146 lines
8.1 KiB
Markdown
146 lines
8.1 KiB
Markdown
# Feature Specification: Continuous Integration Pipeline
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**Feature Branch**: `001-ci-pipeline`
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**Created**: 2026-08-21
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**Status**: Draft
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**Input**: User description: "Close out Phase 1 (engineering foundation) gaps: an automated CI pipeline that validates every change before it can be merged/deployed, per docs/09-testing-observability-cicd.md section 3."
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## User Scenarios & Testing *(mandatory)*
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### User Story 1 - Every change is automatically validated before merge (Priority: P1)
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An engineer pushes a change (new commit or pull request) to the repository. Before the change
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can be merged or deployed, the system automatically checks out the code, installs dependencies,
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validates required environment/configuration, and runs type-checking, linting, format-checking,
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and the automated test suites (unit, integration, E2E) against it, then reports pass/fail back
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to the engineer.
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**Why this priority**: This is the baseline safety net every other phase depends on. Without it,
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regressions in later phases (ticketing, orchestration, AI support) can reach production
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undetected, and the constitution's "MUST verify compliance before merge" governance rule has no
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automated enforcement.
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**Independent Test**: Push a commit that fails a lint rule (or a failing test) and confirm the
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pipeline reports failure and blocks the change; push a clean commit and confirm the pipeline
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reports success end-to-end.
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**Acceptance Scenarios**:
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1. **Given** a new commit is pushed, **When** the pipeline runs, **Then** it executes checkout,
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dependency install, environment validation, type-check, lint, format-check, unit tests,
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integration tests, and E2E tests, in that order, and stops at the first failing stage.
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2. **Given** all validation stages pass, **When** the pipeline reaches the build stage, **Then**
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it produces a build artifact and a container image ready for the next stage.
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3. **Given** any validation stage fails, **When** the pipeline reports status, **Then** the
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engineer can see which stage failed and why, without needing to reproduce the failure
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manually to get that information.
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---
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### User Story 2 - A validated build can be published and deployed without manual steps (Priority: P2)
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Once a change has passed all validation stages, the system publishes the resulting build
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artifact/image and can deploy it to an environment (e.g. test/staging/production) using
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environment-specific configuration and credentials, without an engineer manually running deploy
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commands.
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**Why this priority**: Automating publish/deploy is what makes the validation in User Story 1
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actually load-bearing — a validated build that still requires manual, error-prone deploy steps
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undermines the safety the pipeline is meant to provide. It's second priority because User Story
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1 (catching regressions) delivers value even before deploy is automated.
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**Independent Test**: Merge a validated change and confirm it is published and deployed to a
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target environment automatically, with no manual command execution required.
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**Acceptance Scenarios**:
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1. **Given** a build has passed every validation stage, **When** the pipeline reaches
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publish/deploy, **Then** the artifact is published and deployed to the target environment
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using that environment's own configuration and credentials.
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2. **Given** a deploy targets a production environment, **When** the pipeline runs, **Then** it
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uses protected, environment-managed credentials and never reads secrets from a file committed
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to the repository.
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---
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### Edge Cases
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- What happens when a required environment variable/secret is missing for the target
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environment? The pipeline MUST fail fast at the environment-validation stage with a clear
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message identifying what's missing, before running any test or build stage.
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- What happens when a pipeline run is triggered for a branch/change that has no deploy target
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(e.g., a feature branch, not main)? The pipeline MUST still run all validation stages through
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build, but MUST NOT publish or deploy.
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- How does the system handle two changes validating concurrently? Each run MUST be isolated —
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one run's failure or artifacts must not affect a concurrent run for a different change.
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- What happens when a stage (e.g. E2E tests) is flaky and fails intermittently for reasons
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unrelated to the change? Out of scope for this feature — flaky-test quarantine/retry policy is
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a separate concern to be addressed if/when it becomes a problem.
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## Requirements *(mandatory)*
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### Functional Requirements
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- **FR-001**: The system MUST automatically run on every proposed change (commit/pull request)
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without requiring an engineer to manually trigger validation.
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- **FR-002**: The system MUST validate that required environment configuration is present and
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well-formed before running any test stage, and MUST fail with a specific, actionable message
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if it is not.
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- **FR-003**: The system MUST run, in order, and stop at the first failure: type-checking,
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lint checks, format checks, unit tests, integration tests, and end-to-end tests.
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- **FR-004**: The system MUST report which stage failed and the relevant failure output back to
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the engineer who proposed the change, without requiring local reproduction to see it.
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- **FR-005**: The system MUST only proceed to build/publish/deploy stages after every prior
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validation stage has passed.
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- **FR-006**: The system MUST produce a versioned, reproducible build artifact and container
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image once validation passes.
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- **FR-007**: The system MUST support deploying the same validated artifact to multiple
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environments (at minimum: test/staging and production), using environment-specific
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configuration.
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- **FR-008**: The system MUST NOT read production secrets/credentials from any file committed
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to the repository — environment credentials MUST be supplied by the pipeline's own protected
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configuration at run time.
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- **FR-009**: The system MUST isolate concurrent pipeline runs so that one change's validation
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or build artifacts cannot affect another concurrent run.
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- **FR-010**: The system MUST make current and historical pipeline run status (pass/fail, per
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stage) visible to engineers without requiring direct server/log access.
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### Key Entities
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- **Pipeline Run**: One execution of the full validate → build → publish → deploy sequence for
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a specific change; has an ordered list of stage results and an overall pass/fail outcome.
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- **Stage Result**: The outcome (pass/fail, output) of one stage (e.g. lint, unit test) within a
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Pipeline Run.
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- **Deploy Target**: An environment (test, staging, production) a validated build can be
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published/deployed to, with its own configuration and credentials.
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## Success Criteria *(mandatory)*
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### Measurable Outcomes
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- **SC-001**: 100% of proposed changes are validated automatically before merge — zero changes
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reach the main branch without having passed the pipeline.
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- **SC-002**: An engineer can determine which validation stage failed, and why, within 1 minute
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of the pipeline completing, without reproducing the issue locally.
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- **SC-003**: A validated change can be deployed to any supported environment with zero manual
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deploy commands run by an engineer.
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- **SC-004**: No production secret ever appears in repository history (verified by secret-scan
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of the repository).
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- **SC-005**: Two changes validating at the same time never interfere with each other's result
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(zero cross-run contamination incidents).
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## Assumptions
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- "Environments" for deploy purposes are, at minimum, test/staging and production, matching the
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`.env.test` / `.env.development` / `.env.prod` split already present in the codebase's package
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scripts.
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- The existing local quality scripts (typecheck, lint, format:check, test:unit, test:integration,
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test:e2e, build) are the source of truth for what each pipeline stage runs — this feature wires
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them into an automated, triggered pipeline rather than defining new checks.
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- Deployment targets are container-based (the repository already has Docker Compose files per
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environment), so "publish" means publishing a container image and "deploy" means rolling it
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out via the existing container orchestration for that environment.
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