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Welcome back! In Sprint 03, we completed the design discussion around CI/CD on Google Cloud Platform (GCP), defined our problem statement, evaluated native GCP services, and selected the tools for an automated pipeline.

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Completed Work

We mapped out Continuous Integration and Continuous Deployment as an “infinity loop” to show how commits flow through build, test, and deploy stages—emphasizing feedback loops and full automation.
The image shows an infinity loop diagram representing CI/CD (Continuous Integration/Continuous Deployment) with a gradient color scheme. It is labeled "Design Discussion on CI/CD."

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Next Sprint: Implementation Roadmap

In Sprint 04, we’ll shift focus to hands-on setup using GCP services. Below is our task breakdown:
TaskObjectiveKey Activities
Explore Cloud BuildLearn GCP’s managed CI service• Configure build triggers
• Define steps & substitutions
• Author cloudbuild.yaml
Understand Artifact RegistryCompare to Container Registry• Review repository types & regions
• Set IAM permissions
• Discuss supported artifacts (Docker, Maven, npm, etc.)
Implement Build & Push PipelineAutomate Docker image creation and publishing• Fetch source from GitHub
• Build with cloudbuild.yaml
• Tag & push to Artifact Registry
Make sure your cloudbuild.yaml is correctly indented. Even a single space error can cause build failures.
Verify IAM roles for Cloud Build and Artifact Registry. Missing permissions will block image pushes.
The conceptual flow below illustrates how Cloud Build retrieves code from GitHub, builds a Docker image via cloudbuild.yaml, and securely pushes it to Artifact Registry with proper tagging and permissions.
The image is a diagram showing a process flow from "Cloud Build" to "GCP Artifact Registry" with a Docker icon in between, indicating a containerization process.
That wraps up our Sprint 03 review. In the next lesson, we’ll deep-dive into Cloud Build configuration and create our first automated pipeline. See you soon!

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