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Zorluk: KolayAnalyzing Software Development Lifecycle (SDLC) and CI/CD Pipelines

An engineering team is building a secure CI/CD pipeline on Google Cloud Platform to deploy a microservice to Cloud Run. Arrange the following SDLC pipeline stages in the correct chronological order from developer commit to full production deployment.

  1. 1Developer commits source code changes to Cloud Source Repositories.
  2. 2Cloud Build executes automated unit tests and builds the container image.
  3. 3Artifact Analysis scans the container image for vulnerabilities before storing it in Artifact Registry.
  4. 4Cloud Build deploys a new revision to Cloud Run with a 10% canary traffic split.
  5. 5After monitoring health metrics, Cloud Build updates the traffic split to route 100% of traffic to the new revision.

Cevap

The correct chronological sequence for the GCP CI/CD deployment pipeline is: 1) Developer commits source code to Cloud Source Repositories, 2) Cloud Build executes unit tests and builds the container image, 3) Artifact Analysis scans the image for vulnerabilities before storing in Artifact Registry, 4) Cloud Build deploys the new revision to Cloud Run with a 10% canary traffic split, and 5) Cloud Build routes 100% of traffic to the new revision after health checks pass.
The correct sequence follows Google Cloud CI/CD best practices: Source Commit -> Build & Test -> Security Vulnerability Scan -> Canary Traffic Deployment -> 100% Traffic Promotion.

Adım Adım Çözüm

1
Identify the pipeline trigger stage.
Developer commit to source control initiates the continuous integration workflow.
Automated pipelines are triggered by code changes pushed to repository branches.
2
Identify the build and integration testing stage.
Cloud Build compiles the container image and runs unit tests.
Code must pass automated tests and build successfully prior to artifact storage.
3
Identify the security governance stage.
Artifact Analysis scans the container image for vulnerabilities before pushing to Artifact Registry.
Vulnerability scanning ensures compromised dependencies are identified before deployment.
4
Identify the initial deployment strategy.
Cloud Build creates a Cloud Run revision with a 10% canary traffic split.
Canary releases minimize blast radius by validating the update against real production traffic.
5
Identify the final production promotion stage.
Shift 100% of production traffic to the new Cloud Run revision.
Full promotion occurs only after metric monitoring verifies the canary release is stable.

Anahtar Kavram

Sequencing CI/CD pipeline stages from source code trigger to vulnerability scanning and canary deployment on GCP.
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