user being over-permissioned.

Conditional delegation replaces that static inheritance with a dynamic exchange. Each time the agent presents a user token, a policy decision point (or PDP) evaluates the surrounding signals. Then, it issues a downstream credential trimmed to fit these conditions.

The effect is finer-grained control. A developer role may keep write privileges in staging, but if the same developer’s laptop starts to drift out of compliance, the PDP can automatically downgrade production access to read-only.

There is a catch, however: operational overhead. PDPs need real-time feeds from these downstream services. Teams face messy work when they stitch those signals together across their ecosystem.

Mid-Session Risk Re-Evaluation

Systems that rely on static tokens (e.g., JWTs) assume that an issuer’s status never changes during the token’s lifetime. But the reality is that a user may be off-boarded mid-shift or a device could fall out of compliance. The chances are (fairly) low, but the consequences can be damaging, such as a user accessing a bank account that they’ve been removed from.

Mid-session risk re-evaluation removes that blind spot by treating tokens as ephemeral. Systems modeled after Continuous Access Evaluation (CAE) don’t wait for expiration. Instead, they use revocation channels to terminate sessions when token permissions change.

The trade-off is latency and coordination. Each re-check adds a performance hit, and revocation requires tighter integration across downstream services. But for workloads where a single unauthorized request can expose extremely sensitive info—such as patient data in a healthcare application where access is ephemerally granted to care providers—the cost of stale permissions might be worth the cost of extra milliseconds.

Adaptive Responses

Most enterprises treat access as a binary switch: grant or deny. That rigidity often hinders AI agents that operate in workflows with many un-deterministic steps. A deny blocks all data, but it also stops the agent from moving forward.

Adaptive responses offer a middle ground. Instead of completely shutting the agent down, the system throttles request rates to slow any potential damage. Or, it routes results through human review before release. The agent keeps functioning, but with some guardrails.

The ability to degrade gracefully is especially valuable in AI systems where availability is a priority. Customer support bots or compliance review assistants can’t just error out on every elevated risk. By applying tiered responses, we are able to strike a balance to keep the system operational.

However, implementing this is quite complex. Policies need fine-grained enforcement, sometimes down to the field level. Additionally, transparency matters. Logs and audit trails must explain why the system masked a field or throttled a query so that security teams can reconstruct decisions months later.

Behavioral Context as Input

Additionally, an agent’s behavior is a signal. Agents leave trails of telemetry in the form of query patterns, download volume, request timing, and more. A sudden spike of bulk exports or simultaneous logins from distant regions suggests elevated risk.

Developers can account for this risk with behavior-based checks. Humans might take hours to manually exfiltrate a dataset. An agent can do the same in less than a second if left unchecked. When developers feed behavioral signals into the PDP, the system can automatically catch and respond to misuse without waiting for human review.

The hard part is calibration. Thresholds set too tightly flood users with re-authentication prompts while thresholds set too loosely let anomalies slip past. To reach higher-confidence decisions, most enterprises blend behavior scores with other context inputs (i.e., device posture, network, location).

Closing Thoughts

Context-aware permissions are straightforward in principle. You evaluate live signals, trim scope, and adapt to risk. In practice, adoption is harder. Every extra check adds latency. Fragmented systems send signals asynchronously. Developers must add extra checks for complex token exchange flows. And the system must log each masked field or throttled request clearly enough for security teams to explain six months later.

Still, the investment pays off for sensitive applications. Role-based access defines what a user should be able to do, but only context-aware permissions ensures those guarantees hold in the moment. It ties identity to the live conditions of a request to make AI agents more predictable.

That shift works best when authorization is centralized. Tools like Oso provide a control plane where policies are defined once and enforced consistently across apps and APIs. Instead of rewriting context checks for every service, teams can use Oso to manage them centrally.

If you would like to learn more, check out the LLM Authorization chapter in our Authorization Academy.

FAQ

What is context-aware permissioning?

It’s an access model where each request is evaluated against live conditions (i.e. device posture, network, behavior) rather than relying only on static roles assigned at login.

Why aren’t static roles enough for AI agents?

Static roles assume conditions don’t change mid-session. But agents run at machine speed, often across multiple systems. A stale token can keep working even after a user is off-boarded or a device falls out of compliance.

What’s the risk of using service accounts for agents?

Service accounts usually hold broad, long-lived privileges. When an agent runs under one, it bypasses user-specific roles and revocations, turning a single integration into a systemic exposure point.

What is mid-session risk re-evaluation?

It’s a mechanism where tokens are short-lived and continuously re-validated. If risk signals change (like a device falling out of compliance), systems can revoke sessions immediately rather than waiting for expiration.

What are adaptive responses?

Adaptive responses replace binary “grant or deny” outcomes with graduated actions. Instead of blocking an agent entirely, systems can redact sensitive fields, throttle request rates, or require human approval.

How does behavioral context factor into permissioning?

Agents generate telemetry (query patterns, data volume, request timing) that can be scored against baselines. Sudden anomalies trigger re-evaluation.

TL;DR

• Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) are common ways to design permissions within an application. Policy-Based Access Control (PBAC) is a method of implementing access control – whether RBAC or ABAC – where you decouple your policy from your code.
  
  
• RBAC ties permissions to roles like Owner, Editor, or Viewer that directly map to permissions. It’s easy to start with, but it creates “role explosion” and becomes rigid as systems grow.
  
  
• ABAC introduces flexibility by factoring in user attributes, resource metadata, and context, such as time or location. It enables dynamic decisions but is harder to manage, test, and optimize at scale.
  
  
• PBAC takes central control by using explicit, auditable policies that combine roles, attributes, and direct permissions. Tools like Oso enable teams to implement these policies declaratively, keeping authorization consistent and testable across services.
  
  
• Oso also supports ReBAC (Relationship-Based Access Control), which defines permissions based on relationships such as manager-of, member-of, or owner-of. (While this article focuses on RBAC, ABAC, and PBAC, we touch on how ReBAC fits into unified, policy-driven authorization systems here.)

In microservices, authorization logic tends to fragment over time. What begins as a few role checks in one service expands into rules based on user attributes, resource metadata, and environmental conditions like time or region. When these rules are implemented separately across APIs, jobs, and frontends, ensuring consistent access control becomes difficult.

This post explains how to design authorization that remains consistent and maintainable across services. It covers three access-control models: RBAC, ABAC, and PBAC, and how they fit together:

• RBAC maps users to predefined roles and permissions.
• ABAC evaluates user, resource, and contextual attributes for more granular control.
• PBAC centralizes all authorization logic in policies evaluated by a policy engine.

‍

Using Oso and its Polar language, we’ll look at how to define RBAC and ABAC declaratively and enforce them through PBAC for reliable authorization across distributed environments.

Access Control Models That Shape Secure Systems

In cloud-native systems and distributed applications, controlling who can access which resources and under what conditions is a pillar of security architecture and operational discipline. Access-control models provide structured ways to enforce these decisions, ranging from static, role-based assignments to dynamic, attribute-driven evaluations. The two foundational models most organizations rely on are RBAC and ABAC, each addressing different levels of granularity and complexity.

RBAC: Role-to-Permission Mapping for Predictable Systems

Role-Based Access Control (RBAC) assigns users to roles, and each role is associated with permissions. This model is effective when user responsibilities are clearly defined and access requirements are relatively stable. For example:

• In a project management tool, an Admin can create, update, and delete project configurations, while a Viewer can only read project details.
  
  
• In a cloud management system, an Owner can manage billing and account settings, whereas an Editor can deploy and modify resources but cannot access billing information.

RBAC’s simplicity enables fast onboarding and predictable permission management, but it struggles with complex and evolving environments. When systems span multiple teams, geographies, or tenants, RBAC can lead to role proliferation (a.k.a. role explosion), where dozens or hundreds of roles are required to capture nuanced access conditions. This complexity not only increases administrative overhead but also raises the risk of unintended privilege escalation and complicates audit and compliance processes.

ABAC: Attribute-Based Access Evaluation

Attribute-Based Access Control (ABAC) evaluates access dynamically based on a combination of user attributes, resource metadata, and environmental/contextual parameters. ABAC is ideal for systems that require fine-grained, context-sensitive access control, especially in regulated industries and multi-tenant architectures. Examples include:

• In a banking application, a Compliance Officer may access transaction records only for accounts they manage, while HR personnel are denied access to financial data.
  
  
• In a hospital system, a cardiologist can access patient records for cardiology cases, but not oncology or neurology patients.
  
  
• Time-bound or location-bound access, e.g., a report is readable only during business hours or only from a corporate network, can be enforced without creating new roles.

ABAC reduces the need for creating numerous specialized roles because permissions are calculated at runtime, considering multiple conditions. However, ABAC introduces policy complexity: each new attribute or condition adds evaluation logic, increasing the challenge of testing, updating, and auditing policies. Careful schema design, attribute validation, and policy governance are critical for ABAC to scale safely.

RBAC vs ABAC at a Glance

‍

RBAC gives you predictable guardrails. ABAC adds context, like “only engineers in the same department can edit logs after hours.” The trouble starts when those rules get baked directly into code. An API checks if role == "admin", a middleware checks department, and the frontend hides a button. Six months later, one service blocks the action, another quietly allows it, and nobody can explain why during an audit.

Beyond Access Control: PBAC as the Authorization Control Plane

PBAC solves this problem of fragmented authorization logic by externalizing access control into a centralized policy engine. Instead of embedding conditions across controllers and interfaces, each service makes a standard authorization query: isAllowed(user, action, resource). 

The policy engine evaluates roles, attributes, and contextual data against defined policies and returns a consistent, auditable decision. This model provides authorization as a service, ensuring uniform and maintainable access control across all systems.

When applied, those policies capture conditions that would otherwise lead to role sprawl or scattered logic:

• Finance systems often need fine-grained clearance rules. Instead of creating a special “AfterHours-ReportViewer” role, PBAC expresses it directly:

 allow(user, "view", report) if
  user.clearance >= 5 and
  report.type == "EOD" and
  request.time >= "18:00";

• Multi-tenant SaaS platforms need regional separation for compliance. Rather than duplicating roles per region, PBAC encodes the condition once:

 allow(user, "read", tenantData) if
  user.role == "support" and
  user.region in tenantData.allowedRegions;

• Collaboration tools must combine ownership and sharing. Instead of complex role hierarchies, PBAC states the logic explicitly:

 allow(user, "edit", doc) if
  user == doc.owner or
  user in doc.collaborators;

Because policies live outside application code, they can be tracked in version control, reviewed via change requests, tested in CI, and rolled out like config. Change the rule once, and every service enforces it immediately. Decision logs give you exact “who did what and why” visibility. And instead of creating endless roles for edge cases, you capture the conditions directly in policy.

PBAC doesn’t replace RBAC or ABAC; it enhances their reliability. Roles still group users, attributes still provide flexibility, but PBAC ensures those rules are applied the same way across APIs, UIs, and background jobs. For large-scale or regulated systems, that shift, from scattered checks to centralized, declarative policies, is what makes authorization consistent, auditable, and easy to evolve.

Architecture: How PBAC Enforces RBAC & ABAC Consistently

In most SaaS systems, authorization logic spreads everywhere.

• An API route checks role == "admin".
• Middleware validates department == "Engineering".
• The frontend hides buttons based on user.clearance.

Individually, these checks work, but when applied across multiple services, they tend to drift. One endpoint denies an action, another quietly allows it, and no one can explain why during an audit.

PBAC fixes this by making all services call the same enforcement layer. Instead of scattering conditions across controllers and UIs, you centralize them in a policy engine and ask:

const allowed = await authz.isAllowed(user, action, resource);

That one decision point enforces RBAC role rules, ABAC attribute checks, and any resource-specific policies you’ve defined.

Flow in a SaaS App

The workflow below illustrates the high-level architecture of the access control system: 

Here’s a detailed flow of how access control is enforced at each step:

1. Authentication (Identity Provider)
   

• A user signs in through Auth0 or OIDC.
• The IdP issues a JWT that includes their ID, role, and optional attributes (e.g. { role: "collaborator", department: "Engineering", clearance: 3 }).
  

2. Policy Engine (Oso)
   

• Every request runs through Oso.
• The engine applies your Polar policies: RBAC rules (roles -> permissions), ABAC checks (clearance vs. sensitivity), or per-resource overrides.
• Output is always the same boolean: allow or deny.
  

3. Backend Enforcement (Next.js API Routes)
   

• Each route calls authz.isAllowed() before touching the database.
• Example: POST /products checks that the user has "create" permission. If not, it fails fast with 403 Forbidden.
  

4. Frontend Adaptation (Next.js + Tailwind)
   

• The UI queries the same engine (or uses cached decisions).
• Buttons, forms, and routes are shown or hidden based on the policy decision.
• Example: a Viewer never sees “Edit” or “Delete,” while an Owner does.

5. Permission Store (MongoDB)
   

• Stores users, roles, attributes, and per-resource grants.
• Oso pulls from this store when applying policies, ensuring consistent results across API and UI.

Access Control in Action: From RBAC and ABAC to Centralized Policy Enforcement

To see how this works in implementation, imagine a small product management app where different people sign up and start working with resources. Some users are assigned fixed roles, others carry specific attributes, and still others gain permissions through ownership. RBAC and ABAC describe the rules of access, but enforcement becomes messy when those rules are spread across the API, middleware, and frontend. This is exactly where PBAC, implemented here in Polar with Oso as a permission layer, provides a single point of evaluation.

Roles as Guardrails (RBAC)

When Shan signs up, his JWT token includes:

That role maps directly to permissions in a Polar policy:

actor User {}

resource Product {
  roles = ["owner", "collaborator", "viewer"];
  permissions = ["read", "update", "delete"];

  # role inheritance
  "viewer" if "collaborator";
  "collaborator" if "owner";

  # permissions
  "read" if "viewer";
  "update" if "collaborator";
  "delete" if "owner";
}

RBAC is simple and fast, but breaks down once you need rules that depend on context.

Attributes as Context (ABAC)

Bob signs up without a role but with attributes:

When Alice creates Product A, she tags it with metadata:

ABAC rules evaluate those attributes:

user_department(_: User, _: String);
user_clearance(_: User, _: Integer);
product_department(_: Product, _: String);
product_sensitivity(_: Product, _: Integer);
has_permission(user: User, "update", product: Product) if
  user_department(user, dept) and
  product_department(product, dept) and
  user_clearance(user, c) and
  product_sensitivity(product, s) and
  c >= s;

This is more flexible than roles, but managing many attributes across services is error-prone.

Ownership and Sharing (Resource-Level Rules)

When Alice creates Product A, she automatically becomes its owner:

actor User {}

resource Product {
  roles = ["owner", "reader", "editor", "deleter", "sharer"];
  permissions = ["read", "update", "delete", "share"];
  # Track who created the product
  relations = { creator: User };
  # Ownership: creator automatically becomes owner
  "owner" if "creator" on resource;
  # Owner inherits all roles
  "reader"  if "owner";
  "editor"  if "owner";
  "deleter" if "owner";
  "sharer"  if "owner";
  # Map roles to permissions
  "read"   if "reader";
  "update" if "editor";
  "delete" if "deleter";
  "share"  if "sharer";
}

Here’s how the flow is:

1. When a product is created

Your application sends a relational fact linking the creator (Alice) to the new product:

rel(product_a, "creator", alice)

• The policy says "owner" if "creator" on resource;
• That means Alice automatically gets the owner role on product_a.
• Because "owner" inherits all other roles, Alice has every permission:
  
  
  
  • read
  • update
  • delete
  • share

When Alice shares the product with Bob

Instead of granting permissions directly, your app assigns Bob one or more roles on the product by sending role facts:

role(bob, "reader",  product_a)   # Bob can read
role(bob, "editor",  product_a)   # Bob can update
role(bob, "deleter", product_a)   # Bob can delete
role(bob, "sharer",  product_a)   # Bob can share

• Each of these role assignments maps directly to the corresponding permission inside the Product resource block.
  
  
• For example:
  
  
  
  • role(bob, "reader", product_a) : allows Bob to read product_a
  • role(bob, "editor", product_a) : allows Bob to update product_a:

Centralized Enforcement with Policies

Here’s the pivot: instead of scattering checks, every part of the app asks the same question:

const canUpdate = await authService.isAllowed(osoUser, "update", osoProduct);

Oso evaluates the Polar policies and returns true or false. That single decision includes:

• RBAC role rules,
• ABAC attribute checks,
• Resource-specific overrides.

The same enforcement logic runs in API routes, background jobs, and the frontend UI. No more drift.

Why This Matters

• RBAC defines predictable baseline permissions.
• ABAC adds context for real-world flexibility.
• Resource ownership + sharing gives per-object precision.
• PBAC ties it all together, not as another model, but as the enforcement layer.

And in this app, Oso is the engine making PBAC practical; policies are written in Polar, versioned in Git, tested in CI, and enforced everywhere through one isAllowed() call.

Applying RBAC and ABAC Through PBAC

RBAC and ABAC define the logic of authorization, but without a consistent policy layer, those rules are often duplicated across APIs, services, and frontends. PBAC (Policy-Based Access Control) solves this by centralizing RBAC and ABAC rules into policies that can be versioned, reviewed, tested, and enforced uniformly. This ensures that the same logic is applied everywhere, reducing errors and making audits reliablet. For example, one service might enforce “Managers can approve invoices up to $10,000,” while another accidentally enforces “Managers can approve all invoices.” Drift like this makes audits unreliable and security gaps inevitable.

This is where PBAC fits in: at the point where you need to ensure rules are applied uniformly across a distributed system. PBAC decouples policy logic from application code and centralizes it into a single decision point, such as an authorization service (isAllowed(user, action, resource)). Instead of each service re-implementing RBAC or ABAC checks, they all delegate the decision to PBAC.

By decoupling logic this way, PBAC provides:

• Consistency: RBAC and ABAC rules are written once and enforced everywhere.
  
  
• Auditability: every authorization decision records which policy allowed or denied it.
  
  
• Version control: policies live alongside code, can be reviewed in PRs, and tested in CI.
  
  
• Scalability: as teams add services, they don’t need to reimplement rules; they consume the central policy engine.

PBAC isn’t a separate authorization model like RBAC or ABAC. Instead, it’s an approach that organizes rules (whether role-based, attribute-based, or a mix) into policies that are managed centrally. By externalizing rules into policies, PBAC ensures consistent enforcement across services, APIs, and UIs, reducing duplication and preventing inconsistencies.

The real decision, then, is not “Which model should I use?” but “What mix of RBAC and ABAC does my system require, and how will PBAC enforce those rules consistently over time?”

By this point, it’s clear that RBAC and ABAC define the logic of access, while PBAC provides the control plane that makes those rules consistent, auditable, and scalable.

So how does this work in production? Let’s look at a few real-world examples where organizations hit the limits of scattered RBAC/ABAC, and why they turned to a PBAC approach to bring order back into authorization.

Examples: How Teams Built Unified Authorization Control Planes

While this post focuses on RBAC, ABAC, and PBAC, most production-grade authorization systems also incorporate Relationship-Based Access Control (ReBAC), a model that defines permissions based on relationships between entities (for example, manager-of, member-of, or owner-of). Here, PBAC unifies all three: RBAC for roles, ABAC for context, and ReBAC for relationships, evaluated together by a single policy engine.

Below are three production deployments where engineering teams moved from fragmented role checks to a PBAC control plane using Oso. Each shows how structured, policy-based authorization simplifies complexity and scales cleanly across products and architectures.

Oyster: Global HR, Sensitive Data, Many Jurisdictions

Context: Oyster operates a global employment platform in over 180 countries, managing payroll and sensitive PII, as well as internal admin and customer-tenant boundaries.

Constraints. From day one, Oyster required RBAC + ReBAC + ABAC to model hierarchical roles, cross-functional access, and region-specific compliance. Its in-house system soon became brittle, with manual role assignment, duplicated checks, and months-long engineering cycles to add or adjust permissions.

With Oso, Oyster decoupled authorization into Polar policies managed in Oso Cloud. Policies are versioned, reviewed, and deployed independently of app code, with all checks routed through a centralized decision service. Roughly 90 policy files govern more than 10,000 users (internal + external). Oso Cloud handles global, low-latency authorization (< 10 ms) while maintaining regional data-sovereignty compliance.

The end result was:

• 8× faster role implementation through reusable policy patterns.
• Flexible addition of roles and conditions without touching app code.
• Consistent, auditable enforcement across services and jurisdictions.

Webflow: Fine-Grained Enterprise Permissions Without Drag

Context. As Webflow expanded into the enterprise segment, customers demanded granular permissions at the level of CMS collections, pages, locales, and product lines.

Constraints. Its JSON-based, database-tied model didn’t scale. Performance degraded under load, caching was inconsistent, and developer effort ballooned, resulting in weeks lost on rejected authorization changes. Scattered logic across services made reasoning and audits difficult.

Webflow integrated Oso to unify RBAC, ABAC, and ReBAC in one system. Resource blocks define all roles, permissions, and relationships for each resource type, consolidating what had been duplicated logic. Policies are written in Polar and integrated into developer workflows through Oso’s CLI, IDE, and CI tools. The decision engine delivers sub-10 ms checks with near-continuous uptime, and fallback nodes ensure authorization continuity during network outages.

The outcome:

• Clean separation of concerns, authorization treated as infrastructure.
• Safer, faster policy iterations with minimal regressions.
• Unified, fine-grained control aligned with enterprise requirements.

Productboard: Centralized Authorization for Microservices and AI

Context. Productboard serves over 6,000 companies and has transitioned from a monolith to microservices while launching AI-driven products requiring user-scoped visibility.

Constraints. The legacy Ruby authorization layer used hardcoded if checks and couldn’t express custom roles, ReBAC, or field-level rules. Consistency across services and latency at scale were key blockers.

Productboard centralized all authorization logic in Oso Cloud. Each microservice delegates authorize() checks to Oso, which evaluates policies against mirrored relationship data. The same PBAC policies govern both human and AI access flows. The stress tests at enterprise scale, millions of data points per tenant, showed Oso was the only system to meet load requirements with zero errors. In production, authorization runs at < 10 ms p95, ~ 50 ms p99.9, and 99.991 % uptime. AI workflows (RAG-based) filter embeddings and search results through Oso, ensuring AI agents see only authorized data.

The Outcome:

• 2–3× faster enterprise readiness through centralized policy logic.
• A single source of truth for permissions across microservices and AI.
• New revenue opportunities via granular, policy-driven governance with minimal engineering overhead.

The Pattern Behind Scalable Authorization 

In each of these architectures above, expressing roles, attributes, and relationships declaratively and evaluating them through a single policy engine made authorization deterministic, testable, and observable. PBAC doesn’t replace RBAC or ABAC; it composes them, often extending to ReBAC to model ownership and delegation semantics. 

Oso implements this composition at the application layer, where authorization logic must align with domain models and service boundaries. By contrast, managing distributed Rego policies in OPA across many microservices introduces drift, duplicated logic, and operational overhead. Oso’s centralized decision engine eliminates that fragmentation, enforcing consistent authorization semantics across APIs, services, and UIs while maintaining low latency and isolation guarantees..

Oso as a Policy-Based Access Control (PBAC) Layer

The key challenge in authorization is not whether you use RBAC or ABAC; it’s how you enforce those rules consistently without scattering them across your application. That’s what a policy-based approach (PBAC) solves: you decouple authorization logic from application code, write it once as policies, and enforce it everywhere with a single decision point.

Oso gives you that layer through Polar, a policy language designed for application authorization. Polar has first-class primitives for actors, resources, roles, permissions, and relations — the things you actually work with when building app auth. Instead of hardcoding if (role === "admin") checks, you write:

const allowed = await oso.authorize(user, "update", resource);

Behind that call, Oso evaluates your RBAC, ABAC, or per-resource policies consistently.

RBAC in Oso

actor User {}

resource Organization {
  roles = ["viewer", "member", "admin"];
  permissions = ["read", "update", "delete"];

  "read"   if "viewer";
  "update" if "member";
  "delete" if "admin";

  # Inheritance
  "viewer" if "member";
  "member" if "admin";
}

One block defines your entire role, including permission mapping and inheritance. Instead of repeating role checks across controllers, the logic is centralized in policy.

ABAC in Oso

actor User {}

resource Document {
  permissions = ["read", "edit", "delete"];

  # ABAC: decision based on a scalar attribute
  "read" if resource.is_public == true;
}

‍

Rules come from attributes: a document is readable by anyone if its is_public field is set to true. This is an ABAC (Attribute-Based Access Control) policy expressed in Polar.

Per-Resource Policies in Oso

actor User {}

resource File {
  permissions = ["read", "delete"];
  relations = { owner: User };

  # role-to-permission sugar
  "read"   if "owner";
  "delete" if "owner";

  # direct grants
  "read"   if granted(actor, "read", resource);
  "delete" if granted(actor, "delete", resource);
}

Here, ownership and explicit grants are pulled from your DB and enforced as policies. Alice might have delete on File A but only read on File B. This is fine-grained, instance-level control without one-off checks in your code.

Developer Workflow with Oso

To manage RBAC, ABAC, and PBAC effectively, Oso provides tooling across the full dev cycle:

• Rules Workbench: Use Oso Workbench to model and test Polar rules interactively. Developers can simulate isAllowed(user, action, resource) calls and see which rules match.
• Local Dev Server: Run the Oso local server to evaluate policies against sample data before deploying. This ensures Polar rules behave as expected in your environment.
• Pre-commit Hooks + CI: Integrate Oso policy linter/tests in Git hooks and CI pipelines. This automatically blocks invalid syntax, untested rules, or overly permissive policies before they merge.
• Migration Tools: Use Oso Cloud migration tooling to roll out new or updated Polar policies safely. You can stage, test, and incrementally apply changes without breaking production.
• Explain/Debug: With Oso’s explain mode, developers can trace why authorize() returned true or false, showing which rule fired or why access was denied.

This workflow ensures that policy complexity scales safely with your application as you start adding more features and complexities.

‍

Conclusion: Authorization as a Declarative Control Plane

Authorization scales only when it’s built into the system architecture instead of being scattered through service code. PBAC defines that boundary: policies are treated as data and evaluated through a single decision layer. This makes access decisions consistent, observable, and verifiable.

Oso implements this model within the application layer, where authorization must run close to domain data and context. Instead of maintaining separate Rego policies for each microservice, Oso provides a unified policy plane with defined semantics, version control, and low-latency evaluation.

‍

Consistency in authorization comes from consolidation, not duplication. PBAC, implemented through Oso, establishes that boundary and enforces it uniformly.

FAQs

1. Which is better, ABAC or RBAC?

RBAC is usually preferred for its simplicity. It works well when roles and permissions are stable. ABAC introduces flexibility but also more moving parts. Access is based on user, resource, and environment data, which adds overhead as systems and policies grow.

2. Is RBAC part of ABAC?

No. RBAC assigns access through predefined roles. ABAC uses attributes, user details, resource type, department, or clearance level to decide access. ABAC can model RBAC behavior, but it’s a broader, data-driven approach.

3. What is the difference between PBAC and RBAC?

RBAC grants access through fixed role-to-permission mappings. PBAC defines policies that combine roles, attributes, and conditions to make runtime access decisions. RBAC works for predictable structures; PBAC handles complex or dynamic environments where access logic changes often.

4. Is IAM RBAC or ABAC?

 IAM is a framework for managing identities, credentials, and permissions. RBAC and ABAC are models implemented within IAM systems to define how access decisions are made.

‍

TLDR;

• RBAC (Role-Based Access Control) shifts the responsibility of access management from individual users to reusable roles. Instead of attaching dozens of permissions directly to each user, you assign them to a role like admin, contributor, or viewer, each with its own set of permissions, which keeps access predictable and consistent as systems grow.
  
  
• RBAC has use cases across industries like healthcare, banking, cloud, SaaS, and Kubernetes, helping secure sensitive data through least-privilege access control. Doctors can update patient records, auditors in banks have read-only access, and developers in cloud setups are limited to scoped services—each role enforces clear boundaries.
  
  
• RBAC not only secures sensitive data but also prevents cross-tenant access in SaaS platforms and reduces risks of misconfiguration in large-scale infrastructure. By structuring roles carefully, organizations maintain predictability and avoid accidental privilege escalation.
  
  
• The mechanics of RBAC vary by system but follow the same principle: permissions are mapped to roles, then enforced via queries, IAM policies, or Kubernetes bindings. Whether database-level row filtering or JSON policy in AWS, the goal is consistent authorization.
  
  
• Authorization providers like Oso make real-world RBAC setups easier by providing declarative role definitions, drag-and-drop assignments, and built-in testing. This removes the need for hand-coded policies in languages like Rego (policy language used by the Open Policy Agent (OPA) to define and enforce authorization rules) and ensures authorization stays secure, scalable, and maintainable.

RBAC, is one of the most widely used authorization models in software systems like finance, HR, CRMs, etc. Instead of attaching permissions directly to users, RBAC assigns permissions to roles, and users assume those roles. This indirection simplifies access management and keeps authorization consistent as applications scale.

Common role examples include:

• Project Manager: Create tasks, assign work, and close projects
• Contributor: Create and update tasks
• Viewer: Read project status but cannot edit

For example, in a project management tool like Jira or Asana, you might define a project_manager role with permissions to create tasks, assign work, and close projects. Team members take the contributor role, which only allows creating and updating tasks. A client user might be assigned a viewer role, restricted to reading project status but not editing it. By modeling access this way, you don’t manage permissions for every individual user; you manage roles and apply them across the system.

The importance of RBAC becomes clear in multi-tenant and collaborative systems like project management tools, customer support platforms, or SaaS CRMs. In a customer support application, one user could be a support_manager with permissions to assign tickets and update workflows, while another is a support_agent limited to responding to tickets. An account_admin might configure organization-wide settings, and a billing_viewer could access invoices without the ability to change subscription details.

The problem is that RBAC often becomes hard to maintain over time. Teams usually begin with two roles, admin and user, but soon add exceptions like read_only_admin or limited_user, leading to what is known as role explosion. Permissions end up scattered across the codebase, and developers can no longer confidently answer, Who has access to what?

In this post, we will examine RBAC examples, hierarchical roles, resource-scoped roles, action-constrained roles, and hybrid models that address these challenges and keep role systems manageable.

Top 5 RBAC Examples In the Real World

RBAC (Role-Based Access Control) is best understood not through theory but by looking at how it works in real-world scenarios. Instead of abstract policies or technical rules, it is the practical use cases that show how roles and permissions are assigned to manage access effectively.

Before moving forward, let’s understand two important terms often used in RBAC implementations: Polar and Rego.

Polar is the declarative policy language used by Oso, an open-source authorization framework. It allows developers to define access control logic in a structured and readable way. With Polar, you can express who can perform what action on which resource using simple rules. It integrates directly into application code, making authorization decisions consistent and easy to maintain.

Rego, on the other hand, is the policy language used by Open Policy Agent (OPA). It’s a more general-purpose language that can enforce policies across systems, like APIs, CI/CD pipelines, Kubernetes clusters, or microservices. Rego policies define rules for evaluating requests and returning authorization decisions, making it suitable for large-scale, distributed environments.

Looking at such examples helps clarify how permissions, roles, and responsibilities translate into practice. So let’s start one-by-one:

RBAC in Healthcare Systems

Healthcare applications need a clear separation of responsibilities between medical, financial, and administrative staff. Doctors update patient records, nurses maintain vitals and medication details, receptionists handle appointments, and administrators manage system settings.

In the healthcare sector, organizations like Tamr have used Oso's authorization platform to secure regulated, high-sensitivity data in the cloud. By implementing fine-grained access controls, Tamr enables users to access only the data pertinent to their roles, thereby reducing the risk of unauthorized access and ensuring compliance with healthcare regulations.

Similarly, Kaleidoscope, a biotech R&D platform, utilizes Oso to manage access to sensitive research data. Their platform allows lab and computational teams to plan and track scientific work, integrating data and streamlining collaboration, all while maintaining strict access controls to protect intellectual property and comply with industry standards. 

These examples demonstrate how RBAC, when implemented effectively, can protect sensitive healthcare data, ensure compliance with regulations, and streamline workflows by providing appropriate access to users based on their roles.

‍

‍

A common implementation is role–permission mapping in the database. When a user calls an API endpoint, the system validates whether the role tied to that user includes the requested permission. 

With Oso Polar policies, we can define these roles and their permissions directly in code. Instead of relying on SQL queries to validate access, the policy itself enforces which actions each role can perform.

