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Welcome to Sprint 03, where we focus on architecting the Continuous Integration and Continuous Deployment (CI/CD) pipeline for our application on Google Kubernetes Engine (GKE).

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Recap of Previous Sprints

So far, we have:
  • A working application stored in GitHub.
  • A Google Kubernetes Engine (GKE) cluster running on Google Cloud Platform (GCP).
  • Hands-on experience deploying our app manually to the cluster.
The image shows the Google Cloud Platform logo and the abbreviation "GKE" with a hexagonal icon, representing Google Kubernetes Engine.

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Why Automate Your GKE Deployments?

Automating deployments increases reliability, reduces human error, and accelerates delivery. A well-designed CI/CD pipeline will:
  • Build container images on every commit
  • Run automated tests (unit, integration)
  • Push images to Container Registry
  • Deploy to GKE with zero-downtime updates
  • Provide instant feedback on build or deployment failures
Consider using Google Container Registry or Artifact Registry to store and scan your Docker images.

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Key Design Discussion Topics

Before writing any pipeline code, we need to decide on:
The image shows an infinity loop diagram labeled "CI" and "CD," representing Continuous Integration and Continuous Deployment, with a gradient color scheme. It is titled "Design Discussion."

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Goals for Sprint 03

By the end of this sprint, we aim to deliver:
  • A documented design for our CI/CD pipeline, including architecture diagrams and decision rationale.
  • A prioritized task list covering:
    • Pipeline definitions (YAML files or scripts)
    • Service account creation and IAM roles
    • Secret management and access controls
    • Integration with Container Registry and monitoring tools
These deliverables will serve as the blueprint for implementing our automated builds and deployments in the next sprints.

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