KodeKloud Notes

Overview

In Sprint 05, our team focused on extending our Google Kubernetes Engine (GKE) continuous delivery workflow. The primary objectives were to:

Isolate resources by creating a dedicated Kubernetes namespace
Deploy our container image using a Kubernetes Deployment manifest
Automate build and deploy steps via Cloud Build
Verify that pods and services are running as expected

Sprint Goals

Objective	Description
Namespace Creation	Provision a new namespace in GKE for application isolation
Deployment Manifest	Define a `Deployment` YAML to run our container image at scale
CI/CD Pipeline Update	Upgrade the Cloud Build configuration to build & deploy automatically
Deployment Validation	Confirm pods are ready and services are reachable

The image lists sprint goals, including creating a namespace in a GKE cluster, creating a deployment file, updating Cloud Build code, and validating the deployment.

Achievements

Namespace Provisioned
Successfully created my-app-namespace in our GKE cluster.
Deployment Manifest Applied
Deployed app-deployment.yaml with replica scaling and liveness probes.
Cloud Build Pipeline Modified
Added build triggers and deployment steps to cloudbuild.yaml.
End-to-End Validation
Verified pod readiness with kubectl get pods and service endpoints via kubectl port-forward.

Warning

A Cloud Build step failed due to an outdated builder image. Always inspect build logs with:

gcloud builds log BUILD_ID

Then update the cloudbuild.yaml to reference the latest builder tags.

Key Takeaways

Automating deployments with Cloud Build reduces manual errors.
Namespaces provide effective isolation for development and production workloads.
Regularly update pipeline images and inspect CI logs for faster troubleshooting.

References

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