‍

actor User {}

resource HealthcareSystem {
  roles = ["doctor", "nurse", "receptionist", "administrator"];
  permissions = [
    "view_patient_record", "update_patient_record", "prescribe_medication",
    "update_vitals", "administer_treatment",
    "schedule_appointment", "manage_patient_intake",
    "manage_users", "audit_logs", "system_settings"
  ];

  # doctors
  "view_patient_record" if "doctor";
  "update_patient_record" if "doctor";
  "prescribe_medication" if "doctor";

  # nurses
  "update_vitals" if "nurse";
  "administer_treatment" if "nurse";

  # receptionists
  "schedule_appointment" if "receptionist";
  "manage_patient_intake" if "receptionist";

  # admins
  "manage_users" if "administrator";
  "audit_logs" if "administrator";
  "system_settings" if "administrator";
}

‍

When an API call is made, Oso evaluates whether the requesting user has the right role to perform that action. For instance, a receptionist cannot update patient records because the "update_patient_record" permission is never linked to their role. This ensures least-privilege access without manually writing SQL checks.

RBAC in Banking Applications

Banking applications require strict separation of duties to prevent fraud and ensure compliance with financial regulations. Customers, tellers, managers, and auditors operate in the same system but must have carefully bounded access. 

For example, customers should never query or update another user’s account, while tellers can process transactions but not authorize unusually large ones. Managers handle escalations and approvals, and auditors must review immutable records without the ability to alter them.

Here’s an example of what roles and permissions might look like in a typical banking application. This table illustrates how different roles are defined to control access to sensitive financial operations and ensure secure handling of customer data:

‍

‍

We’ll implement this RBAC in Polar using Oso to define these roles and their permissions directly in code instead of relying on row-level database security.  Consider this policy:

‍

actor User {}

resource BankSystem {
  roles = ["customer", "teller", "manager", "auditor"];
  permissions = [
    "view_balance", "transfer_funds", "download_statements",
    "process_transaction", "verify_identity",
    "approve_large_transaction", "manage_tellers",
    "view_audit_logs"
  ];

  # customers
  "view_balance" if "customer";
  "transfer_funds" if "customer";
  "download_statements" if "customer";

  # tellers
  "process_transaction" if "teller";
  "verify_identity" if "teller";

  # managers
  "approve_large_transaction" if "manager";
  "manage_tellers" if "manager";

  # auditors
  "view_audit_logs" if "auditor";
}

‍

In this setup, customers can view their balance, transfer funds, and download account statements within their own accounts. Tellers handle deposits, withdrawals, and customer verification but cannot approve high-value transactions. Managers have the authority to approve those transactions and supervise teller activities, adding a layer of oversight. Auditors maintain read-only access to financial logs for compliance checks without the ability to modify records.

Instead of scattering access rules across SQL queries, Oso centralizes these permissions in the policy. For example, when a teller attempts to approve a large transaction, Oso will deny the request because "approve_large_transaction" is only mapped to managers. This makes access decisions clear, auditable, and consistent across the entire banking system.

RBAC in Cloud Infrastructure (AWS IAM)

Cloud environments demand strict access segmentation because misconfigured permissions are one of the most common causes of breaches. In AWS, Identity and Access Management (IAM) enforces access through roles and policies. 

‍

‍

Similarly, with Oso Polar, we can represent cloud personas such as developers, DevOps engineers, auditors, and administrators with scoped permissions that mirror least-privilege IAM setups.

‍

actor User {}

resource CloudAccount {
  roles = ["developer", "devops", "auditor", "administrator"];
  permissions = ["read", "write", "manage_lambda", "view_logs", "manage_ec2", "manage_ecs", "manage_eks", "manage_cloudformation", "manage_iam", "manage_billing", "full_access"];

  # role-permission mapping
  "manage_lambda" if "developer";
  "view_logs" if "developer";
  "manage_ec2" if "devops";
  "manage_ecs" if "devops";
  "manage_eks" if "devops";
  "manage_cloudformation" if "devops";
  "read" if "auditor";  # auditors get read permission
  "manage_iam" if "administrator";
  "manage_billing" if "administrator";
  "full_access" if "administrator";
}

‍

Developers can deploy and debug workloads by managing Lambda functions and viewing logs but have no access to IAM or billing. DevOps engineers manage infrastructure components such as EC2, ECS, EKS, and CloudFormation stacks without account-level governance rights. Auditors operate with read-only access to review system activity, while administrators retain full privileges, including IAM and billing, forming the highest trust boundary.

So, by centralizing access rules in Oso, permissions become explicit, consistent, and auditable across the entire cloud environment. For example, a developer attempting to modify IAM policies will be denied because "manage_iam" is tied exclusively to the administrator role. This prevents privilege creep and enforces least-privilege access in the same spirit as AWS IAM’s JSON policies, but expressed at the application layer for clarity and maintainability.

RBAC in Multi-Tenant SaaS Platforms

In SaaS environments, RBAC must not only manage user actions but also enforce strict tenant isolation. A contributor from one company should never gain access to another company’s data, even if their role name matches. Roles such as tenant admin, team lead, contributor, and viewer must always be scoped to the tenant ID at both the application and authorization layers.

With Oso Polar policies, we can model this tenant-aware RBAC directly. Each role is defined relative to a tenant resource, ensuring that permissions cannot leak across organizational boundaries.

‍

‍

Have a look at the example policy of a Multitenant SaaS environment in Polar: 

‍

actor User {}

resource Tenant {
  roles = ["tenant_admin", "team_lead", "contributor", "viewer"];
  permissions = [
    "manage_users", "manage_roles", "manage_billing", "manage_settings",
    "create_project", "manage_project", "assign_contributors",
    "update_task", "add_comment", "upload_file",
    "view_project", "view_task"
  ];

  # tenant admin
  "manage_users" if "tenant_admin";
  "manage_roles" if "tenant_admin";
  "manage_billing" if "tenant_admin";
  "manage_settings" if "tenant_admin";

  # team lead
  "create_project" if "team_lead";
  "manage_project" if "team_lead";
  "assign_contributors" if "team_lead";

  # contributor
  "update_task" if "contributor";
  "add_comment" if "contributor";
  "upload_file" if "contributor";

  # viewer
  "view_project" if "viewer";
  "view_task" if "viewer";
}

‍

Tenant scoping is enforced at runtime by combining user identity and tenant claims, often carried in JWT tokens. Middleware verifies the token, extracts the tenant ID, and ensures that every Oso allow check is executed in the context of the correct tenant resource. 

For example, a contributor from tenant=acme_corp can update tasks in their own projects, but the same role tied to another tenant, such as tenant=globex_inc, has no access to Acme’s data. This guarantees tenant isolation while still supporting flexible, role-based permissions inside each organization.

RBAC in Kubernetes Cluster Management

Kubernetes includes Role-Based Access Control (RBAC) as a first-class feature of the API server, allowing administrators to define which users or service accounts can perform specific actions on resources. This prevents accidental disruptions, such as a developer deleting workloads or modifying cluster-wide configurations. 

Common roles include the cluster admin, who has unrestricted access across all namespaces and resources; the namespace admin, who manages deployments, services, and configurations within a single namespace; the developer, who is restricted to basic workload creation in their assigned namespace; and the auditor, who is limited to read-only visibility of resources, logs, and events.

‍

‍

This RBAC structure can be expressed in Oso Polar, modeling clusters and namespaces as resources, with roles scoped to each resource. Cluster-level roles like cluster_admin and auditor provide broad privileges, while namespace-specific roles like namespace_admin and developer allow finer-grained access. 

Roles can also inherit permissions from higher-level resources, ensuring that a cluster admin automatically gains management permissions in all namespaces. This approach mirrors Kubernetes’ native RBAC system while using Oso’s declarative, testable authorization model.

‍

actor User {}

resource Cluster {
  roles = ["cluster_admin", "auditor"];
  permissions = ["full_access", "read_only"];

  "full_access" if "cluster_admin";
  "read_only" if "auditor";
}

resource Namespace {
  roles = ["namespace_admin", "developer", "auditor"];
  permissions = ["manage_workloads", "create_pods", "view_resources", "list_pods"];

  relations = { cluster: Cluster };

  "manage_workloads" if "cluster_admin" on "cluster";
  "view_resources" if "auditor" on "cluster";

  "manage_workloads" if "namespace_admin";
  "create_pods" if "developer";
  "list_pods" if "developer";
  "view_resources" if "auditor";
"auditor" if "developer";
"developer" if "namespace_admin";
}

# Example Test: Simulate users performing actions
test "developer can create and list pods in assigned namespace" {
  setup {
    has_role(User{"maria"}, "developer", Namespace{"dev"});
    has_relation(Namespace{"dev"}, "cluster", Cluster{"prod"});
  }

  # Developer actions
  assert allow(User{"maria"}, "create_pods", Namespace{"dev"});
  assert allow(User{"maria"}, "list_pods", Namespace{"dev"});
  assert_not allow(User{"maria"}, "manage_workloads", Namespace{"dev"}); # Not allowed
}

test "auditor can view resources but not manage workloads" {
  setup {
    has_role(User{"stephan"}, "auditor", Namespace{"dev"});
    has_relation(Namespace{"dev"}, "cluster", Cluster{"prod"});
  }

  assert allow(User{"stephan"}, "view_resources", Namespace{"dev"});
  assert_not allow(User{"stephan"}, "create_pods", Namespace{"dev"});
  assert_not allow(User{"stephan"}, "manage_workloads", Namespace{"dev"});
}

In this Polar example, maria is a developer who can create and list pods in her assigned namespace but cannot manage workloads, while stephan is an auditor who can view resources but cannot modify or create workloads. Relations link namespaces to clusters, enabling inheritance of cluster-level permissions and ensuring consistent enforcement of least privilege. This model mirrors Kubernetes RBAC behavior in a declarative, testable, and maintainable way.

Challenges with RBAC in Rego

While Role-Based Access Control provides structure and scalability for authorization, implementing it in real-world applications is rarely straightforward. Even experienced developers encounter hurdles when defining, maintaining, and enforcing roles and permissions across complex systems.

Policy Complexity and Syntax Errors

Writing RBAC policies directly in Rego can be error-prone. Small mistakes in indentation, variable naming, or logical operators can result in policies that fail silently or incorrectly deny access. Developers often spend hours debugging why a seemingly correct rule does not grant or restrict access as intended. As the number of roles, resources, and conditional rules grows, the policy code becomes harder to read, test, and maintain.

Example:
A missing array index or a typo in a role name might allow a user to escalate privileges unintentionally. Debugging these subtle errors often requires inspecting the full evaluation trace of the Rego engine, which can be time-consuming.

# Intended policy: only 'admin' can delete repos
allow {
    input.action == "delete_repo"
    input.role == roles[_]   # roles = ["admin"]
}
# Bug: 'admins' typo instead of 'admin'
roles = ["admins"]

In this case, the policy silently fails because "admins" does not match the actual role "admin". Instead of denying access cleanly, the rule never evaluates as expected, which can create confusion during testing. 

Resource and Context Explosion

RBAC roles are static and don’t capture conditions like time, location, or environment. Without attributes layered on top, roles become either too permissive or too restrictive, making the access model misaligned with real-world requirements.

Example:
A developer might have different roles for dozens of repositories, each with slightly different permissions. Without careful abstraction, adding a new repository or changing a permission could require updating multiple Rego rules, introducing the risk of inconsistencies.

Debugging User Reports of Wrong Access

A customer reports that a "project_admin" cannot create new projects. The developer inspects logs but finds no error, Rego simply evaluates the policy as false. To diagnose, they must run opa eval with full input JSON and inspect the trace output. This requires reconstructing the exact request context (user role, resource, action, tenant ID, time-based constraints), which is error-prone and slow under production pressure.

Tools like Oso are designed to simplify these challenges by providing built-in support for roles, hierarchies, and relationships. Instead of hand-coding every policy in a textual language, Oso uses Polar and provides a drag-and-drop, input-driven approach to define roles, permissions, and resource constraints. 

Developers can configure roles and access rules using structured input values rather than manually writing full policy code. These definitions can then be applied directly in the application, reducing the risk of syntax errors and simplifying the process of scaling RBAC examples across multiple resources and environments.

Example: Implementing RBAC with Oso

Oso is an authorization framework designed to make access control easier to implement, maintain, and scale in applications today. Unlike hand-coded policies in Rego or custom checks scattered throughout application logic, Oso provides a centralized, declarative approach using its own policy language, Polar.

Oso allows you to define roles, permissions, and resource constraints in a way that is reusable, auditable, and directly enforceable in your app. Rather than manually writing long conditional statements, you describe what access looks like, and Oso evaluates these rules at runtime.

Let’s understand how to create an RBAC example in Oso:

Step 1: Define Roles and Resources

In the Rules Editor (Workbench mode), you start by selecting the type of resource (e.g., Item) and the actor type (User). Then, you add roles (like viewer or owner) and assign permissions to each role using a form-based interface with drag-and-drop menus.

This policy ensures that users with a given role automatically receive the correct permissions on the resource.

Step 2: Assign Roles to Users

After defining roles and permissions, you assign roles to individual users. Using a form-based interface with drag-and-drop menus, you add facts like:

has_role(User{"alice"}, "viewer", Item{"foo"});

has_role(User{"bob"}, "owner", Item{"foo"});

This visually maps users to roles on specific resources. Oso automatically integrates these assignments into the Polar policy.

Step 3: Make Authorization Decisions

Once roles and permissions are configured, you can check if a user can perform a specific action on a resource. For instance, check if alice has the view permission on Item: foo.

In the interface:

• Select User: alice
• Select Action: view
• Select Item: foo
• Click Check access

Oso evaluates the request against the policy and the assigned roles. The output will indicate whether the action is ALLOWED or DENIED, along with an explanation.

Step 4: Run Tests

The platform allows you to create and run tests to validate your RBAC setup. For example, you can assert:

assert allow(User{"alice"}, "view", Item{"foo"});

assert_not allow(User{"alice"}, "edit", Item{"foo"});

After running the test, Oso shows results directly in the interface, confirming that the roles and permissions are correctly enforced.

‍

Let’s see the dashboard of Oso here:

‍

In this screenshot, the Oso Cloud Rule Editor is being used to model and test Role-Based Access Control (RBAC). A resource called Item is defined with two roles, viewer and owner, and two permissions, view and edit. The policy specifies that a viewer can only view an item, while an owner can both edit and view it (since owners inherit viewer privileges). 

Users are then assigned roles on a specific resource: Alice is assigned the viewer role, and Bob is assigned the owner role on the same Item("example"). To validate these assignments, a test is created that checks different access scenarios. The assertions confirm that Alice can view but cannot edit, while Bob can both view and edit. 

Since all assertions pass, the test shows that the RBAC rules are correctly enforced, preventing unauthorized actions and allowing legitimate ones. Essentially, Oso here is being used to write authorization policies, link roles to permissions, assign users to those roles, and verify that the system enforces the intended access boundaries.

Conclusion

Role-Based Access Control is a reliable framework for managing permissions by assigning them to roles rather than individual users. This approach simplifies access management, ensures consistency, and scales well across complex systems. 

Real-world examples, from project management tools to code hosting platforms, show how users can hold different roles across resources, allowing precise control without administrative overhead.

RBAC can become complex as roles multiply, but hierarchical, resource-scoped, and hybrid RBAC-ABAC models help maintain clarity and security. Tools like Oso further simplify implementation by providing a centralized, declarative interface for defining roles, permissions, and constraints, along with built-in testing to verify access rules. Using structured RBAC models with such tools ensures predictable, secure, and maintainable access control in modern applications.

FAQs

What is Role-Based Access Control (RBAC) and why is it used?

RBAC (Role-Based Access Control) is an authorization model that assigns permissions to roles rather than individual users. Users assume these roles, which simplifies access management, ensures consistency, and reduces the risk of unauthorized access, especially in large or multi-tenant systems.

What is an example of an RBAC role?

A common RBAC role is Project Manager in a project management system. A Project Manager can create tasks, assign work, and close projects. Other roles might include Contributor (can create and update tasks) and Viewer (can only read project status).

What is the difference between an IAM role and RBAC?

IAM roles grant temporary, as-needed permissions in cloud environments, for example, a Lambda function assuming a role to perform a task. RBAC is a broader model where users are assigned roles with associated permissions, usually persistent, though ephemeral roles are possible. Essentially, IAM roles implement RBAC concepts but focus on temporary access.

What challenges can arise when using RBAC ? Can you combine and ABAC?

Over time, RBAC can lead to role explosion, where too many specialized roles are created. This makes it difficult to track who has access to what and can complicate permission management if not carefully maintained.

Introduction

Access control is a cornerstone of application security, ensuring that users only access the resources they are authorized to use. Two widely adopted access control models are Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC). While both models aim to secure systems and data, they differ significantly in how they assign and manage permissions.

In this article, we’ll explore the key differences between RBAC and ABAC, their use cases, and how to decide which model—or combination of models—might be the best fit for your organization. Whether you’re looking for a straightforward, role-based solution or a more flexible, attribute-driven approach, this guide will help you make an informed decision.

If you’re short on time, check out the TL;DR section or the video below for a quick summary of the main differences.

TL;DR: Quick Comparison of RBAC vs ABAC

‍

What is RBAC?

Role-Based Access Control (RBAC) is a widely used authorization model that simplifies access management by grouping permissions into roles. A role is essentially a collection of permissions that defines what actions a user can perform on specific resources. For example, roles like "Admin," "Editor," or "Viewer" might grant varying levels of access to a system.

When a user is assigned to a role, they inherit all the permissions associated with that role. This makes RBAC an intuitive and efficient way to manage access, especially in organizations with well-defined job functions or hierarchical structures.

Key Features of RBAC:

• Simplified Permission Management: Instead of assigning individual permissions to users, permissions are grouped into roles, which can then be used to assign multiple permissions to a user at once.
• Ease of Implementation: RBAC is straightforward to set up and manage, making it a popular choice for organizations with stable, predictable access requirements.
• Improved Security: By limiting access based on a user’s role, RBAC reduces the risk of unauthorized access and enforces the principle of least privilege.

Example Use Case:

Imagine a content management system where:

• Admins can create, edit, and delete content.
• Editors can modify existing content but cannot delete it.
• Viewers can only read content.

By assigning users to these roles, the organization can efficiently manage access without needing to define permissions for each individual user.

Pros and Cons of RBAC:

• Pros:
  • Easy to understand and manage.
  • Scales well for organizations with clear role definitions.
  • Reduces administrative overhead by grouping permissions.
• Cons:
  • Less flexible for dynamic or complex environments.
  • Can become cumbersome if roles proliferate without proper management.

RBAC is often seen as a foundational model for access control. However, as we'll explore later, it can also be viewed as a specific implementation of Attribute-Based Access Control (ABAC), where the "role" is treated as just one of many possible attributes.

For a more detailed explanation of RBAC, including its implementation and use cases, check out our Role-Based Access Control guide.

What is ABAC?

Attribute-Based Access Control (ABAC) is an advanced authorization model that provides fine-grained access control by evaluating a variety of attributes. Unlike RBAC, which relies solely on roles, ABAC considers multiple attributes related to the user, the resource, and the environment to make access decisions.

Key Features of ABAC:

• Granular Control: ABAC allows for dynamic access policies based on attributes such as user identity, role, department, location, time of access, and more.
• Flexibility: This model supports complex scenarios where access needs to be adjusted based on changing conditions or contexts.
• Dynamic Authorization: ABAC policies can be tailored to accommodate specific business rules, making it ideal for environments with evolving access requirements.

Example Use Case:

Consider a healthcare application where access to patient records is controlled based on:

• User Role: Doctors and nurses have different levels of access.
• Location: Access is granted only within the hospital network.
• Time: Access is restricted to working hours.

By evaluating these attributes, ABAC can enforce nuanced access policies that adapt to the specific needs of the organization.

Pros and Cons of ABAC:

• Pros:
  • Provides comprehensive and adaptable access control.
  • Supports complex policies that reflect real-world scenarios.
  • Enhances security by considering multiple factors in access decisions.
• Cons:
  • Requires careful planning and management to implement effectively.
  • Can be more complex to set up compared to RBAC.

ABAC expands upon the basic principles of RBAC by incorporating attributes into the mix, allowing organizations to create more granular and dynamic authorization policies. This flexibility makes ABAC particularly suitable for environments where access needs are complex and subject to frequent changes.

For a deeper dive into ABAC, including its benefits and implementation strategies, check out our Attribute-Based Access Control guide.

Real-World Challenges with RBAC and ABAC

While both RBAC and ABAC are powerful models for managing access, they each come with challenges that you should consider when deciding which to use.

Challenges with RBAC

1. Role Explosion:
   • In large organizations, the number of roles can grow exponentially as more granular permissions are needed. This "role explosion" makes managing roles and permissions increasingly complex and difficult to scale.
   • For example, a company with multiple departments may need separate roles for "Manager," "Team Lead," and "Employee" in each department, quickly leading to hundreds of roles.
2. Lack of Flexibility:
   • RBAC is rigid and works best in environments where roles and permissions remain stable over time. It’s not well suited for dynamic or context-specific access needs, such as granting access based on time, location, or project status.
3. Over-Permissioning:
   • Users are often assigned roles that grant more permissions than they actually need, increasing security risks. This happens because RBAC lacks the granularity to fine-tune access for specific scenarios.

Challenges with ABAC

1. Policy Complexity:
   • ABAC policies can become highly complex as they incorporate multiple attributes (e.g., user role, location, time, and resource sensitivity). Writing and maintaining these policies requires significant effort and expertise.
   • For instance, defining a policy that grants access only to "senior managers in the finance department during business hours" involves multiple attributes and conditions.
2. Performance Concerns:
   • Evaluating access requests in ABAC can be resource-intensive, especially when dealing with a large number of attributes or complex conditions. This can impact system performance, particularly in high-traffic environments.
3. Implementation Overhead:
   • Implementing ABAC requires a deeper understanding of the organization's data and workflows to identify the right attributes and conditions. This can make adoption slower and more challenging compared to RBAC.

RBAC vs. ABAC: Key Differences

Both Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) are widely used access control models, but they differ significantly in how they manage permissions. Understanding these differences can help you choose the right model for your organization’s needs.

1. How They Work

• RBAC: Access is granted based on roles. Users are assigned predefined roles (e.g., "Admin," "Editor," "Viewer"), and permissions are tied to those roles.
• ABAC: Access is granted based on attributes. These attributes can include user roles, resource types, environmental factors (e.g., time, location), or any other relevant criteria.

2. Flexibility

• RBAC: Offers a simple and intuitive structure for managing access. It works well in environments where roles are stable and clearly defined.
• ABAC: Provides dynamic and fine-grained control by evaluating multiple attributes. This flexibility allows ABAC to adapt to changing conditions and enforce nuanced access policies.

3. Complexity

• RBAC: Easier to implement and manage because it relies on a straightforward role hierarchy. However, it can become cumbersome if too many roles are created.
• ABAC: More complex to set up and maintain due to the need to define and manage multiple attributes and policies. This complexity is the trade-off for its adaptability and precision.

4. Use Cases

• RBAC: A retail company assigns permissions based on job roles
  • Store managers can access sales reports and manage inventory.
  • Cashiers can process transactions but cannot access financial data.
• ABAC: A healthcare system controls access to patient records
  • Doctors can access patient records only during their shifts and within the hospital network.
  • Nurses can view records for patients assigned to their care but cannot edit them.
  • Access is denied if the request comes from outside the hospital’s secure network.

When to Use RBAC vs ABAC

Choosing between Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) depends on your organization’s structure, security requirements, and the complexity of your access control needs. Each model has its strengths and is suited to different scenarios.

When to Use RBAC

RBAC is ideal for organizations with static access requirements and clearly defined roles. It works well in environments where simplicity and ease of management are priorities. Consider using RBAC if:

• Your organization has stable roles: For example, a company where employees have fixed roles like "HR Manager," "IT Support," or "Sales Associate."
• You need a straightforward implementation: RBAC is easier to set up and manage, especially for smaller teams or organizations with limited engineering resources.
• Your access needs are predictable: If permissions rarely change or are tied directly to job functions, RBAC provides a reliable and efficient solution.

When to Use ABAC

ABAC is better suited for organizations with dynamic and complex access needs. It provides fine-grained control by evaluating multiple attributes, making it ideal for environments where access requirements frequently change. Consider using ABAC if:

• Your organization requires granular control: For example, access policies need to account for attributes like user location, time of access, or the sensitivity of the resource.
• You operate in a highly regulated industry: ABAC can enforce compliance by tailoring access policies to meet specific regulatory requirements (e.g., HIPAA, GDPR).
• Your access needs are context-dependent: ABAC can dynamically adjust permissions based on real-time conditions.

Combining RBAC and ABAC for Better Authorization

At Oso, we recognize that modern organizations often require a combination of access control models to meet their unique needs. While RBAC and ABAC are widely used, many organizations benefit from a hybrid approach—combining the simplicity of RBAC with the flexibility of ABAC. For systems where relationships between entities play a key role, they can even incorporate ReBAC (Relationship-Based Access Control). Learn more about ReBAC and how it works here.

When implementing your hybrid model, start with RBAC to define broad permissions, then layer ABAC policies for dynamic access control. For example, assign a 'Team Member' role with baseline permissions and use attributes like project status or user location to refine access.

Why Use a Hybrid Approach?

A hybrid approach allows you to:

• Simplify baseline access management: Use RBAC to define broad permissions based on roles, such as "Admin," "Manager," or "Employee."
• Add granularity and adaptability: Layer ABAC on top of RBAC to refine access policies based on attributes like location, time, or resource sensitivity.
• Balance ease of management with precision: By combining the two models, you can avoid the complexity of managing numerous roles while still enforcing dynamic, context-aware access policies.

This approach is particularly useful in environments where:

• Roles alone are insufficient: For example, when access needs to account for real-time conditions or regulatory requirements.
• Flexibility is critical: Organizations with dynamic access needs, such as global enterprises or industries with strict compliance standards, benefit from the adaptability of ABAC.

Example Use Cases for a Hybrid Approach

1. Enterprise with Regional Restrictions
   • RBAC: Assign employees roles like "Regional Manager" or "Team Lead."
   • ABAC: Enforce additional policies to restrict access to data based on the user’s location, ensuring compliance with regional regulations.
2. Healthcare System
   • RBAC: Define roles such as "Doctor," "Nurse," and "Administrator."
   • ABAC: Add attributes to control access to patient records based on the user’s shift hours, department, and the sensitivity of the data.
3. SaaS Application
   • RBAC: Assign roles like "Admin," "Editor," and "Viewer" to manage baseline permissions.
   • ABAC: Use attributes like subscription tier, account status, or geographic location to customize access for specific users.

How Oso Supports Hybrid Models

Implementing a hybrid model can seem daunting, but Oso’s Authorization as a service platform is designed to make it seamless, combining the simplicity of RBAC, the flexibility of ABAC, and even the relationship-driven granularity of ReBAC. With Polar, Oso’s declarative configuration language for authorization, you can define and enforce both role-based and attribute-based logic in a single policy, ensuring efficient and scalable access control.

By adopting a hybrid approach, organizations can achieve the best of both RBAC and ABAC, addressing real-world challenges while maintaining security and flexibility.

Example: Using Polar to Implement a Hybrid Model

Let’s say you’re building an application for a project management platform. You want to combine RBAC, ABAC, and ReBAC to manage access to project resources. Here’s how you could do it with Oso and Polar:

RBAC for Baseline Permissions:

1. Define roles like "Project Manager," and “Member."
2. Use Polar to write rules that grant basic permissions based on these roles. For example:

# Define Actor (User)
actor User {}

# Define Resource (Project)
resource Project {
  permissions = ["read", "update", "delete", "member.add", "member.remove"];
  roles = ["member", "project_manager"];

  # Role permissions
  # project managers can do everything members can do
  "member" if "project_manager";

  # project manager permissions
  "delete" if "project_manager";
  "member.add" if "project_manager";
  "member.remove" if "project_manager";

  # member permissions
  "read" if "member";
  "update" if "member";
}

‍

ABAC for Attribute-Based Refinements:

1. Add attributes like project status (e.g., "Active" or "Archived") and user location.
2. Refine access policies based on these attributes. For example:

# Define Actor (User)
actor User {}

# Define Resource (Project)
resource Project {
  permissions = ["read", "update", "delete", "member.add", "member.remove"];
  roles = ["member", "project_manager"];

  # Attribute-based permissions
  # All users can read public projects
  "read" if is_public(resource);

  # Role-based permissions
  # project managers can do everything members can do
  "member" if "project_manager";

  # project manager permissions
  "delete" if "project_manager";
  "member.add" if "project_manager";
  "member.remove" if "project_manager";

  # member permissions
  "read" if "member";
  "update" if "member";
}

‍

ReBAC for Relationship-Based Control:

1. Incorporate relationships between users and resources, such as team assignments or ownership.
2. Use Polar to enforce permissions based on these relationships. For example:

# Define Actor (User)
actor User {}

# Define Resource (Team)
resource Team {
  roles = ["member"];
}

# Define Resource (Project)
resource Project {
  permissions = ["read", "update", "delete", "member.add", "member.remove"];
  roles = ["member", "project_manager"];

  # A project can be associated with a team
  relations = {team: Team};

  # Relationship-based permissions
  # Members of a team that owns a project can view the project
  "read" if "member" on "team";

  # Attribute-based permissions
  # All users can read public projects
  "read" if is_public(resource);

  # Role-based permissions
  # project managers can do everything members can do
  "member" if "project_manager";

  # project manager permissions
  "delete" if "project_manager";
  "member.add" if "project_manager";
  "member.remove" if "project_manager";

  # member permissions
  "read" if "member";
  "update" if "member";
}

By combining these models, you can create a powerful and flexible authorization system that meets the needs of your application.

Why Use Oso for Hybrid Models?

• Ease of Implementation: Oso’s Polar language makes it simple to define and enforce complex policies.
• Flexibility: Combine RBAC, ABAC, and ReBAC seamlessly to handle a wide range of access control scenarios.
• Scalability: As your application grows, Oso’s tools make it easy to adapt your policies to new requirements.

Conclusion

Choosing the right access control model—RBAC, ABAC, or a combination of control models—depends on your organization’s specific needs. RBAC offers simplicity and ease of management, making it ideal for environments with stable roles and predictable access requirements. On the other hand, ABAC provides the flexibility and granularity needed for dynamic, attribute-driven scenarios.

For many organizations, a hybrid approach that combines RBAC and ABAC delivers the best of both worlds. By using roles as a foundation and layering attributes for fine-grained control, you can create an access control system that is both powerful and easy to manage. Additionally, incorporating models like ReBAC into a hybrid solution can further enhance your ability to enforce relationship-driven permissions.

At Oso, we make it easy to implement these models with tools like Polar, enabling you to define and enforce policies that meet the demands of modern applications. Whether you’re managing a small team or a global enterprise, Oso provides the flexibility and scalability you need to secure your systems effectively.

Ready to take your authorization to the next level? Explore our Authorization Academy or learn more about how Oso can help you build a robust access control system.

‍

TL;DR

• Role-Based Access Control (RBAC) is a method of managing user permissions by assigning users to roles, where roles are granted specific permissions to act on resources such as API endpoints, database records, and cloud infrastructure objects.
  
  
• RBAC is important in production environments because it enforces the principle of least privilege, cutting down on security incidents, misconfigurations, and accidental over-provisioning. By restricting each user or service to only the actions they’re authorized to perform, you get a system whose behavior is stable and auditable, you know exactly who can do what, and surprise changes are far less likely.
  
  
• Implementing RBAC is easiest with a centralized access policy engine (for example, Oso) that enforces the same rules across all parts of your application, APIs, microservices, and frontend components. This eliminates scattered access control logic and keeps enforcement consistent throughout the entire stack.
  
  
• RBAC policies must be enforced at the backend (API) to guarantee security and consistency. The frontend (UI) can adapt dynamically to a user’s role, hiding or disabling actions they aren’t allowed to perform, but this is purely for usability. True enforcement always happens at the API layer.
  
  
• Hand-rolling access control logic becomes unmanageable at scale, leading to inconsistencies, poor auditability, and security risks. A centralized RBAC engine like Oso simplifies management by defining a robust policy module so that one need not to reinvent the wheel, making it auditable, scalable, and easier to maintain.
  
  
• When RBAC is implemented through a central policy engine, you can unit-test every permission rule in one place and immediately apply changes across all APIs, microservices, and front-end components. Adding a new role or resource becomes a single policy update instead of dozens of scattered code edits. This approach keeps access decisions consistent, auditable, and predictable as your system grows.

