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 Gatekeeper?
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
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:
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.
Create Constraints: Instantiate Constraints from your ConstraintTemplates, specifying the parameters and the resources they should apply to.
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.
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!
About the author
Mathew Pregasen
Technical Writer
Mathew Pregasen is a technical writer and developer based out of New York City. After founding a sales technology company, Battlecard, Mathew focused his attention on technical literature, covering topics spanning security, databases, infrastructure, and authorization. Mathew is an alumnus of Columbia University and YCombinator.
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