Choosing a Kubernetes Policy Engine#

Kubernetes does not enforce security best practices by default. A freshly deployed cluster allows containers to run as root, pull images from any registry, mount the host filesystem, and use the host network. Policy engines close this gap by intercepting API requests through admission webhooks and rejecting or modifying resources that violate your rules.

The three main options – Pod Security Admission (built-in), OPA Gatekeeper, and Kyverno – serve different needs. Choosing the wrong one leads to either insufficient enforcement or unnecessary operational burden.

Implementing Compliance as Code#

Compliance as code encodes compliance requirements as machine-readable policies evaluated automatically, continuously, and with every change. Instead of quarterly spreadsheet audits, a policy like “all S3 buckets must have encryption enabled” becomes a check that runs in CI, blocks non-compliant Terraform plans, and scans running infrastructure hourly. Evidence generation is automatic. Drift is detected immediately.

Step 1: Map Compliance Controls to Technical Policies#

Translate your compliance framework’s controls into specific, testable technical requirements. This mapping bridges auditor language and infrastructure code.

Static Validation Patterns#

Static validation catches infrastructure errors before anything is deployed. No cluster needed, no cloud credentials needed, no cost incurred. These tools analyze configuration files – Helm charts, Kubernetes manifests, Terraform modules, Kustomize overlays – and report problems that would cause failures at deploy time.

Static validation does not replace integration testing. It cannot verify that a service starts successfully, that a pod can pull its image, or that a database accepts connections. What it catches are structural errors: malformed YAML, invalid API versions, missing required fields, policy violations, deprecated resources, and misconfigured values. In practice, this covers roughly 40% of infrastructure issues – the ones that are cheapest to find and cheapest to fix.

Testing Infrastructure Code#

Infrastructure code has a unique testing challenge: the thing you are testing is expensive to instantiate. You cannot spin up a VPC, an RDS instance, and an EKS cluster for every pull request and tear it down 5 minutes later without significant cost and time. But you also cannot ship untested infrastructure changes to production without risk.

The solution is the same as in software engineering: a testing pyramid. Fast, cheap tests at the bottom catch most errors. Slower, expensive tests at the top catch the rest. The key is knowing what to test at which level.

OPA Gatekeeper: Policy as Code for Kubernetes#

Gatekeeper is a Kubernetes-native policy engine built on Open Policy Agent (OPA). It runs as a validating admission webhook and evaluates policies written in Rego against every matching API request. Instead of deploying raw Rego files to an OPA server, Gatekeeper uses Custom Resource Definitions: you define policies as ConstraintTemplates and instantiate them as Constraints. This makes policy management declarative, auditable, and version-controlled.