When building internal tools at scale, whether it’s a developer portal, an audit dashboard, or a CI/CD orchestrator, access control quickly stops being a feature and becomes a risk surface. In a past role, I worked on a multi-tenant deployment platform used by dozens of internal teams. A misconfigured authorization rule allowed a junior engineer to deploy to production instead of staging, a classic example of how fragile hand-rolled RBAC can lead to real security incidents. It wasn’t malicious, but it took down a customer-facing API. Most access-related incidents stem not from code defects, but from the absence of proper contextual enforcement and boundary controls. 

In a lifecycle, especially one that’s regulated or customer-facing, the strategic imperative is not whether to adopt RBAC, but how to implement it early without disrupting operational continuity. From developer environments to admin consoles and feature toggles, every internal interface becomes a potential vector for misuse. Engineers, platform teams, and security leaders all want the same thing: to move fast without sacrificing control. RBAC offers a structured way to scale those guarantees.

This post is for DevSecOps leads, product security engineers, and platform architects who’ve either implemented or are planning to roll out RBAC in their stack. We’ll walk through how to do RBAC properly, at the code level, across environments, and with real UI examples, using a sample app we built from scratch: a small e-commerce product-catalog demo implemented with Next.js (Next API routes + React frontend), Node/Express-style handlers, PostgreSQL, JWT authentication, and Oso as the centralized policy engine. Instead of hand-writing permission checks across controllers, routes, and UI components, we implemented policies once in Oso (the .polar file), wired the app to call isAllowed(user, action, resource) from server routes, and then surfaced role-aware controls in the Next.js UI. That means you can see exactly how much boilerplate, edge cases, and brittle logic Oso replaces, things you would otherwise have to design, implement, and test yourself (role mapping, environment scoping, audit trails, revocation, partial evaluation and caching, etc.). Along the way we’ll discuss tradeoffs of hand-rolled logic, show how Oso simplifies role-based access management, and spell out what “enterprise-ready” RBAC looks like in practice.

What Is RBAC?

RBAC (Role-Based Access Control) is an authorization model designed to manage who has access to what in a system. Rather than assigning permissions directly to individual users (which quickly becomes unmanageable), RBAC introduces an abstraction:

• Users are assigned to roles: Each user inherits permissions by belonging to a role like Viewer, Editor, or Admin.
  
  
• Roles are granted permissions: A role defines which actions (read, edit, delete) are allowed.
  
  
• Permissions are scoped to resources or actions: Permissions apply to specific resources (e.g., product, feature flag) and the actions performed on them.

This creates an access system that scales cleanly as your app grows. For example, a user with the Collaborator role can edit product details or post comments, but they can’t delete products, that action is reserved for Owners. The system doesn’t check for individual user IDs (e.g., “is user123 the product creator?”); instead, it checks the user’s role against the policy attached to that role. By avoiding hardcoded checks like “only the creator of this product may delete it”, you remove scattered exceptions and let Oso enforce consistent rules across every endpoint. When a role’s permissions change, the new behavior applies immediately without rewriting business logic.

Why RBAC is Important

Without access boundaries, everything becomes a potential point of failure: not just the services, but the humans operating them. Teams accidentally ship to the wrong environment, over-provision infrastructure, or expose sensitive data, often because they had more access than necessary.

RBAC enforces the principle of least privilege, which says users should only have the minimum permissions needed to do their jobs. For example, in a product catalog app, a Viewer can read product listings but can’t edit or delete them; a Collaborator can update descriptions or add comments but still can’t remove products; and only an Owner has full control, including deletion. This role separation limits the blast radius of mistakes (a Viewer can’t accidentally wipe data), keeps behavior predictable, and gives security teams confidence that access is consistently enforced without blocking day-to-day work.

Overview of RBAC Architecture

In a well-structured production system, Role-Based Access Control (RBAC) shouldn’t be scattered as if/else checks deep inside application code. It should be treated as its own dedicated service or infrastructure layer, on the same footing as your identity provider and authentication mechanism. RBAC acts as the policy-enforcement counterpart to authentication, while principles such as environment isolation (separating dev, staging, and prod) define the boundaries in which that layer operates. This section walks through how a role-based access control system fits into a modern stack, how it interacts with the rest of the infrastructure, and where each responsibility actually lives in practice.

The following architecture supports fine-grained authorization across a distributed stack:

1. Identity Provider (e.g., Auth0)

The flow begins with the Identity Provider, such as Okta or Auth0, which handles user authentication. After the user logs in, the Identity Provider issues an identity token (e.g., JWT) containing user information like ID, email, and sometimes role metadata.

2. App/API

After successful authentication, requests are forwarded to the App/API layer, which acts as the initial entry point for processing the request. The App/API interacts with the Access Policy Engine to check permissions before taking any further action.

‍

3. Access Policy Engine (Oso/OpenFGA)

This is where role-based access decisions are made. The engine evaluates whether a specific user is authorized to perform a certain action on a given resource (e.g., “Can this user update this document?”). It could be a system like Oso, OpenFGA, or a custom-built solution.

4. Permission DB (PostgreSQL)

The Access Policy Engine queries the Permission Database to evaluate relationships between users, resources, and actions. For example, it checks whether "User A" has permission to "Update" a specific resource or if "Collaborator" has permission to "Delete a comment." The Permission DB is optimized for fast lookups and stores this mapping information, often populated by role assignments or sync jobs.

5. Final Decision

The Access Policy Engine processes the permission check and returns a final authorization decision. The App/API then either proceeds with the requested operation or returns a 403 Forbidden error if the user is not authorized to perform the action.

‍

6. RBAC-Aware Frontend (Next.js)

The frontend, built with Next.js or similar frameworks, adjusts its UI based on the user's roles or permissions. It ensures that only the relevant UI elements (e.g., buttons, forms, pages) are visible or interactive, aligning with the backend's access control decisions to maintain a consistent user experience.

Implementation Principles for RBAC in a Microservices Stack

Beyond the high-level flow, it helps to ground this in a real business use case. Assume a product catalog app where different users, Owners, Collaborators, and Viewers, need different levels of access to products and comments. Owners can add or remove products, Collaborators can edit and comment, and Viewers can only browse. On the surface, this sounds simple, but if you tried to hardcode these rules into every API route, frontend component, and database query, it would quickly become complex, brittle, and time-consuming to maintain.

That’s why we built this demo app with Oso. Instead of reinventing the wheel or writing a custom authorization framework from scratch, we used Oso’s open-source policy engine to centralize and declare all role logic at once. The app itself is deliberately lightweight, Next.js frontend, Node/Express-style API routes, and PostgreSQL for persistence, but it demonstrates how even a “small” product can benefit from a dedicated RBAC layer. With Oso handling the rules, the implementation becomes practical, auditable, and easy to extend, which is what you need in a production microservices stack.

1. Identity and Authentication

Every access control system begins with identity. Users must be authenticated before any permissions can be evaluated. Most production systems rely on an Identity Provider (IdP) such as Okta, Auth0, or an internal OIDC-compliant service. Once a user is authenticated, the IdP issues a token (typically a JWT) containing identity claims like user ID, email, organization ID, and sometimes role identifiers. These identity claims are then passed downstream to any service requiring authorization logic.

In our demo app, this process starts at the login page (screenshot above). A user signs in with their email and password, the app verifies their credentials, and a JWT is issued containing their user ID and assigned role (Owner, Collaborator, or Viewer). That token is then included in all subsequent requests to the backend, where Oso evaluates whether the user is allowed to perform the requested action.

2. App/API Layer

After authentication, requests flow into the App/API, which acts as the main entry point for business logic. At this stage the application does not decide permissions on its own. Instead, it forwards the user identity and requested action to the authorization layer. This separation avoids oversized, permission-stuffed tokens and keeps enforcement auditable.

Oso’s recommended patterns include:

1. Let services fetch authorization data as needed. Each microservice requests permission info when required, rather than relying on outdated or oversized tokens.
   
   
2. Use an API gateway to forward identity context. The gateway only handles authentication and passes identity, not permissions, to services, letting them evaluate access with fresh policy data.
   
   
3. Centralize authorization logic in one service. Services decide whether an action is allowed by calling a shared policy engine (like Oso) that combines roles, resource context, and environment data.

This approach ensures decisions reflect the most current permissions, avoids token bloat, and keeps your authorization logic auditable and maintainable across services.

If a user with access Y is trying to access resource X, it throws an access denied message.

The key advantage of having a separate RBAC engine is that the logic becomes reusable, auditable, and environment-aware. Whether you’re calling it from a backend route, an internal tool, or a CLI-based automation script, the permission logic remains consistent. This separation of concerns also makes it easier to manage and evolve your role based access control model over time, as permissions change or new roles are introduced.

Here, we showed how that token flows into backend routes, using Postman to test requests like “view product” or “edit product.” Those tests made it clear that identity alone isn’t enough, we still need a consistent way to decide what that user can do once authenticated.

That’s where the RBAC engine comes in. The key advantage of separating authorization into its own engine is that the logic becomes reusable, auditable, and environment-aware. Whether you’re calling it from a backend route, an internal tool, or a CLI-based automation script, the same permission logic applies everywhere. This separation of concerns makes it easier to evolve your RBAC model over time, as roles change or new ones are introduced.

3. Access Policy Engine (Oso/OpenFGA)

The policy engine is where authorization actually happens. Given (user, action, resource), it evaluates whether the operation is permitted based on centrally defined policies. For example, Oso lets you encode:

allow(user, "update", product) if user.role = "collaborator";
allow(user, "delete", product) if user.role = "owner";

On the frontend, the app doesn’t enforce authorization, but it still needs to mirror backend rules for a smoother user experience. For example, if a user is a Viewer, the “Edit Product” button should already be greyed out rather than throwing a 403 after they click it. This prefetching of effective permissions ensures the UI matches what the backend enforces, reducing errors and confusion.

4. Role and Permission Store (e.g., PostgreSQL)

A persistent store underpins the policy engine, tracking user-role assignments and mapping them to resources. This store (often backed by PostgreSQL or similar) captures relationships like role inheritance, project scoping, or environment-specific restrictions. Defining permissions declaratively in version-controlled policy files provides auditability, clarity, and maintainability.

This store also plays a critical role in providing auditability. By tracking which roles exist, what permissions they hold, and how they’re used, the system can generate logs and reports for compliance and debugging purposes. Every permission decision can be traced back to a clearly defined rule or role mapping, reducing ambiguity when things go wrong.

5. Final Decision

After evaluation, the policy engine returns an allow/deny decision. The App/API enforces this outcome: if permitted, the request continues; if not, it returns a 403 Forbidden. Every decision can be logged, giving you an audit trail of who tried to do what and when.

6. RBAC-Aware Frontend (Next.js)

While the frontend may receive minimal role or identity information (e.g. "role": "collaborator"), it should never enforce access control directly. Instead, the UI adapts behavior, such as hiding buttons or disabling actions, for better user experience.

However, all authorization decisions must still be enforced in the backend, where the service calls into Oso’s policy engine (e.g. isAllowed(user, action, resource)) to validate whether the requested operation is permitted. This guarantees consistency, auditability, and prevents misuse via tools like Postman or cURL.

By avoiding client-side permission caching or local storage of permission hashes, the system maintains a single, centralized source of truth for all access logic: declarative, testable, and enforceable.

Up to this point, we’ve focused on the app-level flow, login, backend checks with Oso, role storage, and a frontend that adapts to permissions. That gives us a clear view of how RBAC works within a single application. But in production, you rarely have just one app. You’re running multiple services behind gateways, identity providers, and caches.

To understand how centralized RBAC holds everything together in that larger picture, let’s step back and look at how it fits into a modern microservices architecture.

How Centralized RBAC Fits Into a Modern Architecture

This diagram represents a role-based access control (RBAC) system architecture implemented across a microservices-based backend, with an API Gateway, Authn Server, Token Store, and local caching at multiple layers. Here's a step-by-step explanation of how it works:

1. User Logs In & Receives Identity Token

The user authenticates through an Identity Provider (IdP) like Okta or Auth0. Upon successful login, the IdP issues an identity token (typically a JWT) containing basic user claims, such as user ID and email, but not full access rights or roles. This token is strictly used for authentication, not for enforcing permissions.

2. Authorization Happens at the Service Layer, Not the Gateway

The API Gateway acts as a routing layer. It forwards requests to the relevant backend microservices without making any authorization decisions itself. Unlike traditional architectures that rely on token-scoped permissions at the gateway level, this model ensures that all access control logic is centralized and auditable.

3. Microservices Query Oso for Access Decisions

When a service (e.g., Inventory Service, Product Service) receives a request, it performs an authorization check by invoking isAllowed(user, action, resource) on Oso. Oso evaluates the request against its .polar policy file to determine whether the action should be permitted.

This dynamic, runtime evaluation ensures that:

• Permissions are always up-to-date
  
  
• Access rules are centrally defined and enforced
  
  
• There's no risk of permission drift across environments

4. Optional: Caching at the Policy Layer (Not Gateway)

To improve performance, caching is employed inside the authorization engine (e.g., Oso Cloud) for stable parts of policy execution (such as policy compilation) so redundant work is minimized. Some optimizations include visibility into policy versioning (so you can see when policies update) and support for time-based access expiry.

For example:

• The cache key isn’t just (user, action, resource) but also the policy version or relationship graph version used to compute the decision. That way, if a policy changes or a relationship is updated, the cache can be invalidated or refreshed automatically.
  
  
• The service can merge cached facts with fresh facts. E.g., if it already knows the user’s roles but needs a fresh attribute from a DB, it can combine them before evaluation, something a gateway cache can’t do without understanding the policy model.
  
  
• The service can implement smart TTLs or event-driven invalidation based on policy/relationship changes. From the outside you’d have to guess, but inside the authz service you know exactly when something makes cached decisions stale.

5. UI and API Stay Synchronized

Since all authorization decisions are made per request and per resource by Oso, both the frontend and backend operate off the same access logic. The UI can query what the current user is allowed to do and render controls accordingly, while the API enforces those rules regardless of frontend behavior.

Contemporary security architectures abstract authorization into policy engines, eliminating hand-written, route-level access checks:

• Role mapping per microservice
  
  
• Vector DB filters for RAG-based access control
  
  
• Ad hoc policy checks inside LLM toolchains

Instead, you plug into a declarative, unified access layer, like Oso, and make authorization an API, not a part of your codebase. This architecture eliminates scattered permission checks and gives you a scalable foundation for consistent access enforcement across services and interfaces.

Why You Shouldn’t Hand-Roll Authorization Anymore

But even with the right architecture, how you define and enforce policies still determines success. Here's why centralized, declarative authorization is now the baseline, and why hand-rolled logic no longer cuts it.

1. Why Hand-Rolled Authorization Always Breaks First

Authorization used to be baked directly into the application layer. Every microservice had its own version of role mapping. Routes were guarded with one-off isAdmin checks. Access was defined in YAML files, controller logic, and conditional middleware scattered across codebases. It may have worked in the early days, but once you’re managing multiple services, environments, and personas, that approach turns into a liability. There’s no single source of truth, no audit trail, and no consistency across the stack.

As soon as new components like internal admin panels, agent-based automation, or AI orchestration chains are introduced, the old model breaks entirely. Each part of the system ends up reinventing access control in its own silo. And that makes it impossible to reason about, or enforce, security at scale.

2. Centralized Policy Is the New Baseline

Modern authorization is externalized into a unified access layer. Instead of encoding roles and permissions directly into app logic, you define policies declaratively, using a tool like Oso, OpenFGA, or Cedar. These tools let you describe RBAC rules in a structured language. You define roles, permissions, relationships, and scopes in a way that’s consistent and testable. Then you integrate the policy engine as an API that your services, tools, and agents can call in real time.

You don’t repeat logic across your backend, frontend, and automation layers. Access decisions are made programmatically and deterministically, eliminating ambiguity and ensuring policy fidelity. This approach turns authorization into infrastructure, not a set of scattered decisions.

Step-by-Step: Implementing the RBAC Layer

The project is structured around a classic fullstack architecture: Express.js for the backend API, PostgreSQL as the database layer, and a frontend UI built with Next.js. We chose this stack to demonstrate how RBAC enforcement can be cleanly embedded into real-world app layers, not just as a backend filter but as an end-to-end access boundary. The user management flow includes registration, login, and protected routes, all wired to a simple JWT-based session system. Authentication happens first, and role-based authorization follows immediately after.

1. Define roles & permissions (claims vs. enforcement)

Users are assigned one of four roles, owner, collaborator, viewer, developer, persisted in PostgreSQL. At login, the role is issued as an identity claim in the JWT so the frontend can render the right controls. We never authorize the token. On every request, the API loads the user & target resource from PostgreSQL and asks Oso, via isAllowed(user, action, resource). This keeps identity in the token and authorization in policy. (See Oso request-level enforcement.)

The owner role grants full permissions, including viewing, commenting, editing, and deleting any product in the system.

The collaborator role allows the user to view and comment on products, and make limited edits, but lacks deletion privileges.

The user is assigned the viewer role, which grants read-only access across the application without permissions to comment, edit, or delete.

The developer role is a special-purpose role with scoped access for debugging or staging environments, not intended for production changes.

2. Wiring Oso into the Backend Authorization Flow

At the core of our access control system is Oso, a policy engine that defines access logic in a .polar file.

Each permission check boils down to one question:

“Is this user allowed to perform this action on this resource?”

To evaluate that, we:

1. Retrieve both the user and the resource from PostgreSQL.
   
   
2. Wrap them into domain-specific objects (OsoUser, OsoProduct).
   
   
3. Invoke the isAllowed() method via our authorization service wrapper.

Oso checks the policy rules and returns yes/no, no conditional branching or role checks cluttering the controller logic.

# User roles
allow(user, "read", _product) if user.role in ["owner", "collaborator", "viewer", "developer"];

allow(user, "create", _product) if user.role = "owner";

allow(user, "update", _product) if user.role in ["owner", "collaborator"];

allow(user, "delete", _product) if user.role = "owner";


# Comment permissions
allow(user, "comment", _product) if user.role in ["owner", "collaborator"];

allow(user, "read", _comment) if user.role in ["owner", "collaborator", "viewer", "developer"];

allow(user, "delete", comment) if 
  user.role = "owner" or 
  (user.role = "collaborator" and comment.authorId = user._id);

# User management (only owners can manage users)
allow(user, "manage_users", _) if user.role = "owner";

3. Enforcing Access Across Frontend and API

Once the authorization engine is in place, we connected the frontend to reflect the same access rules visually. After login, users are shown their role in the profile view. Based on that role, certain actions become available or hidden. 

For role-based access control example:

• Owners can delete products.
  
  
• Collaborators may see an edit button but no delete option.
  
  
• Developers get read/update permissions only in staging and cannot delete in production.
  
  
• Viewers remain strictly read-only.

Policy changes are centrally managed within the .polar file, ensuring consistent, maintainable enforcement.

# User roles
allow(user, "read", _product) if user.role in ["owner", "collaborator", "viewer", "developer"];

allow(user, "create", _product) if user.role = "owner";

allow(user, "update", _product) if user.role in ["owner", "collaborator"];

allow(user, "delete", _product) if user.role = "owner";

# Comment permissions
allow(user, "comment", _product) if user.role in ["owner", "collaborator"];

allow(user, "read", _comment) if user.role in ["owner", "collaborator", "viewer", "developer"];

allow(user, "delete", comment) if 
  user.role = "owner" or 
  (user.role = "collaborator" and comment.authorId = user._id);

# User management (only owners can manage users)
allow(user, "manage_users", _) if user.role = "owner";

These visual controls are purely cosmetic: the real enforcement happens in the backend, but they help create a role-aware interface that prevents user confusion or error. And since permissions are checked again in every API call, there’s no way to bypass access via tools like Postman or cURL.

4. Centralizing and Simplifying Policy with Oso

Instead of scattering role checks across controllers, all access rules live inside authorization.polar. This becomes the single source of truth for permissions.

For example, if we want to give collaborators delete permissions in the future, we’d edit one line in the .polar file, reload the policy, and the entire app respects the new rule, no middleware rewrites needed.

5. Testing the System and Validating Role Behavior

To test the full flow, users can register with different roles either through the /register route in the frontend or directly via the API. 

Once logged in, their role and access level are reflected on the /profile page. From there, they can access /products to view items, attempt edits, or post comments, depending on their permissions. 

This is the main product listing screen where users can view all available products along with their status, category, and creation date.

The comment section allows users to read or add comments for a specific product, with RBAC deciding who can post or delete.

Users with appropriate permissions can access detailed metadata views, showing full metadata like status, creation date, and last modified timestamp.

This modal provides fields for editing product details like name, description, category, and status, editable only if the user’s role permits it.

Only users with the appropriate role (e.g. Owner) see the “Delete Product” action in the dropdown, enforced both in UI and backend.

Every action hits a protected backend endpoint, which consults the Oso engine before proceeding. Unauthorized actions result in a 403 response, and authorized ones continue to the business logic layer. This flow enforces that access control is not optional or assumed, it’s part of the request lifecycle.

Core Concepts in RBAC

When designing access control, roles, permissions, and resources define exactly who can create a project, edit someone else’s comment, or even see that a project exists at all.

In our e-commerce product catalog system, the resource is the Product entity and its associated metadata (comments, visibility status, creation time). Each product lives in a system where access isn’t flat; it varies per user, depending on what role they’ve been assigned.

The actions on these resources include create, edit, delete, comment, and view. For example, an Owner can create and delete projects; a Collaborator can’t create new projects but can still comment and make edits; a Viewer can only observe, no mutations allowed.

We’ve broken the system into clear roles to reflect common collaboration patterns in product teams:

‍

Imagine these roles like access cards in a secure office building. A Viewer has a guest pass, able to walk around and observe, but not touch anything. A Collaborator is like a contractor with a desk, they can make edits, leave notes, and work on existing assets. An Owner holds the master key: they manage the layout, invite others, and remove or reshape the entire structure.

We’re using Oso to formalize these boundaries in code. Oso allows us to declare relationships between users and resources, and then map specific permissions to role levels. So when a request comes in to delete a project, Oso can evaluate: is this user related to this project as an Owner? If yes, allow the action. If not, block it.

What Manual RBAC Actually Looks Like?

Without Oso, you'd be left stitching together authorization logic manually across every part of your stack. Each service would need to implement its own version of access checks, maybe using raw conditionals, a homegrown roles table, or a custom canAccess() function that slowly balloons with edge cases. For every new resource type, you'd have to write fresh logic to define how users relate to it. If you needed to support cross-resource conditions, like “can delete this project only if the user is also an admin of the parent org,” you'd be threading business rules through multiple layers of code.

This file directly shows what authorization looks like without Oso: role checks embedded inside API route logic. It’s exactly the kind of tight coupling and imperative branching that your Oso-based app avoids.

async function handleGetProducts(req, res) {
    try {
        const user = await getAuthUser(req);
        if (!user) {
            return res.status(401).json({ success: false, message: 'Authentication required' });
        }
        
        const allowedRolesToRead = ['owner', 'collaborator', 'viewer', 'developer'];
        if (!allowedRolesToRead.includes(user.role)) {
            return res.status(403).json({ success: false, message: 'Access denied' });
        }

        const { page = 1, limit = 10, search, category, status } = req.query;
        const skip = (page - 1) * limit;

        let query = { isActive: true };
        if (search) {
            query.$text = { $search: search };
        }
        if (category) {
            query.category = category;
        }
        if (status) {
            query.status = status;
        }

        const products = await Product.find(query)
            .populate('createdBy', 'name email')
            .populate('lastModifiedBy', 'name email')
            .sort({ createdAt: -1 })
            .skip(skip)
            .limit(parseInt(limit));

        const total = await Product.countDocuments(query);

        res.status(200).json({
            success: true,
            data: {
                products,
                pagination: {
                    page: parseInt(page),
                    limit: parseInt(limit),
                    total,
                    pages: Math.ceil(total / limit),
                },
            },
        });
    } catch (error) {
        console.error('Get products error:', error);
        res.status(500).json({ success: false, message: 'Internal server error' });
    }
}

As the system grows, so does the complexity. You’d eventually have to build your own policy evaluation layer, your own relationship graph, and your own internal DSL just to keep permissions sane. And even then, there's no standard way to audit what rules exist or test them independently. You're not just maintaining the product, you're maintaining a second, invisible product called "the authorization system," and it's leaking into everything.

What Changes When You Add Oso

Instead of baking permissions directly into each route handler, we now have a centralized engine that knows what every user can and cannot do. This not only prevents unauthorized actions, it also simplifies both debugging and UI logic. As you’ll see later, the frontend can now query what a user is allowed to do before showing buttons or actions. This eliminates the need for embedded role conditionals, promoting centralized governance and auditability.

Oso vs Manual RBAC

Conclusion

As your system grows, authorization can’t live scattered across controllers and frontend checks. It needs to be centralized, declarative, and enforced consistently across every layer, API, UI, and automation. That’s exactly what we built: a fullstack RBAC system where access decisions are cleanly separated from business logic and evaluated through a purpose-built policy engine.

Using Oso with Express and PostgreSQL, we formalized user-role-resource relationships in code, enforced permissions at runtime, and exposed a frontend UI that reflects the same logic visually. The result is an architecture that’s not just functional, but scalable, where access rules live in one place, apply everywhere, and evolve cleanly over time.

RBAC isn’t just about restriction, it’s about control. The right model protects velocity while preventing production drift. With a centralized policy layer, your system becomes safer to build on, easier to reason about, and ready for the complexity that comes with scale. Curious how RBAC compares to attribute-based access control? Read our breakdown of RBAC vs ABAC for deeper insight.

FAQs

1. What’s the difference between user-scoped and role-scoped permissions?

User-scoped permissions are assigned directly to an individual, custom, explicit privileges. Role-scoped permissions are attached to a named role, which is then assigned to users. Role based access control models scale better, while user-scoped models offer precision (at the cost of manageability).

2. Can I manage RBAC through a config file?

Yes, for early-stage systems or simple permission models, YAML or JSON config files work fine. Just make sure to reload them safely and avoid hardcoding paths. For dynamic environments or per-project scoping, a DB-backed model with a policy engine (like Oso or Casbin) is more appropriate.

3. How do I test RBAC effectively in CI/CD?

Treat permissions like any other contract. Write unit tests for permission-checking logic, mock role assignments, and assert expected access outcomes. For integration tests, run flows under different simulated users and validate that protected actions are blocked or allowed accordingly.

4. Is RBAC enough for all security needs?

RBAC governs who can access what, but it doesn’t cover everything. For complete security, you still need input validation, rate limiting, secrets management, and infrastructure hardening. Think of RBAC as necessary but not sufficient, a foundational layer, not the whole structure.

‍

As a developer who's spent years wrestling with access control systems, I can tell you that traditional Role-Based Access Control (RBAC) approaches often fall short when your app needs to grow beyond basic user roles. That's where Attribute-Based Access Control (ABAC) comes to the rescue.

ABAC lets you define access control using attributes of users, resources, and context instead of fixed roles. Think of it as the difference between saying "only admins can edit" versus "users can edit if they're the owner AND the document is in draft status AND it's during business hours."

Sound complicated? It doesn't have to be. Let me show you five practical ABAC examples that'll make your access control both smarter and more maintainable.

TL;DR

ABAC uses attributes (user properties, resource metadata, contextual data) to make fine-grained access decisions. It's more flexible than pure RBAC and perfect for complex business logic. Tools like Oso make implementation straightforward with policy-as-code approaches.

ABAC Policy Examples

Example 1: Conditional Admin Access for After‑Hours Escalations

Scenario: A user can only perform admin actions on resources if they're a support manager and it’s after hours.

Attributes: user.role, hour (current time passed as a context fact)

This is a conditional, time-based admin pattern: support managers get elevated rights only after hours to handle escalations. Instead of handing out permanent admin, you flip it on during the escalation window and let policy turn it off automatically when business hours return—tight control, smaller blast radius, and no manual toggling.

actor User { }

resource Tenant {
  roles = ["member", "support_manager", "admin"];
  permissions = ["read", "manage"];

  "member" if "support_manager";
  "member" if "admin";

  "read" if "member";

  "manage" if "admin";
}

declare current_hour(Integer);

has_role(user: User, "admin", tenant: Tenant) if
  has_role(user, "support_manager", tenant) and
  current_hour(hour) and
  hour matches Integer and
  hour >= 17;

test "support managers get admin access after 5pm" {
  setup {
    has_role(User{"alice"}, "support_manager", Tenant{"tenant1"});
    has_role(User{"bob"}, "member", Tenant{"tenant1"});
    current_hour(18);
  }

  assert has_role(User{"alice"}, "admin", Tenant{"tenant1"});
  assert_not has_role(User{"bob"}, "admin", Tenant{"tenant1"});
}

Why it fits: Support managers get just-in-time admin only after hours, enforcing least privilege and letting the policy auto‑revoke access when business hours resume. It’s granular without extra complexity, and Oso keeps the time/context check in a single, tweakable rule (on‑call, weekends, regions).

Example 2: Conditional Access Based on Resource Tags

Scenario: A contributor can access a project only if it's tagged as "public."

Attributes: user.role, project.tags

This pattern demonstrates business logic expressed as policy rather than hardcoded conditionals scattered throughout your codebase.

actor User {}

resource Project {
  permissions = ["read"];

  "read" if is_public(resource);
}

test "read access for project is allowed if public" {
  setup {
    is_public(Project{"project1"});
  }

  assert has_permission(User{"alice"}, "read", Project{"project1"});
  assert_not has_permission(User{"bob"}, "read", Project{"project2"});
}

Why it fits: When your product manager decides that "internal" projects should also be accessible to contributors, you update the policy once instead of hunting through dozens of API endpoints.

Example 3: Time-Limited Access for Contractors

Scenario: Contractors can access resources only during their active contract window.

Attributes: user.expiration, now

This is a perfect example of contextual access control – permissions that depend on real-time conditions.

actor User {}

resource Repository {
  roles = ["member"];
  permissions = ["read"];

  "read" if "member";
}

has_role(actor: Actor, role: String, repo: Repository) if
  expiration matches Integer and
  has_role_with_expiry(actor, role, repo, expiration) and
  expiration > @current_unix_time;


test "access to repositories is conditional on expiry" {
  setup {
    # Alice's access expires in 2033
    has_role_with_expiry(User{"alice"}, "member", Repository{"anvil"}, 2002913298);
    # Bob's access expired in 2022
    has_role_with_expiry(User{"bob"}, "member", Repository{"anvil"}, 1655758135);
  }

  assert allow(User{"alice"}, "read", Repository{"anvil"});
  assert_not allow(User{"bob"}, "read", Repository{"anvil"});
}

Why it fits: No more manual disabling of contractor accounts. No more "oops, forgot to revoke access" security incidents. The policy automatically enforces time boundaries.

Example 4: Delegated Access (REBAC-style ABAC)

Scenario: A user can access a resource only if someone else has explicitly shared access with them.

Attributes: resource.shared_with, user.id

While not full relationship-based access control, this pattern uses attribute logic to simulate delegation relationships.

actor User {}

resource Repository {
  permissions = ["view"];
  relations = {
    shared_with: User
  };

  "view" if "shared_with";
}

test "access to repositories is conditional on expiry" {
  setup {
    has_relation(Repository{"anvil"}, "shared_with", User{"alice"});
  }

  assert allow(User{"alice"}, "view", Repository{"anvil"});
  assert_not allow(User{"bob"}, "view", Repository{"anvil"});
}

Real-world application: Think shared documents, temporary project access, or vacation coverage scenarios. Someone with access can grant it to others without involving IT.

Example 5: State-Based Permissions (Workflow Control)

Scenario: A user can only edit a record if it's in "draft" status.

Attributes: resource.status, user.permissions

This is a clean example of tying access to business process state – perfect for content workflows, product pipelines, or any multi-stage process.

actor User {}

resource Document {
  roles = ["viewer", "editor", "owner"];
  permissions = ["read", "edit"];

  "read" if "viewer";
  "viewer" if "editor";

  "edit" if "editor" and is_draft(resource);
  "edit" if "owner";
}

test "edit access to document is conditional on if draft" {
  setup {
    is_draft(Document{"document1"});
    has_role(User{"alice"}, "editor", Document{"document1"});
    has_role(User{"bob"}, "viewer", Document{"document1"});
    has_role(User{"alice"}, "viewer", Document{"document2"});
    has_role(User{"bob"}, "editor", Document{"document2"});
  }

  assert allow(User{"alice"}, "edit", Document{"document1"});
  assert_not allow(User{"bob"}, "edit", Document{"document1"});

  assert_not allow(User{"alice"}, "edit", Document{"document2"});
  assert_not allow(User{"bob"}, "edit", Document{"document2"});
}

Why it fits: Your business logic stays in your policies, not scattered across controllers. When the workflow changes (adding a "review" state, for example), you update the policy, not every piece of code that checks permissions.

