Build Summary: v1.1.1 - Automated Release Management & Testing Infrastructure

• Date: October 8, 2025
• Project: acorninteractive.ca
• Version: v1.1.0 → v1.1.1
• Type: Patch - Fixing tag assignment to post deployment

Executive Summary

Version 1.1.1 represents a significant step forward in our development operations by establishing automated release management and testing infrastructure. This release introduces Git hooks via Husky, Jest testing framework integration, CI/CD auto-tagging based on semantic versioning, and comprehensive documentation—all designed to improve code quality, streamline releases, and increase visibility for both technical and non-technical stakeholders.

Key outcomes:

• Automated version tagging based on commit message keywords
• Pre-commit test execution preventing broken code from entering the repository
• Structured release workflow that aligns with project management processes
• Foundation for comprehensive test coverage as QA refactor progresses
• Enhanced observability into development and release planning

What Changed and Why

1. Husky Git Hooks Implementation

What: Installed Husky v9 to manage Git hooks that enforce code quality and release practices.

Why: Manual processes for testing and versioning are error-prone and inconsistent across team members. Automated enforcement ensures every commit meets our standards before entering the codebase, reducing bugs in production and creating a consistent development experience.

Technical changes:

• Added Husky as dev dependency
• Created .husky/ directory with hook scripts
• Configured prepare script in package.json for automatic setup
• Implemented two primary hooks: pre-commit and commit-msg

Files added/modified:

2. Jest Testing Framework Setup

What: Configured Jest testing framework with initial integration tests to validate Husky functionality.

Why: Establishing a testing framework now creates the foundation for comprehensive test coverage as we develop the QA environment refactor. Starting simple allows us to validate the infrastructure works before scaling to full test suites.

Technical changes:

• Installed Jest v27.2.5 and required Babel dependencies
• Created jest.config.js to bypass Meteor's Babel configuration conflicts
• Added test scripts to package.json with --watchAll=false for CI compatibility
• Created initial test suite in __tests__/husky.test.js

Configuration highlights:

Connection to QA Refactor:

As test plans and test cases are developed for the Meteor 3.3/React 18 refactor on the QA branch, we can expand this Jest framework to include unit tests, integration tests, and component tests. The pre-commit hook will automatically run these tests, catching regressions before they reach QA deployment.

3. Pre-Commit Hook: Automated Test Execution

What: Git hook that runs Jest tests before every commit on all branches.

Why: Fast feedback loops prevent developers from committing broken code. Running tests at commit time (rather than just at push or in CI/CD) catches issues immediately when context is fresh, reducing debugging time and preventing broken code from propagating through the team.

Behavior:

• Executes on every git commit command across all branches
• Runs Jest test suite (currently ~0.1 seconds)
• Blocks commit if any tests fail
• Provides clear error messages for failed tests

Example output:

4. Commit-Msg Hook: Version Keyword Enforcement

What: Git hook that validates commit messages on the production branch contain semantic versioning keywords.

Why: Automated tagging in CI/CD requires structured commit messages to determine version increments. Enforcing this at commit time (rather than discovering issues during deployment) ensures every production commit is release-ready and properly categorized.

Behavior:

1. Only enforces on production branch
2. Requires one of four keywords: [major], [minor], [patch], [hotfix]
3. Other branches (QA, staging, feature branches) commit freely without restriction
4. Provides helpful error messages with examples when validation fails

Version keywords:

• [major] - Breaking changes (v1.0.4 → v2.0.0)
• [minor] - New features, backward compatible (v1.0.4 → v1.1.0)
• [patch] - Bug fixes, small improvements (v1.0.4 → v1.0.5)
• [hotfix] - Emergency fixes (v1.0.4 → v1.0.4-hotfix.1)

5. CI/CD Auto-Tagging After Successful Deployment

What: Modified Bitbucket Pipelines to automatically create and push Git tags after successful production deployments.

Why: Manual tagging is a frequently forgotten step that breaks our release tracking and Zapier notifications. Automated tagging ensures every successful deployment creates a permanent, documented version in Git history without requiring developer intervention.

Pipeline changes:

• Added new step: "Create Production Tag After Successful Deployment"
• Parses commit messages to determine version bump type
• Automatically increments version based on semantic versioning rules
• Creates annotated tag with deployment metadata
• Pushes tag back to repository, triggering Zapier webhook

Technical implementation:

6. Comprehensive Documentation Updates

What: Updated README.md with detailed Husky documentation, commit message conventions, and workflow examples.

Why: Documentation serves as the single source of truth for team members and onboarding. Clear, comprehensive docs reduce confusion, support self-service learning, and ensure consistency across the team. This documentation also serves as a reference for non-technical stakeholders to understand our release processes.

