CI Pipeline Workflow

CI Pipeline Workflow

Quick Start

Task Progress:
- [ ] Step 1: Audit existing pipeline
- [ ] Step 2: Design stage structure
- [ ] Step 3: Optimize test parallelization
- [ ] Step 4: Configure artifact management
- [ ] Step 5: Implement and validate

Step 1: Audit Existing Pipeline

• Map the current pipeline stages, their dependencies, and execution times.
• Identify bottlenecks: which stages take the longest? Which block others unnecessarily?
• Check for flaky tests that cause unnecessary reruns.
• Review resource usage: are runners appropriately sized? Are caches effective?
• Measure total pipeline duration from push to deployable artifact.

Step 2: Design Stage Structure

• Organize into logical stages: install, lint, typecheck, unit test, integration test, build, deploy.
• Maximize parallelism: lint, typecheck, and unit tests can run in parallel after install.
• Use fail-fast: if lint fails, skip tests. If unit tests fail, skip integration tests.
• Gate deployments behind all quality checks.
• Separate environment-specific deployment stages (staging, production) with manual approval gates for production.

Step 3: Optimize Test Parallelization

• Split test suites across multiple runners using test file sharding or test duration-based splitting.
• Use test timing data from previous runs to balance shard workloads.
• Run unit tests and integration tests on separate runners in parallel.
• For monorepos: only run tests for changed packages and their dependents.
• Cache test results for unchanged code paths where the test framework supports it.

Step 4: Configure Artifact Management

• Build artifacts once, deploy the same artifact to all environments.
• Tag artifacts with commit SHA and build number for traceability.
• Set retention policies: keep production artifacts longer, clean up PR artifacts after merge.
• Store build metadata (git SHA, branch, build time, test results) alongside artifacts.
• Use content-addressable storage or artifact registries appropriate to the project (npm, Docker, S3).

Step 5: Implement and Validate

• Implement pipeline changes incrementally — test each stage change in a feature branch.
• Verify caching works: first run populates cache, second run uses it (confirmed by cache hit log output).
• Confirm parallel stages don't have hidden dependencies causing race conditions.
• Measure pipeline duration improvement against the baseline from Step 1.
• Document the pipeline architecture for the team.

Pipeline Performance Targets

Metric	Target
Lint + typecheck	< 2 minutes
Unit tests	< 5 minutes
Integration tests	< 10 minutes
Full pipeline (push to artifact)	< 15 minutes
Cache hit ratio	> 80%

Error Handling

• Pipeline config syntax errors: Validate workflow YAML locally (e.g., actionlint for GitHub Actions) before pushing. Report the exact line and field causing the parse failure.
• Flaky tests block pipeline: Identify the flaky test(s) by re-running the failing job. If confirmed flaky, quarantine the test with a tracking issue reference and unblock the pipeline.
• Cache invalidation causes slow builds: Verify cache key patterns match the lockfile hash. If caches are stale, clear them and document the corrected key strategy.

Definition of Done

• Pipeline stages optimized with maximum parallelism
• Test parallelization configured and balanced
• Artifact management with retention policies
• Pipeline duration meets performance targets
• Documentation updated with pipeline architecture