Implementing ABAC in Oso

Oso makes ABAC practical by letting you express these complex policies in Polar, a declarative policy language designed for developers.

‍

Here's what makes Oso's approach different:

• Developer control: Policies live in version control alongside your code
• Separation of concerns: Business logic stays in policies, not scattered through your application
• Dynamic enforcement: Policies evaluate in real-time with fresh data
• Testing support: Built-in tooling for policy validation and edge case testing

Quick implementation example:

# Your application code
if oso.authorize(user, "edit", document):
    # Proceed with edit operation
    pass

‍

The policy handles all the complex attribute checking – you just ask "is this allowed?"

DevOps has transformed how developers build, deploy, and manage infrastructure and applications, making automation, scalability, and rapid iteration core to modern development workflows.

While much of the software delivery process has evolved, authorization has largely remained stuck in legacy approaches. Many organizations still manage homegrown solutions with hardcoded permissions across services, custom policies by different teams, and manual updates as access needs shift. These approaches may work initially, but they do not scale properly.

As teams adopt microservices, APIs, and multi-cloud architectures, fragmented authorization systems become a liability. Each policy change demands manual effort across teams and services—slowing development, increasing the risk of misconfigurations, and eroding confidence in access control.

Why Traditional Authorization Models Fall Short

Many homegrown solutions, such as Duolingo’s previous authorization system, were built to solve immediate needs. Early-stage architectures often rely on simple approaches like Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC). These models are easy to implement, making them appealing when rapid development is the priority.

However, as companies scale, these simple models quickly show their limits. Real-world applications rarely stay static. Instead, teams need a blend of authorization models to address growing complexity—supporting multi-tenant architectures, managing resource-specific roles, handling user relationships, and enforcing contextual permissions that shift based on factors like time, ownership, or evolving business rules.

As requirements evolve, this leads to custom logic, scattered exceptions, and manual interventions. The once simple authorization tool becomes fragile, inconsistent, and a bottleneck in the development lifecycle.

The Role of Policy-as-Code and Authorization-as-a-Service

To overcome the challenges of fragmented, manual access control, modern DevOps teams are adopting solutions with the same principles that transformed infrastructure and application delivery into the world of authorization. Two complementary approaches are emerging as the go-to strategies:

• Applying DevOps best practices through Policy-as-Code (PaC).
• Reducing operational overhead with Authorization-as-a-Service (AaaS).

Just as DevOps streamlined infrastructure through automation and version control, PaC and AaaS now deliver the same agility and consistency to authorization.

Policy-as-Code: Authorization Meets DevOps

Policy-as-Code (PaC) is the practice of defining and managing authorization policies in a declarative, code-like format—version-controlled, testable, and integrated into automated workflows. PaC is typically implemented in a domain-specific language or configuration format. By applying core DevOps principles, PaC transforms authorization from a manual, error-prone task into a streamlined, reliable component of software delivery.

Authorization-as-a-Service: Scalable Enforcement Without The Overhead

However, defining policies is only one part of the solution. Teams also need a scalable, reliable way to enforce these policies across their distributed systems and applications. That's where Authorization-as-a-Service (AaaS) comes in, providing managed, cloud-native platforms that handle policy enforcement without requiring teams to maintain their own authorization infrastructure.

Modern authorization solutions combine these two approaches:

• Declarative policies (PaC) that ensure transparency, audit-ability, and easier collaboration.
• Scalable, hosted decision engines (AaaS) that consistently enforce policies across microservices, APIs, and multi-cloud environments.

This powerful combination enables DevOps teams to rapidly adapt to changing business requirements, ensuring consistent authorization enforcement without slowing down development or adding operational complexity.

This overview highlights the reasons behind many companies' shift to Authorization-as-a-Service for complex authorization use cases.

Best Practices for Modern Authorization

Successfully implementing Policy-as-Code and Authorization-as-a-Service requires adopting certain best practices that align closely with DevOps methodologies.

Key practices include:

• Decouple authorization logic from application code. Centralize policies to avoid duplication, reduce drift, and simplify maintenance across services.
• Use declarative policies to standardize access control. Focus on what access is allowed, not how it’s enforced.
• Choose platforms that:
  • Support flexible authorization models to handle evolving business requirements without constant rewrites.
  • Integrate seamlessly with CI/CD workflows for automated testing, deployment, and version control of policies.
  • Provide scalable, managed enforcement through AaaS. Eliminate operational overhead while ensuring consistent policy decisions across distributed systems.
• Model for growth and complexity. Start simple, but ensure your solution can adapt to non-standard use cases, dynamic relationships, and contextual permissions as your application scales.
• Ensure observability and compliance by tracking policy changes, enabling peer reviews, and integrating authorization with monitoring and telemetry to maintain full visibility and audit readiness.

This POC framework offers practical steps for evaluating authorization solutions that align with both Policy-as-Code and Authorization-as-a-Service strategies.

Conclusion: The Future is Flexible, Automated Authorization

Modern authorization can no longer rely on static roles, hardcoded logic, or manual processes. As architectures become more dynamic and distributed, effective access control demands both code-driven policies and scalable enforcement models.

For most companies, building and maintaining a custom authorization system isn’t an investment, it is a long-term liability. When authorization isn’t core to your product’s value, investing engineering resources into homegrown solutions distracts from your main focus. Teams need solutions that integrate seamlessly into development workflows and scale as business needs evolve.

By embracing an authorization service based on Policy-as-Code (PaC) and Authorization-as-a-Service (AaaS), teams bring automation, flexibility, and consistency to authorization. This ensures that access management evolves seamlessly alongside their DevOps workflows. This approach not only strengthens security but also removes operational bottlenecks, allowing development teams to move faster without sacrificing control.

Introduction

Keycloak has long been a popular choice for developers and organizations looking for an open-source identity and access management (IAM) solution. With features like SSO, LDAP integration, and support for major protocols like OAuth2 and SAML, it’s easy to see why Keycloak is often the default. But as infrastructure needs grow and IAM demands evolve, many teams are reevaluating whether Keycloak is still the best fit.

In this post, we’ll explore the top Keycloak alternatives in 2025 — from lightweight self-hosted solutions to fully managed enterprise-grade platforms — and help you decide what might work best for your team.

Reasons to Switch From Keycloak

While Keycloak is powerful, it isn’t always the most convenient solution. Here are a few reasons teams look for an alternative:

• Operational Overhead: Managing Keycloak yourself requires handling updates, backups, scaling, and security patches. That’s a lot for teams that want to focus on product development.
• Complexity: Keycloak’s configuration UI and documentation can feel overwhelming, especially for smaller teams or those new to IAM.
• Performance Bottlenecks: At scale, Keycloak’s performance can lag without considerable optimization and monitoring.
• Lack of Extensibility: Customizing workflows or deeply integrating with non-standard services can be clunky.
• Cloud-Native Preferences: Many teams now prefer solutions that are plug-and-play with modern cloud platforms or serverless stacks.

So, what makes a good Keycloak alternative? A modern IAM solution should:

• Be easy to integrate and customize
• Offer strong protocol support (OAuth2, OIDC, SAML)
• Scale with your application
• Offer great documentation and developer experience
• Provide flexible hosting options (cloud, self-hosted, hybrid)

Let’s dive into the top alternatives worth checking out in 2025.

1. Oso

What is Oso:

Oso is an open-source authorization engine designed to simplify access control logic. Rather than handling authentication or identity management itself, Oso focuses specifically on authorization—fine-grained, logic-driven access decisions that you define in code using a policy language called Polar.

Why is Oso better than Keycloak:

If your team wants fine-grained control over authorization logic but doesn’t need a full user management system, Oso can complement lighter authentication systems beautifully. It’s ideal for apps with complex permissions, like multi-tenant SaaS or systems with nested roles and resources.

Pros:

• Supports complex, real-time policy decisions using Polar
• Embeddable in your app — not a separate service
• Seamlessly integrates with your existing user models
• Encourages code-first, testable authorization logic

Cons:

What is Oso’s pricing?

Oso provides flexible pricing plans tailored to various business scales. Their Developer-tier starts at $0 per month, while the Startup-tier begins at $149 per month. For their Growth-tier and migration services, pricing is customized based on individual consultations with their experts.

2. Auth0

Auth0 is a fully managed identity platform that simplifies authentication and authorization through SDKs, APIs, and a sleek dashboard. It supports social login, enterprise SSO, and multifactor authentication right out of the box.

Why it’s a good alternative:

Auth0 lets teams ship authentication fast without becoming identity experts. Its robust feature set is ideal for growing applications that need to support complex login flows or multiple identity providers.

Pros:

• Built-in support for social, enterprise, and passwordless login
• Rich RBAC and tenant isolation features
• Strong extensibility through Actions and Rules
• Audit logging and anomaly detection baked in

Cons:

• Costs can spike as MAUs increase
• Less flexible UI customization unless on higher plans
• Data residency is fixed unless on enterprise tier

What is Auth0’s Pricing?

Auth0 provides both a free-tier and several premium-tier options. The entry-level premium plan ranges from $35 to $150 per month for 500 users, depending on the specific use case. They also offer annual pricing and allow customization based on the number of monthly active users.

3. Ory

Ory is a modular, cloud-native IAM platform composed of purpose-built services like Kratos (identity), Hydra (OAuth2), Keto (RBAC), and Oathkeeper (gateway).

Why it’s a good alternative:

Ory breaks monoliths like Keycloak into composable services. It’s ideal for teams deploying on Kubernetes or building large-scale, distributed systems where control over every IAM layer is necessary.

Pros:

• Modular services allow fine-grained control over architecture
• Extremely performant and horizontally scalable
• API-first with structured versioning and CLI tooling
• Backed by an active open-source community and foundation

Cons:

• Requires orchestration between modules
• No plug-and-play admin UI — you need to build your own or use third-party
• Limited plug-and-play integrations compared to managed providers

What is Ory’s Pricing?

Ory is primarily based on a free open-source core. However, they offer premium cloud tiers based on the user’s need. Their lowest-tier, Ory Network Production, retails at $70/month.

4. Okta

Okta is a trusted enterprise identity provider offering authentication, user lifecycle management, and SSO across workforce and customer-facing applications.

Why it’s a good alternative:

Okta delivers deep compliance features and battle-tested reliability. If you're serving a regulated industry or managing thousands of internal users, Okta offers tooling that few others match.

Pros:

• Extensive SCIM and directory sync capabilities
• Native support for B2B federation and Just-in-Time provisioning
• Global reliability SLAs and enterprise compliance
• Lifecycle management via Workflows

Cons:

• UI feels outdated and less developer-oriented
• Complex to configure for multi-tenant apps
• Can be prohibitively expensive for startups

What is Okta’s Pricing?

Okta comes with a higher price point than some alternatives and often involves complex enterprise setups that may need specialized expertise. Similar to Microsoft Entra ID, Okta’s entry-level plan is priced at $6 per user per month.

5. FusionAuth

FusionAuth is a complete identity platform that’s installable on your infrastructure or via the cloud. It’s designed with developers in mind, supporting OAuth2, OpenID, JWT, and customizable login flows.

Why it’s a good alternative:

FusionAuth offers the control of Keycloak without the same operational burden. It’s highly configurable and handles a wide range of use cases from multi-tenant SaaS to CIAM.

Pros:

• Fine-grained tenant and role control
• Clean UI and customizable user workflows
• Event and webhook system for downstream triggers
• Well-designed for embedded login experiences

Cons:

• Smaller ecosystem for third-party plugins
• Advanced features (e.g., SAML IdP support) require paid tiers

What is FusionAuth’s Pricing?

Free for self-hosted version available. FusionAuth generally dictates their pricing based on the plan you choose, as well as the type of hosting selected. They offer a monthly pricing calculator on their webpage, allowing users to play with numbers and options before selecting.

6. Gluu

Gluu is a security-focused, open-source IAM platform designed for enterprises needing SAML, OpenID Connect, and UMA support.

Why it’s a good alternative:

If you’re in a compliance-heavy sector like healthcare or finance, Gluu provides flexibility and security without the vendor lock-in of managed IAM providers.

Pros:

• Strong support for older enterprise protocols like SAML2
• UMA support for user-consent-driven authorization
• Compatible with multiple LDAP backends

Cons:

• Heavy infrastructure footprint
• Configuration management is complex and error-prone
• UI and deployment process lag behind modern expectations

What is Gluu’s Pricing?

Gluu is free open-source. However, they do offer commercial support which is typically based on MAU’s.

7. Supabase Auth

Part of the Supabase ecosystem, Supabase Auth is a simple but effective authentication system built on GoTrue (originally from Netlify). It supports social logins, email magic links, and passwordless login.

Why it’s a good alternative:

Perfect for fast prototyping or projects already using Supabase’s database and serverless functions. It keeps your stack tight and easy to manage.

Pros:

• Passwordless login is built-in and easy to set up
• Social providers available with one-click configuration
• Real-time syncing with Supabase DB

Cons:

• Authorization logic is basic — better suited for simple apps
• Limited enterprise readiness
• Doesn’t support SAML or SCIM

What is Supabase’s Pricing?

Supabase offers a free-tier with 50,000 MAU and limited specs. Upgrading to the higher-tiers offer better specs, with the next being the pro-tier retailing from $25/month.

8. Clerk

Clerk provides frontend-centric authentication for React, Next.js, and other JavaScript frameworks. It comes with drop-in UI components and APIs for managing sessions, MFA, and user profiles.

Why it’s a good alternative:

If your frontend stack is React-heavy, Clerk gets you to production quickly with minimal boilerplate. It handles session and user state without needing custom logic.

Pros:

• Prebuilt components for fast frontend integration
• First-class support for MFA and email verification
• Supports org-based auth and multi-session handling

Cons:

• Limited back-end language support
• Less extensible outside React ecosystem
• Not ideal for deeply customized workflows

What is Clerk’s Pricing?

Clerk offers a free-tier for up 10,000 MAUs including everything needed to get started. Their next tier is their pro plan which begins at $20/month and $0.02/MAU after your first 10,000.

9. AWS Cognito

Amazon Cognito is a managed identity service from AWS. It combines user pools (authentication) with identity pools (federation) for managing user identity and access.

Why it’s a good alternative:

If you’re building on AWS and don’t want to leave the ecosystem, Cognito provides reasonable IAM integration with your Lambda functions, API Gateway, and other services.

Pros:

• Tight AWS service integration (IAM, API Gateway, AppSync)
• Highly scalable and resilient
• Federation support with minimal setup

Cons:

• Poor developer ergonomics and API design
• UI customization is clunky
• Debugging issues can be opaque

What is Amazon Cognito’s Pricing?

Amazon Cognito offers a pay-as-you-go pricing model making it cost effective with usage variance. They offer a free-tier for the first 10,000 users and charge per user based on region after crossing the threshold. They also offer more advanced-tiers, which come at greater costs and no free trials.

10. Authentik

Authentik is a modern open-source authentication provider that supports OAuth2, SAML, and LDAP, built with modern developer needs in mind.

Why it’s a good alternative:

It’s arguably what Keycloak should have been—lightweight, modern, Docker-native, and built for today’s security needs. Perfect for self-hosters and homelab pros.

Pros:

• Modern admin interface with visual policy builder
• Clean, modular codebase for extensibility
• Built-in provider bridging between OIDC, SAML, and LDAP

Cons:

• Smaller contributor base and less third-party tooling
• Still maturing compared to older IAM systems
• Some missing features like consent management

What is Authentik’s Pricing?

Authentik is free and open-source, but also has premium-tiers starting at $5/user/month. Their enterprise subscription is based on a consultation, but is said to begin at $20k/year billed annually.

Conclusion

Keycloak has earned its spot in the IAM world, but it's not the only game in town. Whether you're looking for better scalability, cleaner developer experience, or tighter control over your access policies, there's a solution that fits your stack better.

Open-source purists might gravitate toward Ory or Authentik, while those prioritizing ease-of-use might prefer Auth0, Clerk, or FusionAuth. If you’re already invested in AWS, Cognito might be the most seamless option.

Ultimately, the right alternative depends on your team size, hosting preferences, feature needs, and budget. Try a few — and see which one makes identity management feel like less of a chore and more of an accelerator.

‍

Access control management is the practice of ensuring specific people have access to specific resources: no more and no less. At its very core, cybersecurity is about good access control management. Stopping hackers or unintentional data leaks amounts to ensuring that resources aren't accessible by users without access.

In this article, you’ll learn how to approach access control management today. We’ll cover the security risks, the systems involved, and best practices to ensure that your organization remains as secure as possible.

1. Introduction: Why Access Risk Begins With Authorization Logic

When I see IT professionals first approach access management, they initially approach it as a set of checkboxes: enable two-factor authentication, revoke former employees' accounts, audit user permissions quarterly, and so on.

I once believed in this tactical view—and it is important—but it doesn't address a fundamental architectural concern: access risk that stems from how authorization logic is designed and implemented within your application.

For developers, this means systematically identifying where your application's permission logic can fail, grant excessive privileges, or drift from intended behavior over time. Compliance frameworks like SOC 2, GDPR, and HIPAA require demonstrated control over data access for good reason: authorization failures consistently drive both regulatory violations and data breaches.

For example, flawed authorization logic enabled attackers in the 2019 Capital One breach to access 100 million customer records through a misconfigured web application firewall. Similarly, the 2020 SolarWinds attack exploited excessive privileged access to cascade across thousands of organizations. In modern hybrid and cloud-native environments, authorization failures become launching pads for comprehensive system compromise.

2. Understanding Access Management Risk in Application Development

In the early days of your product, authorization might be as simple as checking if someone has access to a particular document or resource. But as your MVP grows, that logic starts spreading everywhere: React components, API routes, database queries, and third-party integrations. Before you know it, you're debugging why the new intern can somehow delete production data, or why that contractor still has internal systems access months after their project ended.

I’ve noticed that this organic growth tends to create access risk through two types of decisions.

• Sprawling authorization checks across services: Those if user.role == 'admin' checks scattered throughout your codebase become maintenance nightmares when business requirements change. Imagine that you now need to add a "super admin" role: every one of those checks may have to be updated, and it would be difficult to verify it’s working correctly.
• Privilege creep: When updating logic becomes costly, I’ve seen developers simply grant broader permissions to existing roles. "Just give them editor access for now" becomes permanent, blurring role boundaries and violating least privilege principles.

These decisions feel inconsequential in the moment, but they compound over time. I’ve experienced this sluggish but constant deterioration of security before. The reality is that engineering teams must own a large portion of access control risk and avoid delegating it entirely to security teams. When developers and security collaborate early in building authorization architecture, those simple permission checks avoid evolving into systemic risks.

3. Top Access Control Risks Developers Should Assess

To understand access control risks, you can start by identifying authorization logic decisions that have the potential to turn into security failures. These are some access security risks I’ve seen emerge as teams and codebases scale:

Inconsistent Policy Enforcement Across Services

When your user service says Sarah is a "viewer," but your API gateway treats her as an "editor," you've got a consistency problem. This can happen more easily than you think. Different teams can implement different interpretations of the same role, creating gaps where unauthorized access slips through.

Authorization Logic Sprawl

You ship an MVP with a simple if user.role == 'admin' check. Then, business requirements evolve, leading this simple check to evolve into an unreadable nested conditional like if (user.role == 'admin' || (user.role == 'editor' && user.department == 'marketing' && resource.owner == user.id))

Sound familiar? Each new business requirement adds another layer of complexity, making your authorization logic impossible to reason about, test, or modify safely.

Zero Visibility Into Effective Permissions

Can you quickly answer "What can the new contractor actually access?" across your entire application? As teams begin to scale, they discover that they can't. Without centralized visibility, access reviews can turn into archaeological expeditions, and security incidents reveal permissions you didn't know existed.

Blurred Lines Between Identity and Authorization

Many applications embed authorization decisions directly into user profiles or JWT tokens, conflating "who someone is" with "what they can do." What should be a simple change, such as "temporarily restricting all contractor access to customer data," becomes a nightmare of updating multiple systems and potentially breaking functionality.

Missing Governance for Permission Changes

Permission changes often happen through direct database updates, config file edits, or hardcoded assignments. Without review workflows and change tracking, you can't understand how permissions evolved or roll back problematic changes, turning every access issue into a forensic investigation.

4. A Code-First Approach to Assessing Access Management Risk

The problems I've outlined so far stem from sacrificing scalability for speed. It’s time to look at authorization in a scaled system as a first-class engineering concern. What if instead of burying permission checks throughout your codebase, you could model access control the same way you model your data: as a structured, queryable, testable system?

This shift from authorization logic to authorization data changes everything. Rather than hunting through conditionals scattered across services, you define policies in a centralized, declarative way. Instead of debugging why someone has unexpected access, you query your policy engine to understand exactly what permissions are in effect.

Separating Authorization From Business Logic

Problematic authorization ties access directly to business logic. However, a tier that allows access to certain premium features is a fundamentally different concern if a certain identity can access those features. Instead, business logic should be separated from authorization, where authorization is purpose-built to strictly answer if a specific identity has access to a specific resource. Meanwhile, whether or not that question is asked is determined by business logic.

The Power of Declarative Policy Languages

Declarative authorization policy languages, such as Polar, let you express complex authorization rules in a readable, maintainable format. Instead of nested conditionals, you write rules that look like: allow(user, "edit", document) if user in document.editors. These policies become living documentation of your access control requirements while remaining executable code.

Policy as Code Unlocks New Capabilities

This approach unlocks engineering best practices that were impossible with scattered authorization logic:

• Versioning & auditability: Track exactly how permissions changed over time, with proper commit history and pull request reviews for policy changes.
• Unit testing policies: Write comprehensive tests for your authorization rules, catching edge cases before they reach production.
• Reusing logic across services: Define common patterns once and apply them consistently, eliminating the drift between different team implementations.
• Reducing developer overhead:  New features focus on business logic rather than reinventing permission checks, freeing developers from having to solve the same authorization patterns repeatedly.

5. How to Conduct a Developer-Friendly Access Risk Assessment

I love theory as much as the next person, but actually auditing an existing authorization mess can be a nightmare. In the past, I’ve used the following checklist as a practical approach to assessing access risk that minimizes cost.

• Inventory all access decisions in your codebase. Start with a simple grep search for patterns like user.role, permissions, can_, is_admin, and authorize. Check frontend code, database triggers, and configuration files. The goal is to build a mental map of where authorization happens.
• Identify where authorization logic lives. Next, group findings by location: API middleware, route handlers, frontend components, database security, and third-party configs. If authorization spans more than three different layers, it’s a good idea to also check for consistency problems.
• Check for duplication and divergence. Look for similar permission checks implemented differently. If a user is given the ability to delete other users, for example, it could be implemented as user.role === 'admin' in one service, but user.permissions.includes('delete_users') in another. These inconsistencies are your highest-risk areas.
• Map user roles to business needs (not convenience). List every role and assess whether it serves a real business function or if it was created simply to make implementation easier.
• Review elevated access paths. Trace how users gain admin or elevated privileges. Can the support staff escalate permissions? Do API keys have excessive scope? Are there emergency access procedures that bypass authorization?

• Add tests for edge cases. Write tests for scenarios like cross-tenant access, expired permissions, and role transitions. Authorization edge cases are where breaches happen.
• Document who can change policies and how. Map your permission change workflow: Who can modify roles? How are changes deployed? Is there approval? Make sure that every step is audited to ensure that policies are only able to be changed by the intended users.

6. Best Practices to Reduce Access Risk in Code

Once the assessment of the current state is complete, I’ve found that I’ll have a strong sense of where the weak points are. Next, I use the following principles to implement new patterns around authorization, which scale with the product I’m working on and minimize technical debt and security risks.

• Centralize policies in a policy engine. Instead of scattering authorization logic across your codebase, consolidate all access decisions in a dedicated policy engine. This creates a single source of truth that eliminates inconsistencies and makes changes predictable. When you need to update permissions, modify policies in this one place rather than hunting for authorization logic throughout your dozens of services.
• Use relationship-based access control (ReBAC) where appropriate. For complex authorization scenarios, relationship-based models are more natural than role-based ones. Consider file access: RBAC creates roles like "Finance_Viewer," "HR_Editor," and "Engineering_Admin" for each department. ReBAC simply says, "Team members can view files in their team's folder,” a simple rule that automatically works as you add new teams. You define relationships like "member_of" and derive permissions from those connections, making policies that mirror how your business actually works.
• Design for least privilege from day one. Start with minimal permissions and add access as needed, rather than granting broad permissions and trying to restrict later. This means being explicit about what each role can do instead of what it can't do. Default-deny policies prevent privilege creep.
• Build policies that reflect your domain model. Your authorization rules should be determined by business concepts, not technical convenience. If your business talks about "project members" and "team leads," your policies should use those terms instead of generic "users" and "admins." This alignment makes policies easier to review and modify as requirements change.

• Provide interfaces for policy review. Security and product teams need visibility into authorization rules without reading code. Having dashboards or admin interfaces that show effective permissions, role definitions, and policy changes is incredibly useful to the  stakeholders who determine access rules.
• Integrate policy checks into CI/CD. All critical code is run through continuous integration / continuous development (CI/CD) pipelines, and authorization policies should be no different. Use CI/CD to eliminate breaking authorization changes and enable review from multiple members of your team.

7. Example: Access Risk in a SaaS App

Let’s make this more concrete with an example. Consider a typical document management platform with three roles for your MVP:

1. Employees who can view their own documents
2. Managers who can access their team's files
3. Admins who have full access

For an MVP, I’ve often implemented this as one-off checks in API routes, which usually suffice for the intended scale.

However, as  business requirements grow, complexity creeps in. What happens when someone is managing two teams? Can managers edit documents or just view them? What about contractors who need access to specific projects but shouldn't see company-wide files? Do departing employees immediately lose access to documents they created?

Without clear policies, it’s easy to start making one-off decisions. The frontend might check user.role === 'manager' while the API verifies user.department === document.department. The mobile app implements different logic from the web app. Soon, you're debugging why the new marketing manager can't access last quarter's campaign docs, or why a former employee still has read access.

Modeling Clear Policies with Polar

Instead of scattered conditionals, you can express these authorization rules declaratively using Polar. Here's how the document access policy looks:

actor User {}

resource Document {
 permissions = ["read", "edit", "delete"];
 roles = ["viewer", "editor", "owner"];
 relations = { team: Team, creator: User };

 # Basic permissions
 "read" if "viewer";
 "edit" if "editor";
 "delete" if "owner";

 # Role hierarchy
 "viewer" if "editor";
 "editor" if "owner";

 # Team-based access
 "viewer" if "member" on "team";
 "editor" if "manager" on "team";

 # Creator access
 "owner" if "creator";
}

resource Team {
 roles = ["member", "manager"];
}

‍‍


This single policy file captures all the business rules: team members can view team documents, managers can edit them, document creators have full ownership, and roles inherit permissions appropriately.

How Policy Review Surfaces Hidden Risks

With centralized policies, security teams can easily spot problematic patterns. Looking at the policy above, they might ask: "Wait, can managers edit documents from other teams if they're temporarily assigned to multiple teams?" It’s easy to tell that the answer is yes but with scattered if statements, that could have been a business logic error, nigh impossible to catch.

Testing becomes straightforward, too. You can write unit tests in Python, such as:

# Test cross-team access
assert not oso.authorize(marketing_manager, "edit", engineering_doc)

# Test role transitions
user.remove_role("manager", marketing_team)
assert not oso.authorize(user, "edit", marketing_doc)


In the typical authorization logic sprawl, it would be much more difficult to test whether role changes take effect immediately or whether temporary team assignments create unintended access paths without a centralized policy store.

8. Access Risk Assessment as a Living Practice

I’ve outlined several ways to assess authorization risk, but as a product grows, new areas of risk can emerge because each new feature introduces potential access control gaps.

Making Access Management Part of Your SDLC

I believe that the most effective approach to maintaining secure access management is to treat authorization as a first-class concern in the software development life cycle (SDLC). During architecture reviews, ask "How will this feature affect who can access what?" alongside performance and scalability questions. When designing new user types or resource hierarchies, map out the permission implications before writing code.

More broadly, this means establishing clear checkpoints in your SDLC. Policy changes should require a security review, just like database schema changes. New roles need a business justification beyond "it makes the implementation easier." Authorization edge cases should get explicit test coverage in your acceptance criteria.

Let’s make this practical.

• Feature planning: Include access control requirements in user stories. "As a team manager, I need to view team reports" should specify whether this includes former team members' data, contractors, or cross-functional project participants.
• Code reviews: Flag pull requests that introduce new permission checks or modify existing ones. Look for hardcoded role checks, inconsistent authorization patterns, or missing authorization entirely on new endpoints.
• Infrastructure reviews: When adding new services, databases, or third-party integrations, assess how they'll inherit or bypass existing authorization controls. Service-to-service communication often becomes an unintended privilege escalation path.

• Regular policy audits: Schedule quarterly reviews of effective permissions, especially for elevated roles. Use your policy engine's visibility tools to identify permissions that exist in theory but aren't used in practice—these often indicate either over-privileged roles or missing functionality.

In my view, don't make perfect security the goal from day one. Instead, slowly build systems that make authorization risks visible and manageable as complexity grows.

9. Conclusion: From Risk to Resilience

Access management doesn't have to be complex. Instead of hunting through scattered if user.role === 'admin' statements and patching holes after incidents, I've found that successful teams consolidate authorization logic into a centralized, reviewable system.

More broadly, I believe authorization can be infrastructure-versioned, tested, and observable, enabling you to ship features confidently, onboard new developers faster, and answer compliance questions with executable code rather than documentation guesswork.

Here's the reality: engineering teams own most access control risk, not just security teams. Every authorization decision made during development directly impacts your security posture. Ready to start? I recommend learning to audit your current access management decisions using Oso’s Authorization Academy, or implementing your first declarative Polar policy with Oso Cloud.

‍

FAQs

What is Access Control Management?

Access control management is the process of implementing tools, policies, and procedures to ensure that users, applications, and devices can only access the data, systems, and services they are explicitly authorized to use. It includes assigning permissions, verifying identities, and continuously monitoring access activities to prevent unauthorized use.

Why is Access Control Management Important?

Access control is critical for:

• Preventing data breaches and insider threats
• Protecting sensitive customer or employee information
• Complying with regulations like GDPR, HIPAA, PCI DSS, and SOX
• Maintaining business continuity through secure and auditable access processes
• It strengthens both cybersecurity posture and regulatory audit readiness.

What is The Difference Between Access Control and Access Management?

• Access control refers to the enforcement of rules that govern who can access what.
• Access management is a broader discipline that includes identity verification (authentication), policy creation, provisioning/deprovisioning, and continuous monitoring.

Access management enables access control.

What are The Three Main Types of Access Control?

1. Preventive controls – Stop unauthorized access (e.g., MFA, encryption, firewalls).
2. Detective controls – Identify and alert on suspicious activity (e.g., audit logs, IDS).
3. Corrective controls – Mitigate damage and restore systems post-incident (e.g., backups, remediation plans).

What’s The Role of Authentication and Authorization in Access Control?

• Authentication verifies user identity (e.g., with passwords or biometrics).
• Authorization determines what that verified user can access, based on roles, rules, or context.

Both are core steps in secure access workflows.

What are Best Practices for Access Control in Enterprise Environments?

• Apply the Principle of Least Privilege (PoLP)
• Use Multi-Factor Authentication (MFA)
• Fine-Grained Authorization (FGA)
• Implement Separation of Duties (SoD)
• Conduct regular access reviews and audits
• Monitor privileged user activity
• Use dynamic, risk-based access when possible

What is Access Management Risk Assessment?

Access management risk assessment is the process of identifying, evaluating, and mitigating risks related to how users, applications, and systems access sensitive resources within an organization. It ensures that access controls align with security requirements, regulatory compliance, and business needs.

What are The Risks of Poor Access Control Management?

• Data breaches and loss of customer trust
• Insider misuse of privileges
• Regulatory fines and audit failures
• Account takeover and lateral movement by attackers
• Operational disruptions from unauthorized changes

What are Dynamic Access Controls and How Do They Work?

Dynamic access control uses contextual data (like time, location, device, and behavior) to evaluate each access request in real-time. It allows organizations to grant or deny access based on dynamic risk scores rather than just static roles or rules.

Why are Access Controls Important for Compliance Audits?

