One Kubernetes Policy and One CI/CD Pipeline Across AWS, GCP and Azure: How to Stop Maintaining Three Playbooks
Blog post from Qovery
A unified Kubernetes policy set and CI/CD workflow across AWS, GCP, Azure, and private clusters is presented as achievable when teams set the portability boundary at the Kubernetes API: manifests, RBAC, admission policies, rollout strategies, and observability can be shared, while cloud-specific concerns such as IAM, load balancers, storage classes, node pools, networking, and managed databases should be isolated in per-cluster configuration overlays. The proposed architecture uses a common policy engine such as Kyverno or OPA Gatekeeper, Pod Security Admission as a baseline, pull-based GitOps through Argo CD or Flux, and a cloud-neutral CI process that builds, scans, signs, and promotes immutable image digests without retaining cluster credentials. Argo CD ApplicationSets or equivalent mechanisms can distribute one application definition to labeled clusters, while External Secrets Operator and per-cluster SecretStores provide a common secrets interface across cloud-native secret services. To limit operational drift, the approach recommends fleet-wide Kubernetes version targets, centrally managed add-on bundles, consistent cluster labels, staged policy enforcement, and shared infrastructure abstractions through Terraform wrapper modules, Cluster API, or Crossplane. It argues that the ongoing burden of upgrades, compatibility testing, policy maintenance, and platform operations can outweigh initial implementation work, making managed internal developer platforms such as Qovery a potential alternative for organizations without sufficient dedicated platform engineering capacity.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Kubernetes | 45 | 2,610 | 243 | 77 | -40% |
| Platform Engineering | 16 | 908 | 205 | 70 | -46% |
| Secrets Management | 11 | 1,356 | 312 | 102 | -34% |
| MCP | 8 | 5,797 | 566 | 174 | -45% |
| OpenTelemetry | 4 | 408 | 84 | 43 | -41% |
| Observability | 3 | 1,557 | 387 | 135 | -43% |
| AI Agents | 1 | 3,062 | 780 | 195 | -45% |
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