pipeline-go

CI/CD methodology and deployment orchestration

pipeline-go

The operational backbone - deployment methodology, CI/CD, and quality gates

Pipeline-go encodes F3L1X development methodology: architecture patterns, deployment workflows, testing standards, and quality gates. It's not just a tool—it's a specification that all realms follow to stay consistent and reliable.

What It Does

Pipeline-go serves as:

  1. Methodology Kernel - The blueprint for how realms are built
  2. CI/CD Pipeline - Automated testing, building, deployment
  3. Deployment Dashboard - Monitor and manage releases
  4. Rollback Management - Revert bad deployments with one click
  5. Quality Gates - Enforce standards before code deploys

Think of pipeline-go as your quality assurance team in software form—ensuring every change meets standards before it reaches users.

Key Capabilities

Methodology Enforcement

  • Architecture Patterns: HackSoftware directory structure
  • Coding Standards: Python, Django, JavaScript style guides
  • Testing Requirements: TDD workflow, minimum coverage thresholds
  • Git Conventions: Commit message format, PR requirements
  • Documentation Standards: CLAUDE.md, spec.md, ACTIVITY_LOG.md

CI/CD Pipeline

  • Automated Testing: Run test suite on every commit
  • Security Scanning: SAST (static analysis), dependency checks
  • Build Automation: Compile assets, collect static files
  • Docker Containerization: Build and push container images
  • Multi-Stage Deployment: Dev to staging to production

Deployment Management

  • Release Orchestration: Coordinate deployments across realms
  • Railway Integration: Deploy to Railway hosting platform
  • Database Migrations: Automatic migration sequencing
  • Rollback Safety: Revert to previous version if needed
  • Deployment Monitoring: Track deployment health

Accessing pipeline-go

Web Dashboard

URL: http://127.0.0.1:8023

The pipeline-go dashboard shows deployment status, history, and logs.

Deployment Commands

python manage.py deploy staging
python manage.py deploy production
python manage.py rollback
python manage.py deployment-history

Common Use Cases

Use Case 1: Deploy New Feature

Commit code, tests run automatically, deployment to staging, then production with zero-downtime rollback if needed.

Use Case 2: Monitor Test Coverage

Dashboard tracks coverage over time, blocks deployments if below 80% threshold.

Use Case 3: Rollback Failed Deployment

One-click rollback to previous working version with automatic database schema rollback.

Important Notes

Git Workflow Standards

Commit format: <verb> <what> - <why if not obvious>

Include: Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Quality Gates

Tests must pass, coverage >80%, no critical security issues, code follows conventions.

Troubleshooting

Deployment blocked by tests

Fix failing tests, push new commit.

Coverage below threshold

Add tests to increase coverage above 80%.

Security scan found vulnerability

Update dependencies or patch vulnerability.

  • realm-spawn - Creates realms following pipeline-go standards
  • worker-bee - Monitors pipeline health
  • test-master - Orchestrates testing
  • All active realms - Follow pipeline-go methodology

Further Reading