Auditors evaluate access controls to ensure that only authorized users can access sensitive systems and data. Strong access controls reduce the risk of data breaches, support regulatory compliance, and demonstrate organizational commitment to security best practices.

What are The Risks of Poor Access Control Management?

Weak or missing access controls can lead to:

• Unauthorized access to sensitive information
• Insider threats and data leaks
• Compliance violations and failed audits
• Inadequate user offboarding
• Difficulty tracking privileged user activity

In the early days of your product, authorization might be as simple as checking if someone's logged in before showing the admin panel. But as your MVP grows, that logic starts spreading everywhere: to React components, API routes, database queries, and third-party integrations. Before you know it, you're debugging why an arbitrary hire can alter production data.

This organic growth creates access risk through three types of decisions that feel routine but compound over time:

• Hardcoded authorization logic: Those if user.role == 'admin' checks scattered throughout your codebase become maintenance nightmares when business requirements change. What happens when you need to add a "super admin" role, or when an "admin" needs different permissions across different parts of your app?
• Sprawling conditionals across services: When authorization logic lives in multiple places—frontend guards, API middleware, database triggers—it becomes nearly impossible to answer: "Who can actually do what?" Inconsistent enforcement is inevitable.
• Privilege creep through unclear role definitions: Developers grant broader permissions to avoid breaking things, especially when role boundaries are fuzzy. "Just give them editor access for now" becomes permanent, violating least privilege principles.

‍

If you're working with infrastructure as code, especially with Terraform, you know how quickly things can get out of hand without proper governance. This is where policy as code comes in handy. Today we’ll discuss Open Policy Agent. OPA is one of the best tools to help you maintain security while using Terraform.

What exactly is Policy as Code?

Policy as Code (PaC) is the practice of defining your governance, compliance, and security rules using code. Think of it as version-controlling your rules, making them auditable, and automatically enforcing them. For Terraform users, this means you can evaluate infrastructure changes before they're deployed and roll them back quickly if something unexpected happens after they're deployed. This significantly reduces the risk of misconfigurations and non-compliance. By integrating PaC into your CI/CD pipelines, you gain consistency, traceability, and faster remediation across your infrastructure workflows.

How Open Policy Agent works with Terraform

‍OPA is a general-purpose policy engine that evaluates policies written in a language called Rego against JSON-based data inputs. When it comes to Terraform, OPA can evaluate your policies against the JSON output of a Terraform plan. Tools like Conftest or OPA’s HTTP API can then be used to test whether your proposed infrastructure changes meet your defined policy requirements. For example, you can use OPA to validate that resources are only deployed in approved regions or that all required tags are present. The results of these evaluations can then be used to block, warn, or simply log non-compliant infrastructure changes in your automated workflows.

OPA vs. Sentinel: a quick comparison

If you've been in the Terraform ecosystem for a while, you might be familiar with Sentinel. So, what's the difference between OPA and Sentinel? OPA is a more flexible, open-source policy engine that works across a much broader cloud-native stack – Terraform, Kubernetes, APIs, and more. Sentinel, on the other hand, is developed by HashiCorp and is tightly coupled with Terraform and the HashiCorp ecosystem. While Sentinel is great for what it does within its scope, OPA provides broader integration opportunities, a larger community, and greater extensibility. If you're a team looking to standardize policy enforcement across diverse environments and tools, OPA is definitely the way to go. For an introduction on how to use OPA for Kubernetes, checkout our guide here.

The benefits of integrating OPA with Terraform

Integrating OPA with Terraform offers several compelling benefits:

• Preventing Non-Compliant Resources: You can stop non-compliant resources from ever being provisioned.
• Enforcing Standards: Easily enforce tagging, naming, or security requirements across your infrastructure.
• Early Feedback: Get immediate feedback in your CI/CD pipelines, catching issues before they become problems.

Writing an OPA policy with Terraform—an example

Let's walk through a simple example of how you might write an OPA policy to ensure that all AWS S3 buckets are encrypted. First, you'll need a Terraform plan output in JSON format. You can generate this using terraform plan -out=tfplan.binary and then terraform show -json tfplan.binary > tfplan.json.

Now, let's write a Rego policy (e.g., s3_encryption.rego):

package terraform.aws.s3

default allow = false

allow {
 input.resource_changes[_].type == "aws_s3_bucket"
 input.resource_changes[_].change.after.server_side_encryption_configuration[_].rule[_].apply_server_side_encryption_by_default[_].sse_algorithm == "AES256"
}

# Deny if any S3 bucket is created or updated without AES256 encryption
deny[msg] {
 some i
 resource := input.resource_changes[i]
 resource.type == "aws_s3_bucket"
 resource.change.actions[_] == "create"
 not resource.change.after.server_side_encryption_configuration[_].rule[_].apply_server_side_encryption_by_default[_].sse_algorithm == "AES256"
 msg := sprintf("S3 bucket '%s' must have AES256 encryption enabled.", [resource.address])
}

deny[msg] {
 some i
 resource := input.resource_changes[i]
 resource.type == "aws_s3_bucket"
 resource.change.actions[_] == "update"
 not resource.change.after.server_side_encryption_configuration[_].rule[_].apply_server_side_encryption_by_default[_].sse_algorithm == "AES256"
 msg := sprintf("S3 bucket '%s' must have AES256 encryption enabled.", [resource.address])
}

To test this policy, you can use the opa eval command:

opa eval -i tfplan.json -d s3_encryption.rego "data.terraform.aws.s3.deny"


If your Terraform plan includes an S3 bucket without AES256 encryption, the opa eval command will return a denial message, indicating a policy violation.

How does OPA differ from Oso?

OPA is a general-purpose policy engine used to evaluate rules against JSON-based data inputs. It’s commonly applied to infrastructure and admission control policies like with Terraform and Kubernetes. Oso on the other hand focuses on application-level access control. It can help with with authorization challenges within your application such as determining if a user is allowed to take a certain action or view a certain document. They are complementary tools specializing in authorization for different parts of your stack.

As an example, engineering teams can centralize infrastructure policy using OPA (e.g., deny insecure configurations) and centralize application authorization logic using Oso (e.g., only grant edit access to users with ‘admin’ or ‘editor’ status). Each tool serves a purpose, and together they support a broader policy-as-code initiative.

When to choose Oso or OPA

This is a common question, and it's important to understand their distinct roles:

• Use Oso when implementing user and object level authorization logic inside an app (e.g., feature gating, permissions, role hierarchies).
• Use OPA when you need to validate resource configuration  across environments, especially in CI/CD or with infrastructure-as-code tools.

OPA shines in its ability to integrate with your infrastucture like Kubernetes and Terraform natively. Oso’s strength is in its ability to easily integrate into your application, simplifiying and centralizing authorization logic.

Conclusion

Adopting policy as code with OPA is great for managing your infrastructure. It brings the rigor and benefits of software development practices to your infrastructure, making it more secure, compliant, and manageable. While OPA handles the infrastructure side, remember that Oso is there to provide robust, fine-grained authorization within your applications. Used together, they create a powerful, layered approach to policy enforcement across your entire stack.

‍

How to secure Kubernetes with Open Policy Agent

In this article, we’ll cover using OPA Gatekeeper for maintaining security and compliance in your Kubernetes environment. Open Policy Agent (OPA) and its Kubernetes-specific integration, OPA Gatekeeper, address the challenges of security and compliance through a clean policy-as-code approach. This article explores what OPA and Gatekeeper are, how they integrate with your Kubernetes environment, and how to use them to enforce organizational security standards. Specifically, this guide will inform you on making your Kubernetes clusters more robust and less prone to misconfigurations.

What is Open Policy Agent (OPA)?

Open Policy Agent is an open-source, general-purpose policy engine that defines and enforces policies as code across your entire infrastructure stack. You can write rules once and apply them everywhere from microservices and APIs to CI/CD pipelines and Kubernetes.

OPA uses Rego for writing policy rules. Rego is designed to query and manipulate structured data like JSON. For example, you could use OPA to deny requests when container images do not come from approved registries. This approach decouples policy decision making from application logic. Your services ask OPA for decisions rather than containing hardcoded rules.

The policy-as-code approach enables version control, testing, and reuse of policies across different environments, making your security posture more consistent and manageable. OPA exposes APIs through HTTP or library calls to evaluate policy queries, acting as a centralized decision point where any component can ask, "Is this action allowed?" or "Does this configuration comply with our policies?".

If you’d like to go deeper on OPA and Rego, we have an entire tutorial with examples.

How OPA helps secure Kubernetes environments

In Kubernetes environments, admission controllers serve as the first line of defense for security and compliance enforcement. These plugins intercept API server requests before objects are persisted. OPA can be deployed as a dynamic admission controller to enforce custom policies on Kubernetes resources.

OPA integration provides flexible mechanisms for implementing fine-grained controls beyond Kubernetes' built-in validations. For example, you could use the OPA integration to mandate specific labels for auditing purposes, enforce resource limits, allow images from approved sources only, etc.

OPA evaluates each incoming object against organizational rules. Non-compliant configurations (such as Pods missing required securityContext settings) are rejected with clear explanatory messages, preventing misconfigurations from being applied.

Beyond real-time enforcement, OPA constantly audits existing resources for violations, detecting any drift from desired states. This provides a comprehensive approach to defining and enforcing cluster governance rules.

What is OPA atekeeper?

OPA Gatekeeper is the result of a collaboration between Google, Microsoft, Red Hat, and Styra to provide native OPA support in Kubernetes. It’s the Kubernetes-specific integration of OPA  designed to simplify policy decisions in Kubernetes environments. Gatekeeper extends the Kubernetes API with Custom Resource Definitions (CRDs) for policy enforcement. OPA Gatekeeper is implemented as a webhook that can both validate incoming requests and modify requests before allowing them to pass.

Gatekeeper enhances OPA with several Kubernetes-native features:

• ConstraintTemplates and Constraints: CRDs that declare policies as Kubernetes objects rather than raw configuration files, enabling policy management through kubectl
• Parameterization and Reusability: ConstraintTemplates serve as reusable policy definitions, while Constraints are parameterized instances, creating extensible policy libraries
• Audit Functionality: Continuous resource auditing against enforced policies, identifying violations in resources created before policy implementation
• Native Integration: Built-in Kubernetes tooling that registers as ValidatingAdmissionWebhook and MutatingAdmissionWebhook, ensuring real-time policy enforcement

Gatekeeper transforms OPA into a Kubernetes-native admission controller using a "configure, not code" approach. Instead of building custom webhooks, you write Rego policies and JSON configurations while Gatekeeper handles admission flow integration.

Working within the Kubernetes control plane

Gatekeeper integrates as a “validating admission webhook” within the API server's admission control pipeline. What does that actually mean? When requests to create or modify Kubernetes resources are sent, the API Server authenticates and authorizes them before invoking admission controllers.

The integration process works as follows: Gatekeeper registers a webhook with the API Server for admission events (Pod creation, Deployment updates, etc.). The API Server pauses requests and sends objects (wrapped in AdmissionReview) to Gatekeeper/OPA for evaluation. Using OPA, Gatekeeper evaluates objects against active policies (Constraints). Policy violations result in rejection responses with explanatory messages, while compliant requests are accepted and fulfilled.

A look at K8s Admissions Control Phases

Gatekeeper's admission webhook translates Kubernetes AdmissionReview requests into OPA's input format and queries the loaded Rego policies. The JSON structure passed to OPA includes object content, operations (CREATE/UPDATE), and user information. OPA outputs violations, which Gatekeeper translates into admission responses.

Beyond real-time enforcement, Gatekeeper provides background caching and auditing capabilities. It can replicate Kubernetes objects into OPA's data store, enabling policies to reference other cluster resources (e.g., "deny this Ingress if any other Ingress has the same hostname"). The audit controller periodically scans resources against policies, storing violation results in Constraint status fields for governance reporting.

To recap, Gatekeeper extends the Kubernetes control plane by adding two main things. The first is policy enforcement at admission time. The second is continuous audit capabilities. With OPA Gatekeeper, you’re able to get both of these functionalities without replacing core components of your Kubernetes environment. This architecture integrates cleanly with Kubernetes API machinery while respecting the platform's design principles.

Next we’ll go a little deeper into Constraint and take a look at a real-world example.

ConstraintTemplates and Constraints

ConstraintTemplate is a fundamental concept in OPA Gatekeeper. This Kubernetes Custom Resource Definition (CRD) defines new policy types, serving as blueprints that contain Rego evaluation code and parameter schemas for different policy uses.

When creating a ConstraintTemplate, you define a new constraint type for the Kubernetes API. For example, a template named "K8sRequiredLabels" creates a constraint kind "K8sRequiredLabels". Templates consist of two main components:

• Targets & Rego: The actual policy code that runs for admission requests. In Gatekeeper, the target is typically admission.k8s.gatekeeper.sh, applying to Kubernetes object admission events. Rego code produces violation[] or deny[] rules when policies are violated, causing Gatekeeper to block requests with explanatory messages.
• CRD Schema: Defines the structure of spec.parameters that users provide in Constraints. This enables policy reusability by allowing administrators to specify inputs (required labels, value ranges, etc.) when instantiating policies.

ConstraintTemplates alone do not enforce policies until you create Constraints, which are template instances. The workflow involves applying a ConstraintTemplate (registering the policy type), then applying Constraint resources to activate enforcement. Gatekeeper compiles Rego from all ConstraintTemplates and enforces policies when corresponding Constraints exist.

This pattern enables reusability and separation of concerns. Policy authors provide generic templates while cluster administrators instantiate them with organization-specific settings. For instance, a K8sRequiredLabels template can generate multiple Constraints: one requiring "owner" labels on Deployments, another requiring "environment" labels on Namespaces.

A Real-World Policy Example: Enforcing required labels

Let's make this concrete with an example. Imagine you want to ensure every Kubernetes Namespace has specific labels, perhaps to indicate the department or owner. Here is how you would do it with OPA Gatekeeper:

1. ConstraintTemplate example—required labels policy

apiVersion: templates.gatekeeper.sh/v1beta1
kind: ConstraintTemplate
metadata:
  name: k8srequiredlabels
spec:
  crd:
    spec:
      names:
        kind: K8sRequiredLabels
      validation:
        openAPIV3Schema:
          properties:
            message:
              type: string
            labels:
              type: array
              items:
                type: string
  targets:
    - target: admission.k8s.gatekeeper.sh
      rego: |
        package k8srequiredlabels

        violation[{"msg": msg}] {
          required := input.parameters.labels
          provided := input.review.object.metadata.labels
          missing := required[_]
          not provided[missing]
          msg := sprintf("Missing required label: %v", [missing])
        }

‍
This ConstraintTemplate defines a new policy type called K8sRequiredLabels. It specifies that this policy will take a message (string) and a list of labels (array of strings) as parameters. The Rego code then checks if all the specified labels are present on the incoming Kubernetes object.

2. Constraint Example—enforcing labels on namespaces

To actually enforce this, you would create a Constraint that uses this template:

apiVersion: constraints.gatekeeper.sh/v1beta1
kind: K8sRequiredLabels
metadata:
  name: namespace-must-have-owner-and-env
spec:
  match:
    kinds:
      - apiGroups: [""]
        kinds: ["Namespace"]
  parameters:
    message: "Namespaces must have 'owner' and 'environment' labels."
    labels:
      - owner
      - environment

This Constraint named namespace-must-have-owner-and-env uses our K8sRequiredLabels template. It is configured to match Namespace objects and requires them to have both owner and environment labels. If someone tries to create a Namespace without these labels, Gatekeeper will block the request and return the specified message.

Getting started with OPA Gatekeeper

Getting started with OPA Gatekeeper is straightforward. You can install it in your Kubernetes cluster using Helm or by applying the raw YAML manifests. The official Gatekeeper documentation provides detailed instructions for installation.

Once installed, you will want to:

1. Deploy ConstraintTemplates: Start by deploying the ConstraintTemplates that define the types of policies you want to enforce. You can find a library of common ConstraintTemplates in the Gatekeeper policy library.
2. Create Constraints: Instantiate Constraints from your ConstraintTemplates, specifying the parameters and the resources they should apply to.

1. Test your policies: Always test your policies thoroughly in a non-production environment first. Make sure they behave as expected and do not inadvertently block legitimate operations.
2. Monitor and audit: Use Gatekeeper's audit functionality to continuously monitor your cluster for policy violations and ensure compliance.

The best way to get started is to pick a simple policy, like requiring specific labels or enforcing resource limits, and implement that first. Get comfortable with the ConstraintTemplate/Constraint pattern and how Rego works. From there, you can gradually build up more complex policies as your needs evolve.

Conclusion

OPA Gatekeeper provides a powerful way to implement policy-as-code in your Kubernetes clusters. By combining the flexibility of OPA with Kubernetes-native integration, it enables you to enforce security and compliance policies consistently across your infrastructure. The ConstraintTemplate and Constraint pattern makes policies reusable and maintainable, while the audit functionality helps you maintain ongoing compliance.

OPA Gatekeeper is a robust solution that integrates seamlessly with your existing Kubernetes workflows. Start with simple policies and gradually build up your policy library as you become more comfortable with the system. Best of luck!

‍

‍

‍

‍

1. Introduction to Open Policy Agent (OPA)

If you're building modern applications, especially those using microservices or Kubernetes, you've probably bumped into the challenge of authorizing access to infrastructure. It's not just about who can log in, but what services they can access once they're in, and what those services can access. Today I want to discuss OPA and how we can use it to reason about and implement policy enforcement.

So, what exactly is OPA? At its core, OPA is an open-source, general-purpose policy engine. Think of it as a brain that makes decisions about whether something is allowed or not. The beauty of OPA is that it decouples policy decision-making from policy enforcement. This means your application or service doesn't need to know how to make a policy decision, it just needs to ask OPA, "Is this allowed?" and OPA will give a clear answer.

This is super important, because without proper consideration, you can end up with a hard to manage mess of policies sprinkled all throughout your code. You have policies for who can access your APIs, what containers can run in Kubernetes, how your CI/CD pipelines behave, and even what data can be accessed in your databases. Trying to hardcode these policies into every single service is a nightmare to manage and update. OPA provides a unified way to manage all these policies as code, making them consistent, auditable, and much easier to maintain.

Here's how it generally works: Your software queries OPA, providing structured data (usually JSON) as input. This input could be something like a user's identity, the resource they're trying to access, the time of day, or even environmental variables. OPA then evaluates this input against its policies, which are written in a high-level declarative language called Rego. The output is a decision, which can be a simple allow/denyor more complex structured data, depending on what your policy needs to convey.

In this article, I'm going to walk you through some practical examples and use cases where OPA truly shines. We'll dive into the details of Rego and see how you can use OPA to solve real-world authorization challenges. Let's get started!

2. Understanding Rego: OPA's Policy Language

Now that you have a grasp of what OPA is, let's talk about Rego. Rego is the language you'll use to write your policies in OPA. It's a declarative language, which means you describe what you want to achieve, not how to achieve it. It's specifically designed for expressing policies over complex, hierarchical data structures like JSON.

In Rego, policies are defined as rules. These rules essentially define what is true or false based on the input data. Let's look at some core concepts:

Rules

Rules in Rego can be either complete or partial.

• Complete Rules: These assign a single value to a variable. For example, a rule that defines whether a request is allowed or denied.

default allow = false

allow {
    input.method == "GET"
    input.path == ["users"]
}

In this simple example, allow is true only if the input method is "GET" and the path is "users". Otherwise, it defaults to false. This means that the following input would result in true .

"input": {
  "method": "GET",
  "path": ["users", "123"]
}

‍


• Partial Rules: These generate a set of values and assign that set to a variable. This is useful for collecting multiple results that satisfy a condition.

allowed_users[user] {
    data.users[user].role == "admin"
}

‍

This rule would create a set of all users who have the role "admin".

So given the following input,

{
  "users": {
    "alice": { "role": "admin" },
    "bob": { "role": "user" },
    "charlie": { "role": "admin" }
  }
}

‍


you’d get this out.

allowed_users = {"alice", "charlie"}

‍


Expressions

Rego policies are built using expressions. Multiple expressions within a rule are implicitly joined by a logical AND. All expressions must evaluate to true for the rule to be true. For example:

allow {
    input.user == "alice"
    input.action == "read"
    input.resource == "data"
}

‍‍


Here, all three conditions must be met for allow to be true. Here’s an example input that would result in  true.

{
  "user": "alice",
  "action": "read",
  "resource": "data"
}

Variables

You can use variables to store intermediate values or to iterate over collections. Variables are assigned using the := operator. OPA will find values for variables that make all expressions true.

allow {
    user := input.user
    data.roles[user] == "admin"
}

‍‍


In this case, user is assigned the value of input.user, and then that user is checked against the data.roles to see if they are an "admin".

Iteration

Iteration in Rego often happens implicitly when you use variables in expressions. For example, to check if any element in a list meets a condition, you can use a variable to represent each element:

allow {
    some i
    input.roles[i] == "admin"
}

‍


This rule would be true if any of the roles in input.roles is "admin". The some keyword is used to declare local variables that are used for iteration.

If you want to return true if roles only contains admin, then you can do the following.

allow {
    not some i
    input.roles[i] != "admin"
}

‍


This says “Allow if there does not exist any index i such that input.roles[i] != "admin"”. In other words, all roles must be “admin”.

This is just a quick overview of Rego basics. The official OPA documentation is an excellent resource for a deeper dive. Now, let's get into some real-world use cases!

3. OPA Use Cases and Practical Examples

Now let’s se OPA in action! I’ve picked out five common scenarios where OPA can be incredibly powerful. For each, I’ll give you a brief scenario, explain how OPA fits in, and provide a Rego policy example.

Use Case 1: Attribute-Based Access Control (ABAC) for Cloud Resource Access

Imagine you’re managing access to cloud resources (e.g., AWS S3 buckets, Azure Blob Storage, Google Cloud Storage). It’s not enough to just know who is trying to access a resource; you need granular control based on various attributes. For instance, a user might only be allowed to access a specific S3 bucket if they are part of a certain team, the request originates from a whitelisted IP range, and the time of day is within business hours. This is a classic ABAC problem, where access decisions are based on attributes of the user, the resource, the environment, and the action.

How OPA helps: OPA is perfectly suited for ABAC because Rego excels at evaluating complex conditions based on structured data. You can feed OPA all the relevant attributes (user roles, source IP, time of day, resource tags, etc.), and your Rego policy will determine if the access is authorized.

Let’s look at a simplified example for controlling access to an S3 bucket. We want to ensure that:

1.The user is part of the 'devops' team.

2.The request comes from an IP within the corporate network range.

3.The access attempt is during business hours (9 AM to 5 PM UTC).

Here’s how you might write a Rego policy for this:

default allow = false

allow {
    input.user.team == "devops"
    is_from_whitelisted_ip
    is_during_business_hours
}

is_from_whitelisted_ip {
    ip_range_contains("192.168.1.0/24", input.source_ip)
}

is_during_business_hours {
    current_hour := time.now_ns() / 1000000000 / 60 / 60 % 24
    current_hour >= 9
    current_hour < 17
}

# Helper function to check if an IP is within a CIDR ip_range_contains(cidr, ip) if {
    # Simplified for example, real implementation would parse CIDR and IP
    # and perform network calculations.
    startswith(ip, "192.168.1.")
}

{
  "user": {
    "name": "alice",
    "team": "devops"
  },
  "source_ip": "192.168.1.50",
  "action": "read",
  "resource": "s3_bucket_logs"
}

‍


If you were to run this with opa eval -d policy.rego -i input.json "data.app.abac.allow", the output would be true (assuming the current time is within business hours and the IP is whitelisted). This demonstrates how OPA can enforce attribute-based policies for infrastructure access.

Use Case 2: Role-Based Access Control (RBAC) for Server Access

Let's say you have a fleet of servers, and different teams or individuals need varying levels of access to them. For example, 'network admins' can configure network interfaces, 'devops' can deploy applications, and 'auditors' can only view logs.

In this kind of scenario, OPA can centralize your infrastructure’s RBAC policies. This makes it easier to manage user roles and their associated permissions across your server fleet. Instead of scattering authorization logic across SSH configurations or individual server scripts, you define it once in OPA. When a user tries to perform an action on a server, your system queries OPA with the user's role and the requested action. Then OPA returns whether it's allowed.

Here’s a Rego policy that implements a basic RBAC system for server access:

default allow = false

# Allow if the user has the required role for the action on the resource
allow {
    some role in data.user_roles[input.user]
    some grant in data.role_grants[role]
    input.action == grant.action
    input.resource_type == grant.resource_type
}

‍
The above Rego code is analogous to the following pseudocode in Python.

for role in data.user_roles[input.user]:
    for grant in data.role_grants[role]:
        if input.action == grant["action"] and input.resource_type == grant["resource_type"]:
            allow = True

‍‍Input Data (example data.json):‍

# Example: network_admin can configure network interfaces
# Example: devops can deploy applications
# Example: auditor can view logs

{
    "user_roles": {
        "alice": [
            "auditor"
        ],
        "bob": [
            "devops",
            "network_admin"
        ],
        "charlie": [
            "auditor",
            "devops"
        ]
    },
    "role_grants": {
        "auditor": [
            {
                "action": "view",
                "resource_type": "logs"
            }
        ],
        "devops": [
            {
                "action": "view",
                "resource_type": "logs"
            },
            {
                "action": "deploy",
                "resource_type": "application"
            }
        ],
        "network_admin": [
            {
                "action": "view",
                "resource_type": "logs"
            },
            {
                "action": "deploy",
                "resource_type": "application"
            },
            {
                "action": "configure",
                "resource_type": "network_interface"
            }
        ]
    }
}

‍
Input Query (example input.json for Alice trying to view logs)‍

{
  "user": "alice",
  "action": "view",
  "resource_type": "logs"
}

‍Running opa eval -d policy.rego -d data.json -i input.json "data.app.rbac.allow" would return true for Alice. If Alice tried to deploy an application, it would return false. This example shows how you can define roles and their permissions for infrastructure components, and then easily check if a user, based on their assigned roles, is authorized to perform a specific action. It’s a clean and scalable way to manage access control for your infrastructure.

Use Case 3: Kubernetes Admission Control

Scenario: Kubernetes is fantastic for orchestrating containers, but how do you ensure that only approved images are deployed, or that all deployments have specific labels for cost allocation or security? Kubernetes Admission Controllers intercept requests to the Kubernetes API server before objects are persisted. This is a perfect choke point for policy enforcement.

How OPA helps: OPA can act as a validating or mutating admission controller in Kubernetes. This means you can write policies in Rego that dictate what can and cannot be deployed to your clusters, or even modify resources on the fly. This is incredibly powerful for maintaining security, compliance, and operational best practices across your Kubernetes environments. If you're a company that needs strict control over your Kubernetes deployments, OPA as an admission controller is, in my opinion, a must-have.

Let's consider a policy that prevents deployments from using images from unapproved registries and ensures all deployments have a team label.

default allow = false

allow {
    input.request.kind.kind == "Pod"
    image_is_approved
    has_team_label
}

image_is_approved {
    some i
    image := input.request.object.spec.containers[i].image
    startswith(image, "approved-registry.com/")
}

has_team_label {
    input.request.object.metadata.labels.team
}

Input Query (example input.json for a Pod creation request):

{
  "apiVersion": "admission.k8s.io/v1",
  "kind": "AdmissionReview",
  "request": {
    "uid": "705ab455-63f4-11e8-b7ad-0242ac110002",
    "kind": {
      "group": "",
      "version": "v1",
      "kind": "Pod"
    },
    "resource": {
      "group": "",
      "version": "v1",
      "resource": "pods"
    },
    "object": {
      "metadata": {
        "labels": {
          "app": "my-app",
          "team": "devops"
        }
      },
      "spec": {
        "containers": [
          {
            "name": "my-container",
            "image": "approved-registry.com/my-image:latest"
          }
        ]
      }
    }
  }
}

‍
Running opa eval -d policy.rego -i input.json "data.kubernetes.admission.allow" would return true for this valid request. If the image was from unapproved-registry.com or the team label was missing, the policy would evaluate to false, and Kubernetes would reject the admission request. This provides a robust and centralized way to enforce policies in your Kubernetes clusters.

Use Case 4: API Gateway Authorization

Scenario: Your microservices architecture likely exposes APIs through an API Gateway. This gateway is the first line of defense for your backend services. You need to authorize incoming requests, perhaps based on JWT claims, IP addresses, or even rate limits. Hardcoding this logic into each microservice is inefficient and error-prone.

How OPA helps: OPA can be integrated with API Gateways (like Envoy, Kong, or AWS API Gateway) to offload authorization decisions. When a request comes into the gateway, it sends the request details (headers, body, path, method) to OPA. OPA evaluates these details against your policies and sends back an allow/deny decision. This centralizes your API authorization logic, making it easier to manage and update policies across all your APIs.

Let's imagine a policy where only authenticated users with a specific role can access a sensitive API endpoint, and only from a whitelisted IP range.

default allow = false

allow {
    input.method == "GET"
    input.path == ["v1", "sensitive_data"]
    is_authenticated
    has_required_role
    is_from_whitelisted_ip
}

is_authenticated {
    input.headers.authorization
    # In a real scenario, you'd decode and validate the JWT here
    # For simplicity, we just check for presence of the header
}

has_required_role {
    input.jwt_claims.roles[_] == "admin"
}

is_from_whitelisted_ip {
    ip_range_contains("192.168.1.0/24", input.source_ip)
}

# Helper function to check if an IP is within a CIDR range
# This would typically be a built-in or a more robust library function
ip_range_contains(cidr, ip) if {
    # Simplified for example, real implementation would parse CIDR and IP
    # and perform network calculations.
    # For demonstration, let's assume a simple string match for now.
    startswith(ip, "192.168.1.")
}

Input Query (example input.json for a valid API request):

{
  "method": "GET",
  "path": ["v1", "sensitive_data"],
  "headers": {
    "authorization": "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
  },
  "jwt_claims": {
    "sub": "user123",
    "roles": ["user", "admin"]
  },
  "source_ip": "192.168.1.100"
}

Running opa eval -d policy.rego -i input.json "data.api.authz.allow" would return true for this request. If the user didn't have the admin role, or the request came from an unwhitelisted IP, OPA would return false, and the API Gateway would block the request. This centralized approach to API authorization is, in my opinion, a much cleaner way to manage access to your services.

Use Case 5: CI/CD Pipeline Policy Enforcement

Scenario: In a fast-paced development environment, ensuring that your CI/CD pipelines adhere to security, compliance, and operational best practices is crucial. This could involve mandating code reviews for all merges to main, ensuring that specific security scans are run before deployment, or restricting deployments to production environments based on certain criteria (e.g., only from specific branches or by authorized personnel).

How OPA helps: OPA can be integrated into various stages of your CI/CD pipeline to enforce policies. This allows you to "shift left" on security and compliance, catching issues earlier in the development lifecycle. By externalizing these policies to OPA, you keep your pipeline scripts clean and focused on their primary tasks, while OPA handles the complex policy evaluations. If you're looking to automate and standardize your pipeline governance, OPA is an excellent choice.

Let's create a policy that ensures all deployments to the production environment must originate from the main branch and have been approved by at least two reviewers.

default allow = false

allow if {
    input.environment == "production"
    input.source_branch == "main"
    input.pull_request.approvals >= 2
}

‍


Input Query (example input.json for a production deployment request):

{
  "environment": "production",
  "source_branch": "main",
  "pull_request": {
    "id": "pr-123",
    "approvals": 2,
    "status": "merged"
  },
  "user": "dev_lead"
}

‍Running opa eval -d policy.rego -i input.json "data.ci_cd.policy.allow" would return true for this deployment. If the source_branch was feature/new-feature or approvals was less than 2, the policy would return false, preventing the deployment. This helps ensure that only well-vetted and compliant code makes it to your critical environments. In my experience, this kind of automated governance is invaluable for maintaining high standards in continuous delivery.

4. OPA vs. Oso: When to Use Which?

So now that we have a good idea of how OPA and Rego work, you’re probably wonder if you should implement this in your system. One question you want to answer is whether you want to go with native OPA or use Oso. Both are fantastic tools for authorization, but they shine in different contexts. Think of it this way:

OPA: The Heavyweight, Flexible, Infra-Friendly Policy Engine

In my opinion, OPA is your go-to when you need to enforce policies outside your application. It's designed to be a general-purpose policy engine that can be integrated across your entire stack. This includes:

• Infrastructure: Kubernetes admission control, Terraform policy enforcement.
• Microservices: API Gateway authorization, service-to-service authorization.
• CI/CD Pipelines: Ensuring compliance and security throughout your deployment process.

