Kyverno vs OPA and Gatekeeper: Which Policy Engine Should You Run?

Both tools do the same core job: they sit in the Kubernetes admission path as a webhook and decide whether a resource may be created as written. Both can also audit what is already in the cluster. If you only need "block privileged containers", either will do it, and the choice comes down to how a rule is expressed and where else you need that rule to run.

The historic separator was the language. Gatekeeper compiles Rego, OPA's policy language, supplied through a ConstraintTemplate and then instantiated as Constraints. Kyverno answered that with policies written as ordinary Kubernetes YAML — no new language, no compilation step, nothing to learn beyond manifests you already write. That contrast drove most adoption arguments for years.

It no longer holds. Kyverno's current policy types — ValidatingPolicy, MutatingPolicy, GeneratingPolicy, DeletingPolicy and ImageValidatingPolicy, stable since v1.18 — express their conditions in CEL, the Common Expression Language. The older ClusterPolicy, the one that was pure YAML matching, is deprecated and due for removal. So a fair comparison today is CEL against Rego, plus a difference in scope that matters more than either.

OPA is not a Kubernetes tool. It is a general-purpose policy engine, CNCF graduated since 2021, and its documented integrations run well past admission control: Envoy and Istio for service authorization, Terraform and CloudFormation for infrastructure plans, CI/CD pipelines, HTTP and GraphQL APIs, Kafka, even SSH and sudo. If you want one policy language and one review process across all of those, this is the only option of the two that offers it.

Rego is more expressive than CEL. It was purpose-built for querying complex hierarchical data, and it handles joins, aggregation and set logic that CEL expresses awkwardly or not at all. For policies that reason across several documents at once rather than judging one resource, that headroom is real rather than theoretical.

And Gatekeeper does mutate. This is worth stating plainly because outdated comparisons still claim otherwise: mutation has been stable since Gatekeeper v3.10 through Assign, AssignMetadata, ModifySet and AssignImage. It is more constrained than Kyverno's — AssignMetadata can only add a label or annotation, not modify an existing one — but "Gatekeeper cannot mutate" is simply no longer true.

Policies are Kubernetes resources, end to end. There is no ConstraintTemplate-then-Constraint indirection: one custom resource carries the match and the logic, so kubectl, kustomize, git review and RBAC all work on policy exactly as they work on a Deployment. That is a smaller conceptual surface, and it is why Kyverno tends to be quicker to adopt on a team that is not already fluent in OPA.

It does more than validate and mutate. Kyverno can generate resources — cloning a registry Secret into every new namespace, or templating a default NetworkPolicy when a Namespace appears — and keep them synchronised with their source afterwards. It can also delete on a schedule. Neither has an equivalent in Gatekeeper, and for platform teams that automation is often the reason Kyverno is chosen at all.

Image verification is built in. ImageValidatingPolicy verifies Cosign and Notary signatures and attestations, supports keyless verification against an accepted issuer and subject, and can rewrite a tag to the digest it just verified. With OPA that supply-chain work lives in a separate tool.

And the CEL choice has a compounding benefit: it is the same language as upstream Kubernetes ValidatingAdmissionPolicy, so what you learn transfers — and Kyverno can generate those native policies, moving enforcement into the API server and removing a webhook hop entirely.

Choosing Kyverno means accepting that your policy language stops at the cluster edge. When someone later asks for the same rule on Terraform plans or in the API gateway, you will be standing up a second engine and maintaining two expressions of one intent. That is a real cost, and it usually arrives a year after the decision rather than during it.

Choosing OPA means paying the Rego tax up front, and paying it again with every engineer who joins. Rego is learnable and its expressiveness is genuine, but it is a language your team has no other reason to know — and a policy nobody can confidently read is a policy nobody will change.

A useful tiebreaker: ask who will write and review the fiftieth policy, not the first. If it is a platform team that will invest in the tooling, Rego's ceiling is worth it. If it is application teams contributing guardrails to their own namespaces, the lower barrier tends to win — and CEL sits in between, which is much of why Kyverno moved to it.