Git Workflows Undergo Dramatic Evolution: From Gitflow to Trunk-Based Development

The landscape of Git workflows has undergone a significant transformation over the past decade, driven by evolving software development and deployment paradigms. Once considered the industry standard, Gitflow, introduced by Vincent Driessen in 2010, utilized multiple long-lived branches (main, develop, feature, release, hotfix) to manage complex, versioned software releases. It excelled in scenarios like mobile apps, desktop applications, or enterprise software where multiple versions require simultaneous support and rigorous auditing. However, Gitflow’s inherent complexity, slow development cycles, and tendency to generate merge conflicts due to long-lived branches proved counterproductive for modern web applications and continuous delivery environments. Its creator even later acknowledged its unsuitability for continuously deployed web applications, signaling a broader industry shift.

This shift gave rise to simpler, faster alternatives, notably GitHub Flow and Trunk-Based Development (TBD). GitHub Flow champions a single, always-deployable main branch, advocating for short-lived feature branches, pull requests for review, and immediate deployment upon merge. It’s ideally suited for SaaS products, APIs, and web services that deploy continuously and maintain only one live production version, emphasizing speed and simplicity for small to medium-sized teams with robust CI/CD and automated testing. However, it struggles with multi-version support and demands high team discipline. Elevating this concept, Trunk-Based Development (TBD) is now widely recognized as a best practice for high-performing DevOps teams. TBD emphasizes continuous integration, with developers committing directly to main (or very short-lived branches) multiple times a day. Incomplete features are managed using feature flags, allowing code to be continuously deployed to production while remaining invisible to users until ready. TBD requires experienced, disciplined teams and, critically, bulletproof automated testing and strong CI/CD pipelines to prevent regressions. This approach virtually eliminates merge conflicts, accelerates deployment frequency, and significantly improves recovery times. The evolution towards TBD has been enabled by the maturation of supporting technologies like advanced automated testing, sophisticated CI/CD tools, and dynamic feature flag management. While hybrid approaches exist to suit specific project needs, the overarching advice for teams is to optimize for speed of feedback and continuously iterate on their workflow, aiming towards TBD as a long-term goal by investing in robust automation, documentation, and performance measurement (DORA metrics).