OPA is incredibly flexible because it decouples policy from enforcement. You write your policies in Rego, and then various services query OPA for decisions. This makes it ideal for broad, system-level policy enforcement where you need a consistent policy layer across diverse technologies. If you're building a large, distributed system and need a centralized policy decision point for your infrastructure and services, OPA is, in my humble opinion, the clear winner.

Oso: The Batteries-Included Tool for Modern Apps

Oso, on the other hand, is built for enforcing access logic inside your application. It's a batteries-included framework that simplifies adding authorization directly into your application code. Oso provides libraries for various languages (Python, Node.js, Go, Rust, etc.) and a declarative policy language called Polar.

Oso is perfect for scenarios where you need fine-grained, application-specific authorization, such as:

• User Permissions: Determining what a specific user can do within your application (e.g., "Can Alice edit this document?").
• Multi-tenancy: Managing access to resources across different tenants.
• Resource-level Authorization: Controlling access to individual resources based on ownership or relationships.

If you're a developer building a new application and you want to quickly and effectively implement authorization logic directly within your codebase, Oso is an excellent choice. It's designed to be developer-friendly and provides a more integrated experience for application-level authorization.

Practical Guidance on Choosing

Here's how I think about it:

• Use OPA where you enforce policies outside the app. This means policies related to your infrastructure, network, or inter-service communication. It's about controlling the environment your applications run in.
• Use Oso where you enforce access logic inside the app. This is about controlling what users can do with the data and features within your application.

It's not necessarily an either/or situation. Many organizations might find value in using both. For example, you could use OPA for your Kubernetes admission control and API Gateway authorization, while using Oso to manage user permissions within your application's backend. The key is to understand their strengths and apply them where they make the most sense for your specific authorization challenges.

5. Conclusion

It was quite the journey, but we did it. We looked at five practical examples showcasing the power and versatility of Open Policy Agent. From fine-grained ABAC and RBAC within your applications to robust policy enforcement in Kubernetes, API Gateways, and CI/CD pipelines, OPA provides a consistent and scalable way to manage authorization across your entire stack. Its declarative policy language, Rego, allows you to express complex rules with clarity and precision.

We also touched upon the distinction between OPA and Oso. In my opinion, understanding their core strengths is key: OPA excels at externalizing policy decisions for your infrastructure and services, while Oso is a fantastic tool for building application-level authorization directly into your code. Both are powerful, and often, they can complement each other beautifully in a comprehensive authorization strategy.

‍

‍

This article explores five alternatives to Open Policy Agent (OPA) that offer compelling features for different authorization requirements. We'll examine what makes each solution unique and help you determine which might be the right choice for you.

‍

Understanding Open Policy Agent and Its Limitations

Before diving into alternatives, let's establish what Open Policy Agent is, the use cases where it shines, and where it might fall short for certain applications.

Open Policy Agent is an open-source, general-purpose policy engine that provides unified policy enforcement across the stack. It uses a high-level declarative language called Rego for policy definition and can be deployed as a sidecar, host-level daemon, or library. In general, teams use Open Policy Agent to enforce policy within cloud infrastructure.

While OPA offers flexibility as a general-purpose policy engine, this broad focus comes with tradeoffs:

• The Rego language has a significant learning curve
• As a general-purpose tool, it lacks application-specific authorization primitives
• Implementation requires substantial custom integration work
• Performance can be a concern in high-throughput scenarios

These limitations have led many development teams to seek alternatives that better align with their specific authorization needs.

‍

Alternative 1: Oso

Oso takes a fundamentally different approach to authorization by focusing specifically on application authorization rather than being a general-purpose policy engine. This specialized focus translates to practical advantages for development teams.

Key Differentiators:

• Purpose-built for application authorization: Unlike OPA's general-purpose approach, Oso’s policy language, Polar, provides primitives specifically designed for application authorization patterns[1]
• High-performance data model: Oso’s data model is optimized for authorization operations. Oso can even work directly with your application data when you need to squeeze every last bit of performance out of larger operations like filtering lists.
• Developer-friendly implementation: The authorization logic can mirror your application code, reducing the complexity of implementation

Oso's specialized focus makes it particularly well-suited for teams that need to implement application authorization models like role-based access control (RBAC), attribute-based access control (ABAC), or relationship-based access control (ReBAC) without the overhead of a general-purpose policy engine.

‍

Alternative 2: AWS Cedar

AWS Cedar represents another specialized approach to authorization, with a focus on readability and application-level authorization.

Key Differentiators:

• Readability focus: Cedar's policy language prioritizes human readability and understanding while also providing a syntax that resembles AWS IAM definitions. It occupies a middle ground between Rego and Polar.
• Structured design: Cedar offers a more structured approach to policy definition compared to OPA's Rego
• Application-level authorization: Like Oso, Cedar focuses specifically on application authorization rather than general policy enforcement

Cedar's safety-oriented approach and fine-grained permissions make it a strong contender, particularly for applications on AWS. However, it has limited tooling and smaller community support compared to more established alternatives.

‍

Alternative 3: Google Zanzibar Based Tools

For applications that need to manage complex relationship-based permissions at scale, tools like AuthZed or Auth0, which are based on Google Zanzibar, offer a compelling alternative to OPA.

Key Differentiators:

• Graph-based authorization model: Zanzibar clones excel at managing access control via relationships
• Single source of truth: Systems based on Zanzibar centralize the source of authorization decisions
• Relationship-focused: Particularly strong for applications where permissions depend on complex relationships between users and resources

While Zanzibar offers powerful capabilities for relationship-based authorization, it introduces system complexity by requiring centralization of all authorization data. As a result, you will need to store, copy, and sync data across your application and your authorization service. It also forces you to model your authorization logic as relationships, which makes it challenging to implement ABAC.

‍

Alternative 4: XACML

The eXtensible Access Control Markup Language (XACML) represents a standards-based approach to authorization that predates OPA and other newer alternatives.

Key Differentiators:

• Standardized approach: As an OASIS standard, XACML offers a well-defined, standardized framework
• Mature ecosystem: With a longer history, XACML has established patterns and implementations
• Comprehensive model: Includes a complete policy language, architecture, and request/response protocol

However, XACML's XML-based approach can be verbose and complex compared to newer alternatives, and it may not be as well-suited for modern cloud-native applications as some of the other options discussed here[2].

‍

Alternative 5: Hashicorp Sentinel

Rounding out our alternatives is Hashicorp Sentinel, which takes yet another approach to policy as code.

Key Differentiators:

• Infrastructure focus: Particularly strong for infrastructure-related authorization decisions
• Hashicorp ecosystem integration: Works seamlessly with other Hashicorp products
• Embedded policy engine: Designed to be embedded within other Hashicorp applications and services

Sentinel's focus on infrastructure makes it particularly valuable for teams that need to enforce policies across Hashicorp-based infrastructure as code deployments. It’s not suited for application authorization.[3].

‍

Choosing the Right Authorization Solution

When evaluating these alternatives to Open Policy Agent, consider these key factors:

• Use case: Are you looking for infrastructure or application authorization?
• Integration complexity: How much custom work will be required to implement the solution?
• Performance requirements: Can the solution meet your latency and throughput needs?
• Team expertise: Which solution aligns best with your team's existing knowledge and skills?
• Deployment model: Does the solution support your required deployment scenarios?

The right choice depends heavily on your specific requirements. For teams building complex applications with sophisticated authorization needs, purpose-built solutions like Oso often provide advantages over general-purpose policy engines like OPA.

‍

Comparing Key Features

‍

Implementation Considerations

Before implementing any authorization solution, consider these questions:

• How easy is it to get started? Is it a cloud service or do you have to deploy it to your infrastructure?
• How much support does it require? Do you have the capacity and infrastructure to provide it?
• What’s the developer experience like? Is it easy to onboard new developers and integrate with your existing development process?
• How is the documentation? Can you quickly find the information you need?
• Does the solution support your authorization needs? Will it support them in 6 months? A year? Beyond?
• Will the solution meet your current performance requirements? Will it continue to do so as your application grows?

‍

Conclusion

While Open Policy Agent offers a flexible, general-purpose approach to policy enforcement, purpose-built alternatives often provide advantages for specific authorization scenarios. By understanding the strengths and limitations of each option, you can select the solution that best fits your unique requirements.

For teams building complex applications with sophisticated authorization needs, solutions like Oso that focus specifically on application authorization often provide the best balance of power, flexibility, and developer experience. The right choice ultimately depends on your specific requirements, existing technology stack, and team expertise.
‍

Citations

[1] https://www.osohq.com/post/oso-vs-opa-open-policy-agent-alternatives

[2] https://www.styra.com/blog/opa-vs-xacml-which-is-better-for-authorization/

[3] https://www.jit.io/resources/security-standards/5-use-cases-for-using-open-policy-agent

‍

Open Policy Agent (OPA) is a general-purpose policy engine that helps with policy enforcement in cloud infrastructure. OPA allows users to define and enforce policies across a wide range of systems, ensuring compliance and security in dynamic environments.

I have always considered OPA to be one of the most important advancements for cloud infrastructure. In my experience, absent a bespoke solution (e.g. Oso), a rigorous OPA implementation makes for stronger enterprise software.

To implement the OPA engine, you submit a request in the form of a JSON or YAML object. OPA evaluates this incoming request against its policies and data to give a policy determination. You can think of the determination as a decision: approved or declined. It is now up to your software to enforce this decision.

‍

‍

‍

Decoupling Policy Logic and Business Logic

One of the main reasons to use OPA is that it allows you to decouple policy decision making from the business logic of your services. OPA helps you determine the decision of a policy while your software enforces that decision. This allows you to manage policies in one place rather than coordinating policy changes in the business logic of several systems which could be written in different languages and managed by different teams.

‍

‍

‍

What is Rego?

Rego is the custom language that OPA uses for writing policies. It is a declarative language designed for inspecting and transforming structured data, like JSON and YAML that is used for expressing access to cloud infrastructure.

Rego was inspired by Datalog, but extended to support structured document models such as JSON and YAML. Some developers consider it particularly confusing (evidenced by this Reddit thread), but Rego is the language of choice for Opa users.

‍

‍

‍

How do you create an OPA policy?

Authorization in OPA starts with loading your authorization data in a structured format like JSON. You then write policy rules in Rego to transform the data as needed in order to derive the authorization context of the data. An example of this could be determining a user’s role or figuring out which organization a file belongs to. When the data is in the right structure, you inspect it to determine whether to allow or deny a request.

‍

‍

‍

How would you design RBAC using OPA?

RBAC, which stands for Role-Based Access Control, is a broad classification for using roles to control the access that users have to resources. Most people are familiar with the concept of roles, and expect them to be a part of any authorization system. For many app developers, roles are the first and fastest step in implementing application authorization.

To design an RBAC system using OPA, you’ll first need to assign roles to all of your users. We’ll do that using a dictionary.  In our case we have two roles: admin and member. Alice is both an admin and a member while Bob is only a member.

Based on their roles, Alice and Bob will have different permissions. We’ll need to define the various permissions that each role has. In the example below, a member can only “read” the Acme repository while an admin can “write” and “delete” the repository.

With these data structures in place, we’ll need to implement logic to determine whether a user has permission to perform a given action based on their role. Given a user, we’ll need to first determine what roles they have. Then, across all of their roles, we need to see what permissions they have.

In this simple example, you can see that we defined a policy that determines what permissions our users have. With this policy defined, we can determine if a given user has permissions to do the requested action.

‍

‍

‍

What does OPA do well?

OPA is a great general-purpose policy engine. It’s designed to accept data from a variety of systems in their native format. Its rules language, Rego, provides primitives that allow you to transform and inspect its data as needed during evaluation to make authorization decisions. In this way, OPA emphasizes interoperability with third-party systems, where the data isn’t under your direct control. It is also well suited to machine-to-machine operations.

‍

‍

‍

What are Open Policy Agent alternatives?

Oso is a good alternative to OPA for use cases like application authorization.

Oso’s policy language, Polar is built around the higher-order entities that you model in applications, such as actors, roles, and relationships. This makes it a natural fit for the application authorization domain.

If this space is relevant to you, I would recommend reading our overview of the distinctions between Open Policy Agent and Oso.

‍

‍

‍

Looking for an authorization service?

Engineering teams are increasingly adopting services for core infrastructure components, and this applies to authorization too. There are a number of authorization-as-a-service options available. OPA is a popular general-purpose policy engine that implements authorization logic as low-level operations on structured data.

Oso Cloud is a managed authorization service that is tailored to Application Authorization. You use Oso Cloud to provide fine-grained access to resources in your app, to define deep permission hierarchies, and to share access control logic between multiple services in your backend. You do all this by using the same sorts of higher-order entities that you’re already modeling in your application: users, roles, relationships, attributes.

Oso also comes with built-in primitives for patterns like RBAC and ReBAC, and it is extensible for other use cases like attribute-based access control (ABAC). It is built using a best practices data model that makes authorization requests fast and ensures that you don’t need to make schema changes to make authorization changes. It provides APIs for enforcement and data filtering. Oso Cloud is also deployed globally for high availability and low-latency.

Oso Cloud is free to get started – try it out. If you’d like to learn more about Oso Cloud or ask questions about authorization more broadly, set up a 1x1 with an Oso engineer.

‍

‍

‍

Common questions related to OPA

How much does OPA cost?

OPA is free and is available under an Apache License 2.0.

Who develops OPA?

OPA is developed by the OPA community. It was originally created by Styra, but Apple hired the maintainers of OPA in August 2025.

How do I get started with Rego?

The best place to get started with Rego is to read the Rego documentation on the OPA website.

‍

OpenFGA is an open-source authorization framework.

Both it and its commercial counterpart, Okta FGA, are interpretations of the Zanzibar whitepaper, which describes the Relationship-Based Access Control (ReBAC) authorization model used at Google. OpenFGA allows developers to define complex application authorization policies using a declarative language.

Why consider alternatives to OpenFGA?

While OpenFGA offers powerful capabilities for access control, you may want to consider alternatives based on specific needs such as ease of implementation and cost of maintenance.

OpenFGA requires that you to replicate data to a secondary data store, which may create more operational overhead than you want to take on. Its rigid ReBAC implementation may not map naturally to your authorization logic. These considerations determine how well a given solution meets your specific organizational constraints and development requirements.

Top 4 alternatives to OpenFGA

The following section will compare and contrast Oso Cloud, Permit.io, Permify and AuthZed.

1. Oso Cloud

Oso Cloud provides application authorization as a service. It diverges from OpenFGA and other Zanzibar-based ReBAC implementations in two fundamental ways.

a. Data architecture: Oso Cloud is able to answer authorization questions using data directly from your application databases. You can gain all the benefits of centralizing your authorization logic - discoverability, sharing, testing - without having to build extra logic to synchronize you application data to Oso Cloud. When you’re getting started with Oso Cloud,  you can focus entirely on your authorization logic. You don’t have to worry about how to get your data to it. But don’t worry - if you decide later that you want to centralize some or all of your authorization data, Oso Cloud supports that, too.
Whether you use OpenFGA or Okta FGA, you have to copy your authorization data out of your application databases to a separate store that the service uses specifically to answer authorization questions. This introduces all the extra overhead that comes with maintaining  two sources of truth: initial data replication, two-phase commits, and drift detection and remediation. You’ll need to manage this from the start.

b. List filtering and LLM permissions. Oso enables you to easily answer questions like “What are all the documents this user can view?” Oso generates filters from your authorization policy so your database returns only authorized results. This is especially important for AI use cases where you need to ensure AI pipelines (search, RAG) return only the data a user is authorized to access. 

OpenFGA was designed for static, relationship-only permissions, not dynamic AI pipelines. List filtering queries are inefficient and can take seconds, making them unusable for AI responses.

c. Semantic flexibility: Authorization logic in Oso Cloud is written in the Polar language. Polar is a general purpose logic language that allows you to ask authorization questions in direct terms. Fundamentally, authorization is the act of answering the question “Can User A perform action B on Entity C?” In a ReBAC model like OpenFGA, you can’t ask this question. Instead, you have to ask “Does User A have relation R with Object O?”

d. Expressive logic: Likewise, OpenFGA and similar systems are only capable of expressing authorization logic in terms of relationships. While it’s possible to do this, in reality much authorization logic isn’t relational. This makes it difficult to support common use cases like global permissions and public objects in OpenFGA. Rather than simply granting an administrator edit access to all organizations or marking a document as public, you have to work around the constraints of the language to figure out how to make those rules look like relationships. In Polar, you can directly express these ideas.

2. Open Policy Agent

Open Policy Agent (OPA) is an open-source policy engine for policy enforcement across your stack. Teams use OPA to enforce policy-as-code across microservices, kubernetes, and other infrastructure components.

• Deployment model: OPA can be deployed as a sidecar, host-level daemon, or library.
• Modeling: OPA uses a high-level declarative language called Rego for policy definition. While powerful, the Rego language has a significant learning curve. As a general-purpose tool, it also lacks application-specific authorization primitives.
• Data: OPA accepts data from a variety of systems in their native format, and Rego allows you to transform data to enforce authorization decisions.

While OPA is available as open source software, its maintainers were recently hired by Apple, and there is no longer a commercial company or offering behind it.

‍

3. Permify

Permify is an open-source, Zanzibar-based solution similar to OpenFGA. It is the most pure open-source implementation in this evaluation.

a. Deployment Model: Permify is a self-hosted solution that you deploy on your infrastructure. They provide a docker container or you can build it from the source code.

b. Data Management: Permify stores authorization data in a dedicated store that you set up within your infrastructure.

c. Modeling: Both OpenFGA and Permify are ReBAC solutions inspired by Google Zanzibar. Permify provides an attribute extension that supports attribute-based access control (ABAC) scenarios like public documents more naturally.

4. AuthZed / SpiceDB

Authzed is another Zanzibar-based authorization as a service solution. It provides managed and self-hosted implementations based on the open-source SpiceDB project.

a. Deployment Model: AuthZed provides both cloud and on-premises deployments. It is distributed as a docker container, in the package managers of most common Linux distributions, or as a chocolatey package on Windows.

b. Data Management: AuthZed stores authorization data in a dedicated store that you deploy and manage within your infrastructure. It offers the widest database support of all the solutions evaluated here.

c. Modeling: Both OpenFGA and Authzed define pure Zanzibar-based ReBAC authorization models.

Feature comparison table

‍

Why choose Oso Cloud over OpenFGA?

Oso Cloud and OpenFGA are both powerful application authorization solutions. Oso Cloud provides the Polar language, which allows you to express all of your authorization logic in the most natural terms. OpenFGA is based on Google Zanzibar, and as a result requires you to express all of your authorization logic in terms of a relationship between two objects. Oso Cloud can use your application data in-place, so you don’t have to synchronize anything to an external store to start answering authorization questions.

OpenFGA and Okta FGA both require you to copy authorization data to an external data store, which creates extra operational overhead for your team. Oso Cloud provides that more streamlined onboarding experience of the two. Because it always allows you to express your authorization logic in the terms that best fit your mental model, it is also the easier solution to maintain over time.

Conclusion

OpenFGA is a powerful solution for application authorization. But you may find that other options better meet your needs. If you’re already using a policy engine like OPA or AWS Cedar, or if you want to make it easier for business users to manage authorization logic, then Permit.io is a great choice. If open-source is a priority, then take a look at Permify. If you want support for a wide variety of databases, then look at authzed.

For all their strengths, all of the above solutions introduce friction into the developer experience. Whether they force you into an unnatural mental model, require a data replication mechanism, or simply lack dedicated, reliable support, you may find that while they meet your authorization requirements, they fall short of your organizational needs.

Oso Cloud has been built from the start to provide an exceptional developer experience. It allows you to model your logic in the terms you already use to think about it. It lets you keep your data in one place, simplifying your code and your infrastructure. This creates a simple path to adoption while supporting the most sophisticated application requirements. Oso provides comprehensive testing and diagnostic features as well as an unmatched support experience to make sure you get to production with confidence.

Ready to give Oso Cloud a try? Head over to our Quickstart to get up and running in a few minutes! Still have questions? Reach out to us on Slack. We’d love to talk authorization with you.

‍

Introduction

If you’ve ever checked into a hotel, you’ve already experienced the difference between authentication (AuthN) and authorization (AuthZ). When you show your ID at the front desk, you’re proving who you are—that’s authentication. Once your identity is confirmed, the hotel decides what you can access: which room you get a key for, whether you can use the pool, gym, or member lounges. That’s authorization.

AuthN and AuthZ sound similar, and sometimes people use them interchangeably, but they actually solve two very different problems in your codebase. AuthN confirms your identity, while AuthZ determines what actions and resources you can access based on factors like your role or team. Understanding the difference is essential for building secure systems and making sure users only get access to what they’re allowed.

TL;DR

‍

AuthN confirms identity, while AuthZ controls access based on that identity. Both are essential for secure applications.

Core Differences

AuthN and AuthZ might seem like two sides of the same coin, and it’s easy to see why people mix them up, but they actually solve very different problems in your application.

AuthN is about identity. Imagine someone trying to check into a hotel. The front desk asks for their ID to confirm they really are who they claim to be. If the ID doesn’t match, they’re politely turned away—no room key, no access. This is AuthN: the process that confirms a user’s identity before anything else happens.

AuthZ is about access and privileges. Once AuthN is successful, the hotel staff checks the reservation details. Maybe the guest has a standard room, or maybe their membership status or special package gives them access to free breakfast, a member lounge, or even a welcome gift. This is AuthZ: where your application determines what resources or actions a user is allowed, based on their role, status, or permissions.

In short:

• AuthN: Are you really who you say you are? If not, you don’t get in.
• AuthZ: Now that we know who you are, what are you allowed to do? Your status or package decides.

These two processes work together to protect identity and control access to resources, ensuring users only get what they’re supposed to—no more, no less.

‍

Common Types

Understanding how AuthN and AuthZ are implemented in real-world applications helps clarify their roles, the tools you might use for each, and the different authentication and authorization types available.

AuthN Types:

• Passwords: Still the most common approach, though not always the most secure.
• Multi-factor authentication (MFA): Adds an extra layer by requiring something you know (like a password) plus something you have (like a code from your phone).
• Biometrics: Uses fingerprints, facial recognition, or voice to confirm identity.
• Single sign-on (SSO): Lets users authenticate once and access multiple systems without logging in again.
• OAuth/OpenID Connect: Protocols that let users log in using credentials from another trusted provider.

AuthZ Types:

• Role-based access control (RBAC): Grants permissions based on a user’s role (admin, editor, viewer, etc.).
• Attribute-based access control (ABAC): Makes decisions based on attributes like department, location, or time of access.
• Relationship-based access Control (ReBAC): Permissions depend on the relationships between users and resources.
• Access control lists (ACLs): Define specific permissions for users or groups on particular resources.
• Custom policies: Many apps use their own logic or rules to determine what users can do, often combining elements of RBAC and ABAC.

Both AuthN and AuthZ are essential for secure access control, and understanding the available types helps you choose the right approach for your application’s needs.

‍

Why It Matters

Getting AuthN and AuthZ right is fundamental for protecting your users and your data. When these two processes work together, only verified users can access your application, and each user is limited to the permissions they are supposed to have.

If AuthN is weak, anyone could pretend to be someone else and gain access. If AuthZ is not set up correctly, even a legitimate user might see sensitive resources they should not, or get blocked from features they actually need. This can lead to data breaches, compliance problems, and a frustrating user experience.

For developers, understanding the difference between AuthN and AuthZ makes it easier to design secure systems, troubleshoot access issues, and scale your application as your user base grows. Strong AuthN and AuthZ are essential for building trust and keeping your application safe.

Enough about hotels—let’s look at how authentication and authorization actually play out in a real software application.

‍

Real-World Use Case: Project Management App

Imagine you’re building a project management tool like Trello or Jira. Here’s how AuthN and AuthZ come into play: 

AuthN: When a user logs in with their email and password (or via Google SSO), the app verifies their identity. This step ensures the user is who they claim to be.

AuthZ: Once authenticated, the app checks what the user is allowed to do—like viewing boards, creating tasks, or managing team members—based on their role.

To visualize this, here’s an Access Matrix Table showing which roles have which permissions:

This table makes it easy to see at a glance which roles can do what, clarifying how authorization decisions are made in your app. For more complex scenarios, like relationship-based access control (ReBAC), you could extend this table or add notes to represent permissions based on user-resource relationships.

Oso’s Perspective

For most teams, authentication is pretty straightforward—just plug into an identity provider or use a standard library and you’re set. Authorization, on the other hand, is where things get complicated. Here are some common pain points developers run into with AuthZ:

• Scattered permission checks: As your app grows, access control logic often ends up spread across controllers, services, and middleware, making it hard to see the big picture or audit who can do what.
• Changing requirements: Business rules evolve. Suddenly, you need to support new roles, special cases, or complex hierarchies, and updating your authorization logic everywhere becomes a headache.
• Lack of consistency: When authorization is handled in multiple places, it’s easy to miss something and accidentally grant (or deny) access where you shouldn’t.
• Testing and debugging: Tracking down why a user does or doesn’t have access to a resource can be tricky when the logic is scattered and hard to follow.

Oso provides Authorization as a service and solves these headaches by giving you a centralized, declarative way to define your authorization policies in code. With Oso, you can:

• Centralize your access control logic so it’s easy to review and update.
• Define roles, permissions, and custom rules in a clear, maintainable way.
• Adapt quickly as your requirements change, without hunting down permission checks scattered throughout your codebase.
• Debug and audit your authorization decisions with confidence, since everything is in one place.
• Test your policies to ensure your authorization logic works as expected before it hits production.

By taking the complexity out of AuthZ, Oso lets you focus on building features, not fighting with permissions.

‍

FAQs/Common Confusions

What’s the difference between AuthN and AuthZ, really?
AuthN (authentication) is about confirming a user’s identity—proving they are who they say they are. AuthZ (authorization) is about determining what actions or resources that user can access, often based on their role or permissions.

Can you have AuthZ without AuthN?
No. Authorization decisions depend on knowing who the user is. Without authentication, there’s no way to know which permissions to check.

Why do people mix up AuthN and AuthZ?
The terms sound similar and both deal with access control, but they solve different problems. AuthN answers “Who are you?” AuthZ answers “What are you allowed to do?”.

Is OAuth authentication or authorization?
OAuth is a way of establishing identity using a token, but it’s often used alongside authorization. Once you have a token that establishes your identity, you can also include data on that token that can be used for authorization. OAuth manages confirming identity and managing the token.

What are some common mistakes with AuthN and AuthZ?

• Treating authentication as enough and forgetting to check authorization.
• Scattering permission checks throughout the codebase, making it hard to audit or update.
• Not updating authorization rules as business requirements change.

Are there best practices for implementing AuthN and AuthZ?
Yes. Use established libraries or providers for authentication, and centralize your authorization logic for easier maintenance and auditing. Always keep them as separate concerns in your architecture.

If you’re ever unsure, just remember: AuthN is “Who are you?” AuthZ is “What can you do?”

‍

Conclusion

Understanding the difference between AuthN and AuthZ is essential for building secure and reliable applications. AuthN (authentication) confirms a user’s identity, while AuthZ (authorization) determines what actions and resources that user can access, often based on their role or other factors. Both are crucial parts of access control and work together to protect your users and your data.

As your application grows, keeping authentication and authorization concerns separate—and using the right tools for each—will help you maintain security, simplify your codebase, and adapt to changing requirements. Whether you’re just starting out or scaling up, investing in strong AuthN and AuthZ practices will pay off in the long run. If you'd like to discuss building those practices into your application, reach out to us on Slack.

‍

Introduction

AWS Cedar is a policy language and enforcement engine developed by Amazon to support fine-grained authorization in applications and services. Built with a focus on access control at scale, Cedar enables developers to define, manage, and evaluate authorization policies across AWS-native environments. It emphasizes policy-as-code, with support for attribute-based access control (ABAC) and resource-based policies, helping teams externalize their authorization logic and improve their security posture.

However, Cedar is still relatively young and tightly coupled to the AWS ecosystem. It currently lacks some of the integrations, ecosystem maturity, and tooling flexibility that more established or open-source alternatives provide.

For teams operating outside AWS, or those looking for more customizable policy models, richer developer tooling, or open standards, there are several compelling alternatives. In this article, we’ll explore five standout options that can help teams implement fine-grained, scalable authorization tailored to their specific stack and workflow.

Why Consider Alternatives to Cedar?

While AWS Cedar offers a focused approach to policy-based authorization within the AWS ecosystem, there are several reasons why teams might consider alternatives.

Pricing Considerations

Cedar itself is free and open-source, but its utility is closely tied to other AWS services like Verified Permissions, which can introduce cost concerns—especially as applications scale or span multiple services. For teams trying to control cloud costs or operate in multi-cloud environments, this tight AWS coupling might become a limiting factor.

Performance Requirements

Cedar is optimized for use within AWS-managed services, but teams building latency-sensitive systems outside of AWS may prefer alternatives that offer local policy evaluation or more direct control over performance tuning.

Implementation Complexity

Cedar offers a powerful policy model, but it comes with a learning curve. Its syntax and mental model may feel unfamiliar to developers who haven’t worked with policy languages before. Teams looking for a more intuitive or developer-friendly experience might gravitate toward tools with simpler APIs or built-in UIs.

Integration Considerations

Cedar is still maturing in terms of ecosystem and integrations. If your system spans a mix of databases, languages, or frameworks—especially outside of AWS—you may run into friction getting everything to work together. Alternative solutions often offer broader SDK support or more flexible integration options.

Vendor Lock-in

Though Cedar is open-source, its design is closely tied to AWS services like Verified Permissions. Teams aiming for long-term portability or hybrid-cloud deployments might prefer vendor-neutral options with open standards and self-hosted capabilities.

Deployment Requirements

Cedar is mainly designed to run in AWS-hosted environments. Organizations with strict data residency, air-gapped infrastructure, or on-prem compliance needs might require solutions that offer greater deployment flexibility or control over the full authorization lifecycle.

Alternatives

Oso

Oso is one of the strongest alternatives to AWS Cedar for teams that want more control and flexibility in how they build authorization. Rather than being tied to a specific cloud ecosystem, Oso externalizes authorization with a cloud-agnostic strategy.

At the core of Oso is Polar, a purpose-built declarative language designed specifically for modeling authorization logic. It supports a range of access control models like RBAC, ABAC, and relationship-based access control, making it adaptable to a wide variety of use cases.

Oso is also built with developers in mind. It offers clean APIs, helpful tooling, and clear workflows that make implementing and managing authorization feel straightforward—even in complex systems.

For teams that don’t want to be locked into a cloud provider or need more flexibility than Cedar currently offers, Oso is a solid option.

Why is Oso better than Cedar?

• Tailored policy language built specifically for application-level authorization
• Strong developer tooling for testing, debugging, and iterating on policies
• Flexible enough to layer on top of existing access control systems

What is Oso’s Pricing?

Oso’s pricing is designed to meet the needs of teams at various stages. The Developer tier is available at no cost, while the Startup tier begins at $149/month. For larger or scaling teams, Oso also offers custom plans that can include migration assistance and personalized onboarding.

Permit.io

Permit.io is a full-featured authorization platform that builds on top of policy engines like OPA (Open Policy Agent) to offer a streamlined, low-code experience. It wraps the power of policy-as-code with developer-friendly APIs and visual tools, allowing teams to manage permissions, roles, and access flows without building that functionality from scratch.

Permit.io uses Rego under the hood but makes it more approachable with an intuitive UI and built-in features like role management, resource mapping, audit logs, and policy versioning. This makes it especially helpful for teams that want strong access control without getting too deep into the underlying policy language or infrastructure.

Where Cedar is tightly coupled with AWS and requires more manual setup, Permit.io offers an elevated experience—ideal for teams looking to move fast and deliver user-facing permission interfaces or admin controls with minimal effort.

Pros:

• Built-in tools for managing roles, policies, and access flows
• Visual editing layer on top of Rego for easier policy creation
• Includes audit logs, versioning, and delegation workflows out of the box
• Requires less manual setup compared to Cedar’s AWS-bound configuration

Cons:

• Learning curve despite the UI layer
• May be overkill for simple applications
• Some features are locked behind paid tiers, which may limit startups on tight budgets
• Less flexibility than fully self-hosted or embedded frameworks

Pricing:

Permit.io provides several pricing options, beginning with a free Community edition. The Startup-tier is priced at $5/month and includes up to 25,000 MAUs and 100 tenants. For larger needs, the Pro tier starts at $25/month and supports up to 50,000 MAUs and 20,000 tenants.