Documentation sections added:

• What Husky does and why we use it
• Environment-specific setup instructions
• Commit message convention with examples for each keyword
• Complete workflow examples
• Troubleshooting guide

Why This Architecture Matters

Alignment Around Versions and Releases

This release establishes a structured release framework that requires alignment between technical implementation and project planning:

For Development Team:

• Clear semantic versioning rules tied to commit messages
• Automated quality gates (tests before commit, keywords before production commit)
• Consistent workflow across all team members
• Reduced cognitive load—automation handles repetitive tasks

For Project Management:

• Version keywords in commits map directly to project scope
• [major] releases should align with major project milestones
• [minor] releases correspond to completed feature sets
• [patch] and [hotfix] reflect maintenance work and urgent fixes
• Release planning can reference specific version numbers confidently

For Clients:

• Clear version history in Git tags with deployment dates
• Zapier webhooks can notify stakeholders of releases automatically
• Version numbers communicate the scale of changes (major vs minor vs patch)
• Release notes can be generated from commit messages and tag annotations

Building Test Coverage Foundation

The Jest framework implemented in this release is intentionally simple—two basic tests validating Husky integration. This simplicity is strategic:

Current state:

• Jest runs successfully in pre-commit hook
• Test execution is fast (~0.1s) and non-disruptive
• Infrastructure proven and ready for expansion

Future integration with QA refactor:

• As test plans are developed for the Meteor 3.3/React 18 refactor, we add corresponding Jest tests
• Test cases written in project management tools map 1:1 to Jest test files
• Component testing, integration testing, and E2E testing can all run through this same infrastructure
• Pre-commit hook scales automatically—no additional configuration needed

Example progression:

As test suite grows, we can optimize by:

• Running only tests related to changed files (lint-staged)
• Moving slower tests to pre-push hook
• Parallel test execution
• Strategic test splitting

Merging Structure Across Branches

Current state: This infrastructure exists only on the production branch.

Next steps: Merge this structure into staging and qa branches to create consistency:

Staging branch:

• Same Husky hooks apply
• Commit-msg validation could be optional or use different keywords
• Tests run on every commit
• Practice environment for release workflow before production

QA branch:

• Husky hooks present but potentially more lenient
• Ideal testing ground for new test suites as they're developed
• Version keywords optional (QA uses different tagging scheme like v3.3.0-rc1)
• Team can experiment with test-driven development practices

• Implementation plan:
• Merge Husky configuration from production → staging
• Validate behavior on staging deployments
• Merge to QA branch with modified commit-msg rules
• Document branch-specific behaviors in README

Impact on Team Workflow

Before this release:

• Manual testing before commits (often skipped)
• Inconsistent commit messages
• Manual tag creation (often forgotten)
• Limited visibility into releases
• Unclear version numbering

After this release:

• Automated testing on every commit (cannot be skipped)
• Structured, meaningful commit messages
• Automatic tag creation after successful deployment
• Clear version history and deployment tracking
• Semantic versioning communicated to all stakeholders

Developer experience:

• Initial learning curve
• Slightly longer commit process
• Clearer expectations and reduced cognitive load
• Better confidence in code quality before push
• Reduced time debugging issues that should have been caught earlier

Stakeholder experience:

• Clear understanding of what's being released and when
• Automated notifications of production deployments
• Version numbers that communicate scope of changes
• Documentation that explains technical decisions in business context
• Confidence in release process and deployment quality

Lessons Learned

1. Start simple with testing infrastructure - Two basic tests proved the system works. Expanding gradually prevents overwhelming the team.
2. Automate what humans forget - Tagging was frequently forgotten. Automation ensures it happens every time.
3. Branch-specific enforcement works well - Production requires strict rules, other branches have flexibility for experimentation.
4. Documentation is stakeholder communication - README and blog posts serve both technical and business audiences.
5. Semantic versioning requires discipline - Team must align on what constitutes major/minor/patch changes. This alignment happens in planning, not at commit time.
6. Fast feedback loops matter - 0.1s test execution makes pre-commit hook non-disruptive. As tests grow, performance monitoring becomes critical.
7. CI/CD pipeline orchestration enables sophisticated workflows - Moving tagging to post-deployment ensures tags only exist for successfully deployed code.

Conclusion

Version 1.1.1 establishes critical infrastructure for quality, consistency, and observability in our development process. By combining automated testing, semantic versioning, CI/CD orchestration, and comprehensive documentation, we've created a foundation that scales with the project.

The true value of this release isn't just the technical implementation—it's the alignment it creates between development, project management, and stakeholder communication. Version numbers now mean something concrete. Releases are documented and traceable. Progress is visible to everyone.

As we continue the Meteor 3.3/React 18 refactor on the QA branch, this infrastructure provides the testing framework, release workflow, and communication structure needed for a successful migration. Future blog posts will continue this pattern, documenting technical changes alongside business context, ensuring the entire team understands both how and why we build what we build.