Building a Kubernetes Deployment Pipeline: From Code Push to Production#

A deployment pipeline connects a code commit to a running container in your cluster. This operational sequence walks through building one end-to-end, with decision points at each phase and verification steps to confirm the pipeline works before moving on.

Phase 1 – Source Control and CI#

Step 1: Repository Structure#

Every deployable service needs three things alongside its application code: a Dockerfile, deployment manifests, and a CI pipeline definition.

Canary Deployments Deep Dive#

A canary deployment sends a small percentage of traffic to a new version of your application while the majority continues hitting the stable version. You monitor the canary for errors, latency regressions, and business metric anomalies. If the canary is healthy, you gradually increase its traffic share until it handles 100%. If something is wrong, you roll back with minimal user impact.

Why Canary Over Rolling Update#

A standard Kubernetes rolling update replaces pods one by one until all pods run the new version. The problem is timing. By the time you notice a bug in your monitoring dashboards, the rolling update may have already replaced most or all pods. Every user is now hitting the broken version.

Feature Flags: Decoupling Deployment from Release#

Deployment and release are not the same thing. Deployment is shipping code to production. Release is enabling that code for users. Feature flags make this separation explicit. You deploy code that sits behind a conditional check, and you control when and for whom that code activates – independently of when it was deployed.

This distinction changes how teams work. Developers merge unfinished features to main because the code is behind a flag and invisible to users. A broken feature can be disabled in seconds without a rollback deploy. New features roll out to 1% of users, then 10%, then 50%, then 100%, with a kill switch available at every stage.