Casbin

Casbin is an open-source authorization library that brings access control directly into your application code. It’s built for flexibility and supports a variety of access control models—including RBAC, ABAC, ReBAC, and even domain-specific variants like multi-tenant RBAC.

Unlike AWS Cedar, which requires connecting to AWS-managed services and writing policies in Cedar's own language, Casbin is designed to be embedded and lightweight. It offers official support across multiple languages—like Go, Java, Node.js, Python, and more—making it easier to integrate into different parts of your stack.

Casbin is especially appealing for teams that want a simple, performant, and self-hosted solution. Its model + policy approach gives developers full control over how rules are structured and enforced, without relying on external dependencies.

Pros:

• Lightweight and embeddable
• Supports a wide range of access control models and policy formats
• Multi-language support makes it suitable for polyglot environments
• Doesn’t require cloud vendor integration or external services

Cons:

• Lacks built-in tools for policy editing, user interfaces, or delegation workflows
• Policy syntax is straightforward but limited for complex use cases
• Requires custom implementation for features like auditing, versioning, or admin consoles

Pricing:

Casbin is an open-source project, so there are no licensing fees. That said, using it in production may still involve operational costs depending on how it’s implemented and maintained.

OpenFGA

OpenFGA is an open-source authorization system inspired by Google’s Zanzibar paper, built specifically for managing fine-grained, relationship-based access control (ReBAC) at scale. It’s designed to handle complex access rules by using a flexible data model and high-performance evaluation engine.

Unlike AWS Cedar, which uses a policy language tied to AWS services, OpenFGA takes a data-first approach, focusing on relationships between users, roles, and resources. It exposes a clean API for defining and querying access relationships, making it well-suited for dynamic environments like multi-tenant SaaS platforms or collaborative apps.

OpenFGA is a strong fit for teams that need highly expressive permission logic and care deeply about performance and scalability. It offers language-agnostic APIs, a strong developer experience, and a growing ecosystem of SDKs and tooling.

Pros:

• Purpose-built for relationship-based access control with a proven model
• High-performance engine designed for scale and low-latency checks
• API-first design that works across most languages or frameworks
• Not tied to a specific cloud vendor or infrastructure

Cons:

• Focused primarily on ReBAC—less ideal for simpler RBAC or ABAC setups
• Requires upfront modeling of relationships, which can add complexity
• Still maturing in terms of documentation, ecosystem, and production tooling

Pricing:

OpenFGA is fully open-source, so there are no licensing fees. However, depending on your setup, there may be notable operational costs involved in running and maintaining it.

SpiceDB

SpiceDB is an open-source database inspired by Google’s Zanzibar paper for managing fine-grained access control at scale. It is designed to be highly performant and expressive, making it ideal for teams building complex authorization systems, such as multi-tenant SaaS applications or collaborative platforms.

SpiceDB adopts a relationship-based access control (ReBAC) model, allowing developers to represent access rules as relationships between users, roles, and resources. Its flexibility and scalability make it a strong alternative to AWS Cedar, particularly for teams that need fine-grained permissions and aren’t tied to the AWS ecosystem. SpiceDB also provides APIs and SDKs for various programming languages, enabling seamless integration into diverse environments.

Pros:

• Built for relationship-based access control with a focus on scalability
• High-performance engine for low-latency authorization checks
• Flexible APIs and SDKs for integration across diverse environments
• Open-source and vendor-neutral, providing full control over deployment

Cons:

• Requires upfront modeling of relationships, which can be complex for simpler use cases
• May involve some operational overhead for teams managing self-hosted deployments
• Still evolving in terms of ecosystem and documentation compared to more mature tools

Pricing:

SpiceDB is free and open-source, but operational costs may arise depending on your deployment strategy. For teams needing managed solutions, commercial offerings like Authzed provide hosted SpiceDB instances with additional support and features.

SpiceDB is a compelling choice for teams requiring a high-performance, relationship-based access control system that scales efficiently and operates independently of any specific cloud provider.

OPAL

OPAL (Open Policy Administration Layer) is an open-source project that extends policy engines like OPA by making them real-time and dynamic. While OPA handles policy evaluation, OPAL is focused on policy distribution—making sure your authorization layer always has the freshest data when making decisions. OPAL is not an alternative to a policy engine, but is a worthy inclusion to this list, because leveraging OPA + OPAL can be a suitable alternative to products like Permit.io.

Where AWS Cedar focuses on static, declarative policies that live inside AWS’s infrastructure, OPAL helps bridge the gap between your policies and the external data sources that drive them. It syncs policy data from databases, APIs, and event streams, so that OPA can evaluate requests with real-time context—such as user roles, resource ownership, or permissions tied to changing business logic.

OPAL is ideal for teams already using OPA or building real-time systems where stale data could cause incorrect authorization decisions. It’s a strong choice for engineering teams who want to stay in control of their stack, and need dynamic policy loading without relying on a managed platform.

Pros:

• Enables real-time, dynamic policy updates
• Keeps your policy engine in sync with external data sources
• Works seamlessly with OPA and other tools in the policy-as-code ecosystem
• Decoupled decision-making from data propagation

Cons:

• Requires more setup and orchestration compared to managed platforms
• No built-in policy authoring or user interface—relies entirely on OPA and custom tooling
• Best suited for teams already familiar with policy-as-code architectures

Pricing:

Opal itself doesn't have a cost, but integrating it into your environment and potentially using related services from vendors might incur costs

Conclusion

AWS Cedar is a capable option for teams fully committed to the AWS ecosystem, but it’s not always the best fit for every use case. Its limited flexibility and cloud-specific design can become constraints for teams needing broader integration or more hands-on control.

If your architecture, pace, or authorization complexity demands more than what Cedar offers, there are solid alternatives worth exploring. The best solution is the one that aligns with your stack, scales with your product, and fits how your team works.

‍

‍

‍

Introduction

SpiceDB has become a popular choice for teams building fine-grained access control, especially when dealing with complex permission models and user-resource relationships. Built around the ideas in Google’s Zanzibar paper, it gives developers a scalable way to express relationship-based access logic, with performance and consistency controls that are production-ready.

That said, SpiceDB isn’t always the right fit for every team or every project. Maybe you’re working in a framework where embedding authorization logic directly in code feels more natural. Maybe you’d rather use a simpler policy engine without managing a dedicated datastore. Or maybe you’re just curious about how other tools approach the same challenge in a different way.

Whatever the case, it’s worth knowing what else is out there. In this post, we’ll walk through five strong alternatives to SpiceDB, explore what makes each one different, and help you find the right tool for your approach to authorization.

Why Choose Alternatives to SpiceDB?

SpiceDB offers a robust solution for complex authorization, especially when relationship-based access control (ReBAC) is essential. But depending on your team’s architecture, skill set, and needs, it might not be the most efficient or intuitive choice. Here are several reasons why teams consider other options:

Complex Setup and Operational Overhead

SpiceDB is powerful, but it isn't lightweight. Running it typically means managing a custom schema, syncing relationships into a dedicated datastore, and integrating it as a separate microservice. For smaller teams or simpler applications, that operational cost may outweigh the benefits.

Steep Learning Curve

The Zanzibar-inspired model can be difficult to grasp if you're not already familiar with graph-based permission systems. For teams used to writing straightforward access rules or policies in code, SpiceDB can feel unintuitive and harder to debug.

Doesn’t Fit All Authorization Models

SpiceDB excels at ReBAC, but not every system needs relationship graphs. If your app relies more on attribute-based logic (ABAC), time-based permissions, or contextual business rules, other engines may offer better support with less workarounds.

Lack of Built-In Policy Language

Unlike tools like Oso or Cedar, SpiceDB doesn't provide a policy language for expressing custom logic. While you can define complex permissions through relationships, you can’t easily write conditional rules like “only allow this if the user is the owner and the document is in draft.”

Limited Out-of-the-Box Developer Experience

SpiceDB is infrastructure-first. It offers strong APIs and performance, but lacks built-in tooling like UI dashboards, visual editors, or audit trails. If your team is building a product that's meant to be administered by business users, you may need to build those layers yourself—or opt for a tool like Permit.io that includes them.

Alternatives

Oso

Oso is a developer-first authorization framework that lets you define access control logic directly in your application using a declarative policy language called Polar.  Your authorization logic is separated from your business logic, making authorization easier to reason about, debug, and test as part of your normal development flow.

Oso is designed to handle a wide variety of access control patterns, from simple role-based rules to more complex setups like attribute-based (ABAC) or relationship-based access control (ReBAC). It also includes thoughtful developer tooling like policy unit testing and decision tracing. While it doesn’t provide a built-in relationship graph like SpiceDB, Oso gives you the flexibility to model these patterns yourself.

Why Oso is a strong alternative to SpiceDB

• SpiceDB is more focused around ReBAC while Polar allows Oso to be more open-ended
  • Lack of policy language is inherently more limiting
• You have to set-up a dedicated data store and a product like Oso may have an easier DX
  • Granted, that also involves learning Polar.

You've pretty much nailed it. I think it's mostly about preference and what someone finds more intuitive. Polar really is Oso's main distinguishing factor. It's the most general-purpose approach to authorization that I've seen in any of these services. It lets you model just about any authorization logic pretty naturally. And in the case of spicedb, you also have the data store to manage. AuthZed does provide a managed spicedb as well, but then you lose all the open source benefit. And spicedb does also have a schema language to learn - it's just more limited since it's so focused on relations.

Why Oso is better than SpiceDB:

• Supports RBAC, ABAC, and ReBAC patterns out of the box with its open-ended language
• Uses Polar, a readable and expressive policy language
• Strong developer tooling: policy testing and decision tracing

What is Oso’s Pricing?

Oso offers pricing tiers to support teams at different stages. The Developer-tier is completely free, while the Startup-tier starts at $149/month. For growing or larger companies, Oso provides custom pricing, which can include migration support and tailored onboarding services.

Cedar by AWS

Cedar is an open-source, purpose-built policy language developed by AWS to power fine-grained authorization in services like Amazon Verified Permissions and AWS Verified Access. It’s designed to be fast, expressive, and secure by default, and focuses on enabling declarative, attribute-based access control (ABAC) and role-based models in cloud-native applications.

Cedar policies are written in a simple JSON-like syntax, and the language is built to be auditable and analyzable — ideal for environments that prioritize clarity and security in access control. Amazon Verified Permissions (which runs on Cedar) allows you to store and evaluate policies at scale as part of a managed service, but you can also run Cedar standalone in your own stack using the open-source library.

For teams already using AWS infrastructure, Cedar is especially appealing. It’s tightly integrated with AWS services and designed to work seamlessly in cloud-native environments. If you’re building serverless apps or microservices in AWS, Cedar offers a native way to implement fine-grained authorization without introducing external complexity.

Pros:

• Designed specifically for fine-grained authorization on AWS
• Strong ABAC support, with some support for RBAC patterns
• Backed by AWS — used in production services like Verified Permissions
• Built-in tooling for static analysis, auditing, and validation

Cons:

• Doesn’t support ReBAC or relationship graph modeling natively
• Best suited for attribute-based models — less flexibility for custom logic or embedded use
• Tightly coupled with AWS — not as appealing if you’re not in the AWS ecosystem
• Requires learning a new syntax and integrating an evaluation engine into your app

Pricing:

While Cedar itself has no standalone pricing, it's used within services like Amazon Verified Permissions, which charges based on the number of authorization requests. There are no upfront costs or minimum fees — you only pay for what you use.

OpenFGA

OpenFGA is an open-source authorization system designed for **fine-grained access control.** Like SpiceDB, it's heavily inspired by Google Zanzibar . Originally developed by the team at Auth0 (now part of Okta), OpenFGA provides a simple and scalable way to model and evaluate complex permission relationships across users, roles, and resources.

It uses a declarative modeling language that allows you to define types, relationships, and authorization rules. OpenFGA is stateless and built to scale horizontally, making it a strong choice for large, distributed systems. You can self-host it or use the hosted version via Auth0 Fine-Grained Authorization.

OpenFGA is arguably the closest architectural alternative to SpiceDB on this list. Both tools are inspired by Google Zanzibar and both are built around relationship-based access control (ReBAC), schema definitions, and high-performance permission checks. The key difference lies in execution: OpenFGA aims to be more approachable, easier to integrate, and slightly more opinionated in how you model access logic.

Pros:

• Built specifically for fine-grained, relationship-based access control
• Stateless and horizontally scalable
• Self-hosted or available as a managed service (Auth0 FGA)
• Good fit for microservices and multi-tenant architectures

Cons:

• Still relatively young — not as battle-tested as SpiceDB in large deployments
• Doesn’t offer as much flexibility around consistency models or datastore options
• Requires learning a specific schema language and model

Pricing:

OpenFGA is open-source meaning there are no licensing costs, however, there may be significant operational costs.

Permit.io

Permit.io is a full-featured authorization platform that builds on top of policy engines like OPA (Open Policy Agent) to deliver a low-code, developer-friendly experience. It combines the flexibility of policy-as-code with visual tools and APIs that make it easy to manage roles, permissions, and access flows — all without needing to build those layers yourself.

At its core, Permit.io lets you define policies using OPA's Rego language but wraps that in a more approachable interface. It includes built-in tools for role management, user-to-resource mapping, policy versioning, audit logs, and more — making it especially useful for teams who need robust authorization.

If your team wants to move fast without getting deep into graph modeling or managing your own infrastructure, Permit.io offers a more elevated experience. It's ideal for SaaS teams who need multi-tenant access control, role delegation, or admin-facing permission interfaces — all of which would require additional development effort if you were using SpiceDB directly.

Pros:

• Full-stack authorization platform with UI, API, and SDKs
• Visual role and permission editors — beneficial for business users
• Built-in audit logs, versioning, and environment controls
• Supports RBAC, ABAC, and custom policies using OPA/Rego

Cons:

• Less flexible than building your own Rego-based or ReBAC model from scratch
• Built on OPA, which can feel complex if writing advanced policies
• May not suit highly custom or deeply embedded use cases
• Vendor-managed — limited control compared to fully open-source tools

Pricing:

Permit.io offers multiple pricing tiers, starting with a free Community edition. The Startup-tier begins at $5/month for up to 25,000 MAUs and 100 tenants, while the Pro tier starts at $25/month and supports up to 50,000 MAUs and 20,000 tenants.

Cerbos

Cerbos is an open-source authorization engine built for modern applications that want to decouple access control from application logic. Instead of embedding authorization rules directly in your code or relying on a relationship graph like SpiceDB, Cerbos lets you define policies in YAML and evaluate them via a lightweight service or SDK.

Cerbos focuses on attribute-based access control (ABAC) and role-based access control (RBAC) out of the box. It’s designed to be simple to adopt, easy to scale, and highly portable across environments — whether you’re building a monolith, microservices, or serverless functions.

With Cerbos, you don’t need to manage a specialized datastore or relationship graph. You define your policies declaratively, then pass user and resource attributes at runtime to get a decision back. This makes Cerbos easy to integrate, especially when you want to keep your data models and access logic loosely coupled.

Pros:

• Policies written in standard YAML
• Strong support for RBAC and ABAC out of the box
• Language-agnostic — works with any backend via API or SDK
• Includes useful tooling: test framework, policy playground, and CI integrations

Cons:

• Doesn’t support ReBAC or relationship modeling
• More focused on binary “allow/deny” decisions
• Complex conditional logic can get verbose in YAML

Pricing:

Cerbos offers several plans, starting with a free, open-source version. Cerbos Hub starts at $0/month for up to 100 monthly active principals, while the Growth-tier begins at $25/month, with pricing based on active usage.

Conclusion

Authorization is a critical part of any application — it protects your data, controls access, and ensures the right users can do the right things at the right time. SpiceDB is a powerful choice for teams needing sophisticated, relationship-based access control, and it has proven itself in demanding production environments.

That said, no single tool is perfect for every situation. SpiceDB’s complexity and operational requirements might not be the best fit for every team or project. Exploring alternatives can uncover solutions that better match your app’s scale, your team’s workflow, and your architecture.

‍

Authorization can quietly become a mess if it's not handled the right way from the start. That's where a great authorization tool comes into play. Cerbos is one such authorization product.  However, depending on what you're building and how your team works, Cerbos might not check every box.

Whether you're looking for something that fits more naturally into a specific tech stack, offers a more visual policy experience, or handles both identity and authorization in one place, it's worth knowing what else is out there. In this post, we'll walk through four solid alternatives to Cerbos, break down what makes each one unique, and help you figure out which might be the right fit for your project.

Why Choose Alternatives to Cerbos

Cerbos is not always the best fit for everyone. Some teams may want a solution that's easier to set up or manage, especially if DevOps resources are limited. Others might need features Cerbos doesn't prioritize, such as built-in user management, real-time policy updates, native support for multi-tenant applications, or advanced permission models like ABAC or ReBAC.

So what makes a strong alternative to Cerbos? That really depends on your needs, but generally, you'll want something that strikes the right balance between flexibility, ease of use, and long-term maintainability. For some teams, that means picking a tool with a lower learning curve or a more visual policy editor. For others, it might mean tighter integration with the rest of their stack  or an opinionated approach that helps speed up implementation. Whatever the case, it's worth exploring the options before committing to a single approach. Let's jump into four solid alternatives to Cerbos and break down what makes each one worth a look.

Oso

Oso is a developer-first authorization framework that brings powerful access control into your application using a declarative policy language called Polar. Unlike Cerbos, which externalizes policy logic into a separate engine, Oso is designed to be embedded directly into your app, giving you tighter integration and more immediate control over how permissions are evaluated.

If you're looking for something more tightly coupled with your application code, Oso is a great alternative. It supports a wide range of access patterns, including role-based access control (RBAC), attribute-based access control (ABAC), and relationship-based access control (ReBAC). This makes it especially useful for applications with complex or evolving permission needs. Oso also comes with helpful tooling like policy testing, decision tracing, and a REPL for debugging logic. All of these features make your developer experience smoother than a more barebones policy engine like Cerbos.

In my opinion, if you're a company that values having authorization logic close to your application code and wants powerful debugging capabilities, Oso should be at the top of your list.

Why Oso is better than Cerbos:

• Embedded in the app, making integration straightforward
• Supports RBAC, ABAC, and ReBAC out of the box
• Developer-focused tools: REPL, policy testing, decision tracing
• Flexible enough to handle complex business rules

What is Oso's Pricing?

Oso's pricing is designed to support a variety of different businesses. The developer-tier is totally free. The first paid-tier is a startup-tier at $149/mo. If you're larger or growing quickly Oso will work with you to determine custom pricing that can include migration services if needed.

Auth0

Auth0, now part of Okta, is a developer-friendly identity platform that handles things like authentication, user management, and access control. It's known for being easy to integrate, making it a decent solution for teams who want to offload identity and authorization complexity.

While Auth0 isn't the best for authorization, it's good if you're looking for the convenience of a managed solution that bundles both authentication and authorization in one place.

Do note that Auth0 doesn't offer the same kind of policy-as-code flexibility or self-hosting option that Cerbos does. However, for teams who want to move fast, stay secure, and integrate with minimal friction, Auth0 provides a lot of value out of the box.

Pros:

• All-in-one identity and access management solution
• Fast to integrate with great developer tooling and docs
• Hosted and scalable with high availability
• Marketplace with prebuilt integrations for social login, SSO, etc.

Cons:

• Custom authorization logic can feel limited or require workarounds
• Policies are managed through a web interface or scripts, not ideal for code-first workflows
• Vendor lock-in and less transparency than open-source alternatives
• It can get pricey at scale or with advanced features

Pricing:

Auth0 offers a free tier as well as premium tiers. The first premium tier goes for $35/month for up to 500 users. The next tier offered is the professionals tier for up to 1,000 MAUs priced at $240/month. Lastly, they offer an enterprise tier, which comes with custom pricing based on a consultation.

Permit.io

Permit.io is another authorization platform built to bring fine-grained access control to your app. It sits on top of open-source policy engines like  OPA, and gives you a management layer with a visual UI, real-time updates, audit logs, and integrations.

Permit.io is similar to Cerbos, but adds tools for managing roles, tenants, and permissions across different environments. If Cerbos feels too hands-on or DevOps-heavy, Permit.io might be the smoother path.

It can be a better option than Cerbos for multi-tenant SaaS apps or any product where permissions change frequently and need to be updated live without redeploying.

If you're building a multi-tenant application and need both developer-friendly policy management and business-user-friendly interfaces, Permit.io could be a good consideration.

Pros:

• Built-in support for multi-tenancy, dynamic roles, and real-time updates
• Based on open standards and integrates with OPA under the hood
• Good balance of control for devs and visibility for non-technical teams
• Combines policy-as-code with a no-code UI for business users

Cons:

• Still a relatively young platform compared to legacy IAM providers
• More layers of abstraction can sometimes make debugging harder
• May be overkill for simple apps or small teams with basic access needs
• Less community adoption compared to tools like Cerbos or Oso

Pricing:

Permit.io offers a few different tiers, with the cheapest being the community edition, which is free. The next tier available is the startup tier, starting at $5/month for up to 25,000 MAUs and 100 tenants. They also offer a pro tier for up to 50,000 MAUs and 20,000 tenants beginning at $25/month.

Keycloak

Keycloak is an open-source access management solution that includes a built-in authorization engine alongside its authentication and user federation features. It's often thought of as an identity platform, but it  also includes authorization functionality . This is mostly used by Keycloak customers who need both identity and fine-grained access control tied to resources, roles, and scopes. The authorization features include role-based access control (RBAC), resource-based permissions, scopes, policies, and permission tickets. These are configurable through a built-in UI or admin API.

Unlike Cerbos, which is policy-as-code focused, Keycloak's authorization logic is more tightly integrated into its platform. That said, it's powerful and flexible enough to model real-world access patterns, including multi-tenant use cases and complex business rules. Keycloak isn't a bad choice if you prefer a declarative, centralized model over embedding logic in code.

If you're a company that needs both identity and authorization in one self-hosted package and doesn't mind the complexity that comes with it, Keycloak could save you from managing multiple systems.

Pros:

• Resource-based authorization with roles, scopes, and policies
• Fine-grained access control is baked into the platform
• Centralized UI and APIs for managing permissions
• Fully self-hosted and customizable for on-prem needs

Cons:

• Authorization is tightly coupled to Keycloak's identity stack
• No policy-as-code model like Cerbos or Oso
• It can be overkill if you only need an authorization engine
• Learning curve with the admin UI and authorization mode

Pricing:

For organizations building customer-facing applications, Keycloak can be economical in price since it doesn't have per-user licensing fees.

Comparison Table

Feature / ToolCerbosOso CloudAuth0Permit.ioKeycloakTypePolicy-as-code engineEmbedded auth frameworkManaged IAM w/ auth featuresManaged + policy-as-codeSelf-hosted auth platformHostingSelf-hosted / DockerEmbedded in app codeFully managedCloud + self-hostedSelf-hosted (on-prem or cloud)Policy ModelYAML-based, decoupledPolar (DSL), inline in appRoles + rules + actionsUI + YAML (OPA under the hood)Role, resource, scope-basedAccess PatternsRBAC, ABAC, multi-tenantRBAC, ABAC, ReBACRBAC + custom token logicRBAC, ABAC, multi-tenantRBAC, resource policiesPolicy-as-CodeYesPartial (via DSL)NoYesNoAdmin UINone (code only)NoneYesYesYesReal-Time UpdatesManual redeployCode-level change requiredYesYesYes (via admin UI/API)Best ForDev teams wanting full controlEmbedded control in codeFast identity/auth comboScalable apps needing hybridComplex, self-hosted systems

Conclusion

Authorization isn't just a backend task or a security checkbox. It's a core part of how your product works and how users experience it. While Cerbos offers a clean, developer-centric way to manage access control with policy-as-code, it's not a one-size-fits-all solution.

Before you make a decision on which authorization tool to use, it could be worth your time to investigate other authorization products, such as Oso, which can offer a better developer experience.

Role-Based Access Control (RBAC) is an authorization approach that organizes access permissions into roles that can be assigned to users. Intuitively, RBAC seems like a simple system. Our responsibilities within an organization naturally confer different levels of access and corresponding security, so an RBAC should hypothetically be easy to set-up. In theory, a person's position maps to a configured role that grants them the permissions they need.

However, this rosy ideal rarely materializes. In the wild, I've seen organizations implement RBAC with overlapping permissions, bloated roles, or incomplete systems that expose security vulnerabilities and cause maintenance nightmares.

The difference between RBAC success and failure often comes down to design principles and ongoing governance rather than the technology itself. Organizations that implement sustainable RBAC systems follow specific patterns for role design, permission granularity, and system maintenance that prevent the common pitfalls.

In this article, I want to share these best practices that successful organizations adopt to design RBAC systems that actually work in practice, not just in theory.

Adopt the Principle of Least Privilege

The principle of least privilege dictates that users should only be granted the minimum permissions necessary to perform their tasks.

When a new user enters a system, it's critical to understand what the user truly needs to accomplish their tasks. Over-permissioning is a common trap.

For example, I once encountered an organization that automatically granted new marketing team members full administrative access to their customer relationship management (CRM) system, simply because "that's what the previous person had" - a classic case of over-permissioning for convenience. It would have been enough to grant read access to customer data and write access to campaign records.

When increasing someone's access, think carefully about how it impacts others with similar roles, or if there are permissions being granted that are unnecessary for the tasks at hand.

Separate users, roles, and permissions

RBAC doesn't mean users should be locked into a single role. Instead, treat permissions as atomic units, roles as bundles of permissions, and users as having one or more roles. This allows greater flexibility and avoids bloated role definitions.

For example, imagine a support engineer who also occasionally helps with onboarding new customers. Rather than creating a monolithic "Support-Plus-Onboarding" role, assign them both the "Support Agent" role (with permissions for ticket management and customer communication) and the "Onboarding Specialist" role (with permissions for account setup and initial configuration). That way, you can later remove the onboarding role as that process becomes more automated.

Separating the concepts of users, roles, and permissions prevents role sprawl, making it easier to manage permissions as responsibilities change.

Design roles around business functions and change rate

Often, I've seen organizations design roles to match job titles. While this works initially, it's brittle to organizational changes. What happens when someone covers another person's job for a week? Or a new employee wearing multiple hats joins the team? It's easy to break the principle of least privilege by temporarily granting such cases an entire role when they only need some of its permissions.

Instead, design roles around stable business functions that persist even when job titles change or new features are added. Instead of "Sales Manager," try "Customer Data Management." Instead of "IT Admin," try "System Configuration.” Describing roles as business functions means they can remain consistent even as organizational structure shifts.

A broader principle is to adjust granularity of roles to the rate of change of your business. A fast-growing startup benefits from atomic roles like "Invoice Processing" and "Customer Support" that can be quickly reassigned as responsibilities shift. A stable enterprise might use broader roles like "Finance Operations" without constant maintenance overhead.

Roles won’t always be perfect, so use the 80/20 rule as a design test: if 80% of users with a role need 80% of its permissions, your abstraction level is probably right.

Plan for role exceptions, but minimize them

No matter how well designed an RBAC implementation is, I’ve always seen them encounter edge cases. Rather than forcing awkward workarounds, my advice is to plan for controlled exceptions while keeping them minimal.

Before creating one-off roles, I’d consider if the need could become a new standard role that applies to other users. This avoids similar exceptions in the future and reduces tracking overhead.

When exceptions are truly necessary, document them with proper approvals and add expiration times if your system supports it. For example, a support agent needing temporary billing access for a major customer issue should receive a time-limited "Billing Support" role rather than permanent customization.

Finally, schedule periodic reviews to consolidate custom roles back into standard ones as organizational needs evolve. Every custom role is security debt that should be paid down when possible.

Automate to reduce human error

Human error is a major cause of security vulnerabilities. Wherever possible, automate RBAC processes to reduce manual mistakes and operational overhead.

There are many ways to automate RBAC processes. Some examples I’ve seen:

• Auto-provision roles based on job titles or departments from HR systems so new hires automatically receive appropriate baseline permissions without manual setup delays.
• Automatically revoke all access when someone is marked as terminated in the HR system
• Automate access reviews by sending managers quarterly emails that list their team's current roles and permissions, requiring them to confirm or request changes within a deadline. This ensures regular validation without the administrative burden of coordinating manual reviews.

That being said, limit automation for high-risk roles like admin access. Manual approval in cases like these help maintain proper oversight.

Design for scoped roles, not global permissions

One of the biggest mistakes I’ve seen in implementing RBAC is to default to global roles. But "Admin" in marketing shouldn’t mean "Admin" in engineering! Real organizations need scoped roles, not global ones, where the same person has different access levels in different contexts.

To implement this concept, design for User → Role → Scope relationships from the start. This often requires more sophisticated RBAC systems that support contextual roles, not just basic role assignment. For example, a department head may need admin rights in their department, but zero access for others.

Scoped roles reduce blast radius when accounts are compromised and enforce least privilege at scale, providing the right access in the right context while maintaining security boundaries.

Add safeguards for risky permissions

Not all permissions are created equal. Gate different risk levels with appropriate safeguards: require MFA for sensitive data access, implement approval workflows for destructive actions, and add audit notifications for administrative functions. This layered approach prevents both accidental damage and malicious insider activity.

Ensure clear escalation paths when approvals are needed urgently and maintain detailed audit trails for all high-risk operations. For example, production deletions should require manager approval, bulk customer data exports need MFA verification, and password resets for other users should trigger security notifications.

The goal is proportional security. Higher risk operations should get stronger controls without slowing down everyday work.

Build or buy an RBAC system? Default to buy

This is a classic debate I’ve seen play out many times. Companies want to implement their RBAC system internally, thinking “Our requirements are simple, we want full control, existing solutions are overkill and we can build it faster.”

But in my experience, this almost always leads to easily predictable problems. Custom RBAC quickly becomes complex as requirements grow, it lacks security expertise, and creates ongoing maintenance that most teams aren't equipped for.

Buying authorization software that supports RBAC offers benefits that keep paying dividends: ongoing security updates, compliance certifications (SOC2, FedRAMP), integration ecosystems, and proven design patterns. There are few exceptions to this rule - free yourself to focus on your core business instead of reinventing security infrastructure.

Maintain and evolve your RBAC system

RBAC systems reflect the organization they operate in, so when organizations change, so do their RBAC systems. In my experience, it’s best to expect and prepare for change gradually rather than doing big overhauls infrequently.

Establish regular maintenance processes from the start:

• Implement access recertification where managers periodically attest to their team's access
• Schedule role audits to consolidate and clean up permissions
• Create change management procedures for organizational shifts
• Consider implementing proper UI/UX for day-to-day operations.
• Build monitoring into your RBAC operations by tracking role usage, identifying permission drift, and setting up alerts for unusual patterns.

Without maintenance, even well-designed RBAC systems decay into security liabilities. Your RBAC system should evolve with your company, or else it may eventually constrain it.

Prepare your incident response playbook

Security incidents are a fact of life, but preparation can make all the difference when they happen. I’ve been in rooms with playbooks and rooms without them—trust me, they make all the difference.

RBAC security incidents have unique characteristics: compromised privileged accounts, insider threats abusing legitimate access, and privilege escalation attacks where attackers use existing permissions maliciously. I’ve seen the following preparations work well for these scenarios.

• Maintaining comprehensive audit trails. ****Log permission grants, revocations, role changes, and access attempts with timestamps, user details, and justifications. These are essential for forensic investigation during incidents and required for compliance frameworks like SOX, GDPR, and HIPAA.
• Establishing emergency access revocation procedures to quickly disable compromised accounts
• Creating lockout triggers for suspicious patterns like unusual locations or bulk downloads
• Enabling emergency admin access when RBAC systems fail or administrators are unavailable.

Once the playbook is created, be sure to practice it with your team and update it as needed. I’ve been in situations where the the playbook was useless because it was only tested during a live security incident.

Effective incident response planning ensures you can respond quickly and methodically when RBAC-related security events occur - don’t skip it!

Next steps for implementation

Whether you're starting from scratch or improving an RBAC existing system, I believe it’s best to focus on the fundamentals: least privilege, clear role boundaries, and automation where possible. Remember that RBAC is an ongoing operational discipline, not a one-time setup.

If you're looking for a proven solution that implements RBAC best practices out of the box, consider using Oso. It handles the complexity of implementing these patterns correctly, so you can focus on your core business instead of rebuilding authorization infrastructure.

‍

Role-Based Access Control (RBAC) is one of the most widely adopted authorization patterns in modern web applications, providing a structured approach to managing who can access what resources and perform which actions.

Unlike simpler permission models that assign rights directly to individual users, RBAC introduces roles, or groupings of permissions for particular functions. This creates a more natural fit and proves far more scalable for most organizations as they grow.

While RBAC offers clear benefits, I've seen many organizations struggle with role design decisions, technical integration complexities, and migrating from existing permission systems. Without a structured approach, RBAC implementations often become overly complex or fail to meet security requirements. In this guide, we'll walk you through a proven framework for implementing RBAC effectively.

1. Planning & Assessment

I always begin by conducting a comprehensive audit of existing permissions and access patterns. This reveals not just what permissions exist on paper, but how they're actually being used in practice. You'll often discover shadow permissions, unused access rights, and users who've accumulated privileges over time that no longer align with their current responsibilities.

Next, it’s time to design roles. The key insight to keep in mind is that roles should reflect business functions, not job titles or features. Instead of "Sales Manager," use "Customer Data Management." Instead of "IT Admin," use "System Configuration.” Describing roles as functions means they remain consistent even as job titles and organizational structure shifts.

Next, define permissions. Permissions should be atomic, meaning that they map 1-1 to a particular kind of access or action. Roles can have as many permissions as needed, so don’t be afraid to limit the scope of a permission.

When assigning permissions to roles, remember to apply the principle of least privilege, which states that users should only be granted the minimum permissions necessary to perform their tasks. I once encountered an organization that automatically granted new marketing team members full administrative access to their customer relationship management (CRM) system, simply because "that's what the previous person had" - a classic case of over-permissioning for convenience.

The least privilege principle also means that when individuals are over-permissioned, the right thing to do is to remove those extra permissions. This is no fault of the individual, but it’s easy to feel slighted when one’s permissions are reduced. Get ahead of this inevitability by preparing a comms strategy which prepares folks for permission reduction. Remind them that this is inevitable, and is a reflection of the system’s growing maturity rather than an individual’s performance.

Once you have your roles and permissions defined, map current users to these proposed roles. This exercise often reveals gaps in your role design and helps identify users who will need special handling during migration.

Finally, develop a clear migration strategy. Plan to run both systems in parallel during the transition, start with a pilot group for validation, and create fallback mechanisms to quickly revert if issues arise. For users with unique permission sets that don't fit any role, use temporary individual permissions rather than creating one-off roles. This planning phase typically takes longer than expected, but the time invested here prevents painful rework later.

2. Build vs Buy? Default to Buy

Build or buy is a classic debate I've seen play out countless times. For this situation, my advice is simple: default to buying an authorization platform.

I've watched too many teams say "our requirements are straightforward, let’s build it,” six months go by, and they find themselves struggling with complex edge cases, security vulnerabilities, and maintenance overhead that they never anticipated.

Purpose-built authorization platforms bring immediate value through ongoing security updates and battle-tested design patterns learned from thousands of implementations. Nine times out of ten, it’ll save you time and headache.

The rare exceptions where building makes sense are when you have extreme performance requirements or unusually simple integration needs. In most cases, you'll get better results faster by focusing your engineering talent on your core business rather than reinventing security infrastructure that’s already been perfected.

3. Implementation & Integration

Once you've chosen your authorization platform, the real work begins with integrating RBAC checks throughout your application. You'll need checks not just at the API level, but also in your user interface to hide features users shouldn't access.

So, I start by identifying every API endpoint, screen, and component that needs access control. This often is more comprehensive than teams initially realize.

Building automation for handling new users comes next. This is critical - manual role assignments are error-prone and don't scale. Set up automated provisioning tied to your HR systems or identity provider so that when someone joins the sales team, they’re automatically granted the appropriate roles without IT intervention.

Finally, testing. This is where I’ve seen many implementations fall short, especially in handling edge cases gracefully. Systems can break when users have multiple roles with conflicting permissions, or when role inheritance creates unexpected access patterns. Testing should also cover security, including attempted privilege escalation and other boundary conditions. The goal of testing is to catch authorization failures before they reach production.

4. Deployment & Monitoring

Next, it’s time to roll out your RBAC system to production. Remember that this change affects every single person in the organization, so be sure to reinforce your comms strategy through multiple mediums (email, Slack, etc) for redundancy.

Your comms strategy should also prepare your organization for the growing pains that come with such a transition. There are almost certainly edge cases you missed that will bottleneck work. Accelerating approval processes during the transition and communicating with empathy upfront (”We know we’re going to miss some things, but we’ll do our best to address them as quickly as we can…”) will allow most people to give you the benefit of the doubt.

The deployment itself requires careful orchestration and multiple safety nets. I always deploy with robust fallback mechanisms that can quickly revert users to their previous permissions if critical issues emerge. Start with a phased rollout by deploying to a small user group first, then gradually expand as confidence builds.

Once your system is live, monitoring becomes your early warning system. Set up comprehensive logging of access patterns and policy violations, and configure alerting for unauthorized access attempts. I've found that many security incidents reveal themselves through subtle changes in normal access patterns, so baseline your users' typical behavior early.

Also, automate periodic access reviews by scheduling quarterly emails to managers, asking them to verify their team's role assignments. Business requirements evolve, users change responsibilities, new features launch, and compliance requirements shift. Automated reviews help you catch role drift before it becomes a security risk and ensure your RBAC implementation continues serving your organization's needs effectively.

Finally, always plan for incidents. This might mean temporary elevated permissions for specific users or a break-glass procedure that logs all actions for later review. Documenting emergency access procedures allows you to maintain business continuity without compromising security.

5. Common Pitfalls & Design Patterns

The first and most common failure I see is "admin creep" - the gradual expansion of administrative privileges as users request extra permissions to solve immediate problems. If left unchecked, this natural tendency erodes the role structure you took so much care in developing. Combat this by establishing clear approval processes for role changes, implementing expiration dates for elevated permissions, and regularly auditing who has elevated privileges.

Scope creep for roles is equally dangerous. Teams start with simple roles, then add exceptions and special cases until they're essentially back to individual permission management. I've seen organizations with hundreds of micro-roles that defeat the entire purpose of RBAC. When you find yourself creating roles for single users or adding extensive conditional logic, step back and reconsider your role structure.

Finally, role hierarchies - they can be valuable, but more often than not, I’ve seen them increase complexity and maintenance. If this is unavoidable, start with flat role structures and only add inheritance when you have a clear, time-tested business case. Keeping the hierarchy shallow (2-3 levels max) work well for clear permission escalation patterns like "Read-Only User" → "Standard User" → "Admin."

Moving Beyond RBAC

RBAC provides a solid foundation for most organizations' authorization needs, offering role-based permissions that scale well and align with business functions. However, it struggles with complex relationship-based access patterns, like "users can only edit documents they created" or "managers can approve expenses for their direct reports."

When you encounter these relationship-dependent requirements, consider alternate models such as relationship-based access control (ReBAC) or attribute-based access control (ABAC).

The truth is, no access model is perfect. Thankfully, creating custom access models of all types (RBAC, ReBAC, ABAC) is made easy by platforms like Oso. Oso handles the complexity of implementing these access models with these best practices in mind, freeing you up to focus on your core business rather than rebuilding authorization infrastructure.

‍

‍

‍

Introduction

Permit.io is an “Authorization as a Service” product that offers policy creation and enforcement tooling. Permit.io utilizes a policy-as-code approach based on Open Policy Agent (OPA) and OPAL, in an effort to reduce the amount of custom code that teams need to write. The platform supports multiple authorization models including RBAC, ABAC, and ReBAC to accommodate various use cases.

The platform includes visual policy editing tools and user interfaces designed for cross-functional team accessibility. Organizations may find Permit.io suitable when seeking quick authorization implementation.

For startups and mid-sized companies evaluating authorization solutions, it's valuable to explore all available options to ensure the best fit for specific technical requirements and organizational needs.

‍

‍

‍

Why Choose Alternatives to Permit.io?

While evaluating alternatives to Permit.io, there are several factors that you should consider:

Pricing Considerations

Permit.io’s pricing is based on Monthly Active Users (MAUs) which can get expensive as your user base grows. The jump from the free tier (1,000 MAUs) to paid plans can be too steep for early stage startups with rapid user growth but limited budget.

Performance Requirements

Teams with  low latency requirements might prefer solutions with more direct control over the authorization layer, especially for high throughput systems.

Implementation Complexity

For smaller projects with straightforward requirements, Permit.io might be overkill with many authorization features such as SCIM (System for Cross-Domain Identity Management) that you might not need. Smaller teams might prefer a lighter, more focused solution.

Integration Considerations

Before picking a solution, you should think about how it’ll fit into the rest of your stack. Teams with unusual tech stacks or legacy systems might find other solutions are more compatible with their environment.

Vendor Lock-in

Organizations that value flexibility might want a solution with clearer migration paths. Relying too much on the Permit.io ecosystem can create a good deal of vendor lock-in.

Deployment Requirements

Organizations with strict compliance requirements or specific deployment needs might find Permit.io’s deployment options too limited, especially those that need full control over their authorization infrastructure.

‍

‍

‍

Top Alternatives to Permit.io

1. Oso

Oso is the best Permit alternative for engineering driven companies that want more control and flexibility in their authorization implementation. Oso is a specialized authorization layer that integrates seamlessly into your existing codebase with a focus on developer-friendly workflows.

Oso offers several advantages that make it the better choice. The platform has an intuitive API design that makes implementation a breeze. Additionally, its purpose-built architecture is specifically optimized for microservices environments, making it great for the unique challenges of distributed systems. From my experience, this focus on developer-friendliness and easy of use makes a big difference, especially when you’re not an authorization expert.

With Oso, there are no surprises, and you’ll be working with a platform that you can rely on. Oso has a simple pricing model that makes budget planning very straightforward. They have predictable pricing starting at $149/month for the Startup tier. In terms of reliability, the platform delivers industry-leading uptime with 99.99% SLA guarantees, ensuring consistent availability for critical authorization functions. It’s trusted by teams such as Duolingo, PagerDuty, and Wayfair to run their authorization logic.

If switching to Oso sounds daunting, rest assured that there’s comprehensive migration tooling and services that are really handy for teams transitioning from existing systems. This significantly reduces implementation time and resource requirements.

In short, Oso is great for engineering teams that value control and flexibility while still wanting the benefits of a specialized authorization framework.

Why Oso is better than Permit.io?

• Oso’s Polar language is purpose-built declarative language for authorization, unlike Permit’s broad focus
• Oso has better support for higher-grade tooling for advanced access control
• Oso can work with existing authorization systems

What is Oso’s Pricing?

Oso’s pricing is diverse, designed to support different businesses. Developer-tier is free, while the first paid tier is a start-up tier retailing at $149/mo. Their growth tiers and migration services are custom priced based on needs.

2. Auth0

Auth0 is an identity platform with clean-cut APIs and SDKs.

Although Auth0 is mostly an identity platform, you’ll find that they provide authorization functionality as well through their Rules and Actions features. Auth0 stands out from Permit through its integration marketplace that contains connections to other technology stacks and third party services. This one platform for authorization and authentication plus the marketplace makes Auth0 a good choice if you don’t have complex authorization needs. This only becomes a challenge, if you decide to expand your authorization functionality down the line.

When thinking about Auth0 for your authorization, you should consider several factors. First, Auth0 doesn’t provide you much room to grow into a more sophisticated authorization process. Their approach to authorization is quite different than many dedicated authorization solution, meaning when the time comes to migrate away, it’ll be quite the undertaking. If you don’t expect to have complex authorization, you won’t need to move away, right? This isn’t always the case, especially for growing companies, and it comes down to cost.  You’ll be paying quite a bit more to do authorization through Auth0 compared to a dedicated authorization solution. I’ve seen several cases of teams needing to move away from Auth0 as they grow due to cost alone.

What are Pros of Auth0?

• Pre-built drop-in components that can reduce dev time
• Custom workflows
• Wide SDK coverage
• Enterprise integrations supported

What are Cons of Auth0?

• Pricing can easily surge on premium tiers with advanced features
• Proprietary lock-in risk
• Harder to self-host or audit
• Can be complex to manage at scale.

What is Auth0’s Pricing?

Auth0 offers a free-tier as well as premium-tiers. The most basic of the premium-tiers can range from $35-$150/month for 500 users based on use case. They also offer yearly pricing, as well as range to pick monthly active users.

3. Open Policy Agent (OPA)

Open Policy Agent, or OPA, is an open-source framework for authorization.

Under the hood, Permit.io uses OPA. OPA is an open-source policy engine that gives you a unified framework for enforcing policies across your tech stack. Rather than using OPA through Permit, your very much could use OPA directly.

Using OPA directly is great if you want the flexibility and cost savings associated with using an open-source project. With no licensing cost, OPA is a great choice for budget conscience teams who are looking to build complex authorization flows. Going directly to the open-source project also gives you the ultimate flexibility and protection against vendor lock-in. You can also rely on the OPA project. It has strong adoption in cloud-native environments and a very strong community that’s supporting it.

I’ve seen my fair share of teams dive directly into OPA, thinking they can roll their own authorization solution. Quickly they realize they’re in over their heads. This is because using OPA directly requires significant implementation resources from specialized experts in policy definition and system integration. OPA also lacks any functionality that would allow non-engineers to change the policies. If you want this, you’ll need to develop custom dashboards. Then there’s also the task of running and managing the infrastructure to support OPA. In short, if you are budget constrained but have the specialized resources required to operate OPA directly, it could be a good alternative to Permit.

What are Pros of Open Policy Agent?

• Open-source and free to use, with no licensing costs
• Highly flexible and customizable for complex authorization needs
• Strong community support and adoption in cloud-native environments
• Unified policy framework that can work across multiple services
• Vendor lock-in is avoided as it is not tied to any specific service
• Supports advanced authorization models and custom policy definitions

What are Cons of Open Policy Agent?

• Significant implementation effort required, especially for teams without expertise in policy definition and system integration
• No built-in user interfaces or dashboards for non-developers to manage policies
• Requires additional infrastructure and resources to run and maintain
• Lacks pre-built integrations, requiring custom development for specific use cases
• Can be overwhelming for smaller teams or projects with straightforward authorization needs

What is OPA’s Pricing?

OPA is open-source and free to use. However, there may be costs to implementing the solution.

4. Cerbos

Another alternative is Cerbos.

If using OPA directly sounds like a daunting task, Cerbos could be a good solution. Cerbos has an open-source core with optional commercial support. This gives you pretty flexible adoption pathways based on your team’s requirements. You can start with the open-source and then buy additional support and capabilities as needed.

Cerbos includes several notable features for organizations evaluating authorization options. Cerbos uses a YAML-based policy definition system which provides a simple policy creation and management experience. Cerbos is also easier to use than OPA because it comes with application-focused design patterns out of the box. This makes it easier to plug Cerbos into your product. Compared to cloud only authorization products, Cerbos offers local deployment options. This is great for teams that need ultra low latency authorization decisions.

When looking at Cerbos, there are several things to keep in mind, though. Cerbos is one of the newer players in the market which means it has a less mature ecosystem and less robust community resources.

Additionally, Cerbos provides more limited out-of-box integration options compared to other products. This means you might need additional development for specific technology stacks. The solution also offers limited interfaces for non-technical users, which may impact adoption in organizations where non-developers need to manage authorization policies.

In short Cerbos requires more implementation effort than fully-managed alternatives, but still gives you the flexibility of an open-source core. This is great if you see OPA as daunting but don’t want to rely on a service like Permit.

What are Pros of Cerbos?

• Declarative YAML policies with strong code versioning that is fully auditable and testable
• Supports local dev workflows
• Supports ABAC and Context-Aware Access
• Decoupled authorization logic

What are Cons of Cerbos?

• Lacks pre-built authentication or identity-features
• No built-in dashboards or GUIs—requires custom tooling
• Fewer community plugins compared to others such as Auth0 or Keycloak

What is Cerbos’s Pricing?

Cerbos features multiple plans. Their open-source plan is free forever. Cerbos Hub begins at $0/month for up to 100 monthly active principals. Their growth subscription retails at $25/month based on monthly active principals.

‍

Feature Comparison Table

‍

‍

‍

Why choose Oso over Permit.io?

Microservices First

Oso was built from the ground up as a microservices solution. Its architecture is designed to handle the complex authorization needs of distributed systems so it’s perfect for modern cloud native applications.

Developer Experience

Oso puts the developer experience first with clean, simple APIs and comprehensive docs. The learning curve is shorter and the integration feels more natural for engineering teams.

Migration Path

One of Oso’s biggest advantages is our dedicated migration service which can reduce migration time by up to 75%. This is especially helpful for teams moving from homegrown solutions or other authorization systems.

Flexibility

Oso offers cloud, hybrid and on-premises deployment options with 99.99% SLA so you have more control over your authorization infrastructure.

Simple Pricing

Oso’s pricing is more transparent with clear tiers starting at $149/month for startups. This is great for growing companies.

‍

‍

‍

Conclusion

For companies looking for an alternative to Permit.io, Oso stands out as the best solution. It’s a modern platform, built from the ground up to be developer friendly and microservices first. It provides the best combination of flexibility and simplicity that allows your team to get started quickly, and scale effortlessly. Lastly, it’s battle tested - trusted by companies like Duolingo, PagerDuty, and Wayfair.

‍

‍

‍

FAQ

Why is Oso better than Permit.io?

Oso is better in microservices environments with its purpose-built architecture and developer-friendly approach. Clearer pricing, dedicated migration services and higher SLA’s make it more attractive for engineering driven companies.

Why is it easy to migrate from Permit.io to Oso?

Migration complexity depends on your implementation but Oso’s dedicated migration services can reduce transition time by up to 75%. Our team will ensure 100% parity with your existing system while minimizing engineering overhead.

Can Oso support multi-tenant SaaS platforms?

Yes, Oso has multi-tenancy out of the box, so it’s perfect for SaaS applications that need to manage permissions across different customer environments.

How does Permit.io perform compared to Oso?

Both have local authorization decisions to minimize latency. But Oso’s microservices first design may have performance advantages in distributed systems where authorization decisions need to be made across multiple services.

‍

‍

‍

Introduction

Over the years, Auth0 has established itself as a player in the world of identity and access management. They offer an authentication and authorization platform that includes social login, multi-factor authentication (MFA), and configurable login flows. It is designed for users that seek a full-featured identity platform that requires minimal setup. When it comes to authorization, Auth0 provides built-in support through Rules and Actions. For more complex authorization that goes beyond RBAC, they offer Auth0 FGA, an add-on authorization product that requires a separate implementation.

While Auth0 is a suitable identify management solution, it’s worth exploring alternatives that might better align with your specific needs and budget constraints. Having been a builder for over a decade, and having experience building in the authorization space, I have a shortlist of products that I’d consider strong alternatives to Auth0.

‍

‍

‍

Why Consider Alternatives to Auth0?

Auth0's pricing structure is complex and becomes expensive quickly as you grow. While it offers authorization support, it's not designed for complex authorization models or strict compliance requirements. This becomes even more important if you’re building a product where fine-grained permissions are central to the product’s functionality.

Pricing Complexity and Cost

For Auth0, pricing starts at $35/month for 500 monthly active users and jumps to $240/month for 1,000 users on the Professional plan. These jumps in pricing can be challenging as you scale. Things get even worse if you need any of the features that are only available in higher tier plans like custom databases and advanced multi-factor auth.

For startups and growing companies, pricing alone can start to make Auth0 look less appealing.

Architectural Limitations

Although it has some authorization features, at it’s core Auth0 is designed to be an authentication solution. That means if you have a complex permission model, Auth0's role-based access control may not provide the flexibility you need for global permissions or attribute-based access control.

The platform takes an opinionated approach to identity management, which works well for standard use cases but can become limiting when you need to implement custom authorization logic that goes beyond simple role checks.

Developer Experience Challenges

Even though Auth0 has great documentation, the inherent architectural limitations of the product really harm the developer experience. To implement any complex authorization patterns, you’ll find yourself writing significant customer code or workarounds. This usually means your authorization logic ends up scattered throughout your application, making it harder to maintain and reason about.

For teams focused on iteration speed and developer velocity, the time sink of implementing and maintaining these authorization patterns in Auth0 can be painful.

‍

‍

‍

Top Alternatives to Auth0

1. Oso

Oso is the best alternative to Auth0. It’s an authorization product that takes a different approach by providing a specialized policy-as-code platform. Since Oso is purpose-built for authorization, it has a declarative policy language that simplifies expressing complex permission logic.

Pros of Oso has over Auth0:

• Declarative Policy Language: At Oso, we created the Polar language to enable developers to easily express authorization rules in a maintainable and readable way. This also allows you to centralize your authorization logic as opposed to scattering it across your codebase.
• Framework-agnostic integration: Oso has SDKs for all major programming languages, so you can have consistent authorization across your entire stack.
• Developer-first approach: With a free tier that’s actually useful for learning and experimentation, and pricing that scales more gradually (starting at $149/month for the Startup plan), Oso has a more predictable cost structure than Auth0’s tiered approach.
• Specialized for authorization: While Auth0 is great at authentication, Oso is focused on solving the authorization problem, with more advanced tools for complex permission models.

In summary, Oso is:

• Purpose-built declarative authorization
• Centralized, code-native authorization logic
• Focused on higher-grade tooling for advanced access control
• Works alongside existing authorization systems

Cons of Oso:

• No integrated identity provider: Oso is purpose-built for application authorization, so you'll supply your own identity provider.
• Closed-source approach: Unlike some Authorization providers, Oso has no open-source version of their cloud offering. If open-source is important to you, this may be a negative.

What is Oso’s Pricing?

Oso offers diverse pricing fit for specific scales of businesses. Developer-tier starts at $0/month, where as startup-tier begins at $149/month. Their growth-tier and migration services over custom pricing based on a consultation with an expert.

2. Okta

Okta is a full identity platform that competes directly with Auth0 (in fact, Okta acquired Auth0 in 2021, but they keep separate product lines). Okta has enterprise-grade identity management with strong SSO and many integrations.

Okta is grown to be more enterprise-focused than Auth0, with pricing and features for larger organizations. For smaller teams and startups, it can be overkill, especially due to its complex implementation requirements relative to other developer-focused alternatives. However, a Fortune 500 buyer would likely want to take a demo with Okta Cloud while also exploring other developer-first solutions like Oso.

Pros of Okta Identity Cloud:

• Extensive integration library
• Platform is not tied to a specific ecosystem
• Centralized management of identities and policies
• Adaptive multi-factor authentication
• Deep B2E Capabilities

Cons of Okta Identity Cloud:

• More Complex for Developers
• Similar features across multiple products can lead to confusion in picking the right tool
• Limited on-prem support
• Advanced customizations may require additional development effort
• Separate Offerings for Dev vs Enterprise

What is Okta Identity Cloud’s Pricing?

Okta Identity Cloud features premium pricing compared to some competitors and complex enterprise deployments requiring specialized expertise. Some users complain that similar features are present across multiple Okta products, sometimes making it confusing to know which product to use for a specific task. Okta does have a beginner tier, however, retailing at $6/user/month.

3. Keycloak

Keycloak is a comprehensive open-source identity and access management solution that provides enterprise-grade capabilities without licensing costs. For teams that value open-source, Keycloak is a strong candidate. Developed by Red Hat, Keycloak has strong feature parity with Auth0 (social login, MFA, customizable user flows).

The main advantage is cost: being open source, you can deploy Keycloak without license fees. But that means you having to manage your own infrastructure and security updates, requiring dedicated DevOps resources.

Pros of Keycloak:

• Fully open-source and self-hostable
• Out of the box enterprise features
• Everything is customizable
• Scalable without licensing costs
• Built-in admin console

Cons of Keycloak:

• Operational overhead
• Steep learning curve
• Lacks modern dev tools
• Complex authorization model

What is Keycloak’s Pricing?

For organizations building customer-facing applications, Keycloak can be economical in price. Keycloak doesn’t have per-user licensing fees, enabling organizations to scale to millions of users without escalating identity costs. Accordingly, Keycloak is popular amongst consumer applications, SaaS platforms, and other scenarios with large or unpredictable user bases.

4. Supabase Auth

Supabase Auth is an open-source authentication and authorization service tightly integrated with Postgres RLS. For teams already using Supabase for database or backend services, this auth system is a streamlined alternative to Auth0 with simple integration.

While not as feature-rich as Auth0 for complex enterprise scenarios, Supabase Auth is a good option for startups and smaller teams with simple pricing based on your Supabase usage rather than per-user. For hobbyists, Supabase Auth is particularly a great option given its friendly pricing and broader ecosystem libraries. However, it lacks more complex out-of-the-box functionality required by enterprise organizations.

Pros of Supabase Auth:

• Tight integration with Postgres
• Built-in social and email auth
• Great DX for fullstack apps
• Open-source Firebase alternative
• Realtime and event hooks

Cons of Supabase Auth:

• Postgres-centric
• Harder for frontend-heavy teams to implement as enforcing RLS requires strong SQL knowledge
• No granular Authz SDK
• Premature for enterprise use
• Limited identity federation

What is Supabase Auth’s Pricing?

Supabase offers a free-tier with 50,000 MAU and limited specs. Upgrading to the higher-tiers offers better specs, with the next being the pro-tier retailing from $25/month.

‍

‍

‍

Feature Comparison Table

Note: This comparison is based on features available as of May 2025. Always check the providers' websites for the most current information.

‍

‍

‍

Why Oso Over Auth0?

For applications where authorization is a core part of your application, Oso has several advantages over Auth0:

Centralized Authorization Logic

With Oso, you can define all your authorization rules in one place using a declarative policy language. This makes your permissions easier to understand, audit, and maintain compared to Auth0 where authorization logic is spread across your application code.

Flexible Permission Models

Oso is great at implementing complex permission patterns like attribute-based access control (ABAC) and global roles that go beyond Auth0’s pure relationship-based approach. This is important for applications with complex permission requirements.

Developer Productivity

As compared to Auth0, implementing authorization with Oso requires much less custom code if you’re looking to build complex permission scenarios. This is thanks to the clean abstractions that Oso provides for authorization. The result is faster development cycles and fewer authorization related bugs than implementing the same features with Auth0.

Scalable Pricing

Oso's pricing model also scales more gradually than Auth0's tiered approach. It starts at $149/month for the Startup plan with 300 MAUs. This provides more predictable costs as your user base grows, avoiding the significant jumps in Auth0's pricing tiers.

‍

‍

‍

Conclusion

Auth0 is still a good choice for authentication, but teams building applications with complex authorization needs should consider alternatives like Oso that specialize in application authorization. By separating authentication from authorization, you can use the best tool for the job rather than compromise with a one size fits all solution.

For senior engineers evaluating auth solutions the key is to assess your specific requirements around both authentication and authorization. If your application needs permission models more complex than simple role checks a specialized authorization solution like Oso paired with your authentication system of choice may be more maintainable and cost effective than relying solely on Auth0.

Ready to see how Oso can help with your authorization needs? Start with their free Developer tier to try out the platform or talk to their engineering team to chat about your use case.

‍

‍

FAQ

Why is Oso better than Auth0?

Oso focuses exclusively on authorization and has more advanced tools for complex permission models than Auth0’s more general purpose approach. With Oso’s declarative policy language you can express complex authorization rules more clearly and maintain them in a central location rather than scattering authorization logic throughout your application code like you do with Auth0.

How hard is it to migrate from Auth0 to Oso?

Migration complexity depends on your current implementation, but Oso is designed to work alongside your existing auth system. This means you can keep Auth0 for authentication and adopt Oso for authorization and do an incremental migration. Oso also offers migration services that can reduce engineering overhead and ensure parity with your existing system.

Can Oso support multi-tenant SaaS platforms?

Yes, Oso is built with multi-tenancy in mind and has native support for tenant isolation and per-tenant authorization rules. This makes it well suited for SaaS applications compared to Auth0 where implementing robust multi-tenancy requires significant custom development.

Introduction

Authorization and authentication are the foundation of modern application security. They decide who can access what and when, serving as critical infrastructure that protects your data and users. As cyber threats get more sophisticated, strong authorization and authentication matter more and more for all organizations.

In 2025, there are many authorization tools, with solutions for every organization, environment, and security requirement. From cloud native to open-source, the options can feel endless.

In this article, I will cover the top 21 authorization systems with a focus on solutions that are actively maintained, well-documented, and known for their reliability and performance. Some of these solutions are mainly focused on authentication with minimal authorization functionality, but I still include them for completeness. Whether you’re building a new application or strengthening your existing security stack, this guide will help you navigate the authorization maze and make informed decisions for your needs.

Developer-Focused Authorization Tools

Developer-focused authorization tools prioritize integration simplicity, flexible implementation, and specialized capabilities that address the unique challenges of modern application development.

1. Oso Cloud

Oso Cloud is a specialized authorization-as-a-service platform for developers who need fine-grained access control without the complexity of traditional solutions. Unlike full-stack IAM platforms that try to solve all identity problems, Oso focuses on authorization with a developer-first approach.

I would argue that Oso Cloud’s magic is in its purpose-built Polar language for authorization modeling. This declarative language makes complex authorization patterns accessible to developers without security expertise. Instead of implementing authorization logic across all your API endpoints, you can define central policies that express access rules in a way that’s both powerful and readable.

The hybrid architecture gives you unprecedented flexibility in data handling. This, in my opinion, is very important to security-conscious orgs. While many authorization solutions force you to centralize all data, Oso lets you choose what data to centralize vs what to keep in your app databases. Notably, this eliminates the overhead of full data replication while still giving you central policy management—perfect for microservices.

Oso Cloud integrates with any authentication system rather than providing an all-in-one identity solution. This specialization delivers exceptional authorization capabilities but requires pairing with a separate authentication provider for complete identity management.

Pros of Oso:

• Purpose-built declarative authorization
• Centralized, code-native authorization logic
• Focused on higher-grade tooling for advanced access control
• Works alongside existing authorization systems

Cons of Oso:

• No integrated identity provider: Oso is purpose-built for application authorization, so you'll supply your own identity provider.
• Closed-source approach: Unlike some Authorization providers, Oso has no open-source version of their cloud offering. If open-source is important to you, this may be a negative

What is Oso’s Pricing?

Oso offers diverse pricing fit for specific scales of businesses. Developer-tier starts at $0/month, where as startup-tier begins at $149/month. Their growth-tier and migration services over custom pricing based on a consultation with an expert.

2. Auth0

Auth0 is a platform centered around identity management, making advanced authentication and authorization available through clean-cut APIs and SDKs. Unlike traditional enterprise IAM solutions that put administrative controls first, Auth0 was built from the ground up to make identity simple for developers.Auth0 provides built-in support for basic authorization through Rules and Actions. For more complex authorization that goes beyond RBAC, they offer Auth0 FGA, an add-on authorization product that requires a separate implementation.”

Auth0 has an extensible model. With Rules, Hooks, and Actions, developers can customize authentication flows without touching application code. This makes Auth0 particularly strong at adaptations—from enriching user profiles with data from external systems to limited custom authorization logic.

Auth0’s pre-built components save implementation time. Instead of spending weeks building secure login flows, password reset functionality, and social login integration, developers can use Auth0’s drop-in widgets and libraries to implement these features in hours with security built-in.

Pros of Auth0:

• Drop-in components reduce dev time
• Customizable workflows
• Extensive SDK coverage
• Rich authentication features
• Enterprise integration capabilities

Cons of Auth0:

• Pricing can easily become premium with advanced features
• Proprietary lock-in risk
• Harder to self-host or audit
• Complex to manage at scale
• Advanced authorization models require implementing an additional product.

What is Auth0’s Pricing?

Auth0 offers a free-tier as well as premium-tiers. The most basic of the premium-tiers can range from $35-$150/month for 500 users based on use case. They also offer yearly pricing, as well as range to pick monthly active users.

3. Amazon Cognito

Amazon Cognito is a full authentication and authorization service deeply integrated with the AWS ecosystem. Unlike standalone identity providers, Cognito provides native access to AWS services while supporting applications hosted anywhere. For organizations that strongly prefer an all-in-one solution, choosing Amazon Cognito alongside the AWS stack is an intuitive option.

Cognito’s value is a function of its scalability and pay-as-you-go pricing. The service can handle authentication for millions of users with no upfront costs or capacity planning. This is helpful for consumer facing applications with unpredictable growth or seasonal usage spikes.

Cognito’s user pools and identity pools provide a flexible foundation for different identity scenarios. User pools manage user directories and authentication, while identity pools provide temporary AWS credentials to access backend resources. This allows developers to have fine grained control over authenticated users and anonymous visitors.

Pros of Amazon Cognito:

• AWS-Native integration
• Massive scalability
• Flexible identity models
• Secure and Compliant
• Cost-effective for apps with variable user loads