This content originally appeared on DEV Community and was authored by Wolfgang Rathgeb
Git Flow is a proven framework, but unlike Git itself, it’s not a set standard. Just because it’s well-documented and has excellent tool support doesn’t mean other git branching techniques couldn’t improve your performance much better – Git Flow could cost more than you think.
I’ve implemented Git Flow in teams multiple times, and in all cases it was an improvement. But when things change, the tools have to change sometimes too.
The pattern is clear: teams often choose Git Flow because it sounds professional, not because they analysed whether it solves their actual problems. Here’s how to choose more intentionally based on my experience.
TL;DR: Quick Decision Matrix
| Risk Level | Small Team (2-4) | Medium+ Team (4+) |
|---|---|---|
|
Low Risk Tolerance (Poor testing, compliance, can’t break production) |
Simplified Git Flow | Simplified- / Git Flow |
|
High Risk Tolerance (Good testing, can handle brief issues) |
Trunk-based / GitHub Flow | GitHub Flow |
Want to understand the reasoning behind these recommendations? Read on for the detailed analysis.
Why Git Workflow Structure Matters
Your team’s structure and working style should drive your git branching strategy choice, not the other way around. Every development team needs some git workflow structure. The key question: which approach actually fits your team’s constraints?
Several factors influence this choice for development teams:
Testing Maturity – Strong automated tests enable faster workflows. Manual testing requires more structured release processes.
Risk Tolerance – Can your team afford brief production issues, or does any downtime create serious problems? This depends on your testing confidence, but also regulatory requirements, financial impact, and business criticality.
Deployment Frequency – Daily deployments need different team coordination than scheduled releases.
Team Structure – Your team size, experience levels, and working relationships matter more than you think. Small experienced teams coordinate naturally. Large or mixed-experience teams need formal processes.
Multiple Version Maintenance – Supporting different customer versions simultaneously breaks most standard workflows.
Tool Constraints – GitHub’s basic merge capabilities work differently than Bitbucket’s Git Flow integration.
We’ll focus on the three most fundamental factors for development teams: testing maturity, risk tolerance, and team structure. We’ll examine testing maturity and risk tolerance together because of their similarity for most teams.
Testing Maturity & Risk Tolerance: The Foundation of Workflow Choice
Testing confidence directly shapes what git workflow risks your team can accept. Development teams with strong automated testing can use faster, simpler workflows. Teams without solid testing need workflow barriers to prevent chaos. The key insight: you can reduce workflow complexity by investing in better testing practices first.
However, testing quality isn’t the only factor. Regulatory requirements, financial impact, and business criticality also constrain your team’s choices.
I’ve seen this dynamic play out across different projects. At an education platform with insufficient automated tests and poor manual testing, Git Flow couldn’t solve our underlying quality problems. While it improved stability, the fundamental issues remained – structure alone wasn’t enough when the quality foundation was missing.
A public sector project showed a different pattern. With no automated tests but solid manual testing processes, Git Flow provided necessary release structure and worked well for organising deployments. However, even this success came with hidden costs. Developers frequently had to context-switch back to fix old code days later when manual testing found issues, destroying team focus and momentum. We improved this by using available testing capacity to test during the development phase rather than only at release time.
The lesson for development teams: Git Flow can organise existing quality processes, but it cannot replace missing ones. Rather than adding workflow complexity to manage poor feedback loops, invest in better testing practices first. This enables simpler, more efficient workflows long-term.
Team Structure: Coordination Complexity Drives Process Needs
Your team’s structure determines coordination complexity. This directly affects how much formal process your git branching strategy needs. Team size matters, but experience levels and working relationships matter more.
At a startup with 2-3 experienced developers who knew each other well, trunk-based development or GitHub Flow worked perfectly (never forget the other factors). But with a monolith codebase and 4+ mixed-experience developers, our team needed formal processes.
In large development teams, trunk-based approaches generally become problematic. Check the other factors to make the right decision for your team.
Multiple Version Maintenance: When Git Flow Gets Complex
Git Flow assumes linear progression: develop → release → main → next cycle. But maintaining multiple versions for different customers breaks this model entirely. When your team needs to backport fixes to v1.5, v2.1, and v3.0 simultaneously, Git Flow’s dual-branch structure becomes unwieldy.
At the education platform, we needed to transition away from Git Flow when version maintenance became necessary. But I argued against making the change at that time – the timing was too chaotic with pandemic-related stress to add a workflow change on top of everything else. People need capacity to execute such processes. Even though the Git workflow would have become simpler, the transition itself would have been another major burden. This experience confirmed that workflow changes need stability windows. Better to stabilise first, then evolve when the team has bandwidth for change.
Most Git Flow tooling doesn’t support multi-version scenarios well. Your development team ends up with complex cherry-picking workflows and coordination overhead. This defeats the purpose of having a structured process.
For teams maintaining multiple versions: Consider branch-per-version strategies instead of trying to force Git Flow into a model it wasn’t designed for.
Git Flow Complexity: Hidden Coordination Overhead
Git Flow looks simple in theory but requires sophisticated tooling for development teams to use properly. Desktop clients like SourceTree or GitKraken support the branching operations fine. But they don’t help with pull request workflows that most teams rely on.
The problem: Git Flow’s dual-branch model needs coordinated merging. Hotfixes must reach both main AND develop. Release branches need proper handling. Feature branches require dual-branch coordination. Only Bitbucket has proper integration for this – and even then, your team sometimes has to do manual steps with hotfixes.
With GitHub or GitLab, development teams end up with manual coordination steps that people forget. This creates merge conflicts and missed updates. The alternative is building CI/CD pipeline automation to handle the missing coordination. But this adds complexity most teams don’t expect when choosing Git Flow.
main o---------o-------o
\ / /
release \ o-------o
\ / /
develop o-o-------o
\ /
feature o-----o
GitHub Flow: Simple and Fast
GitHub Flow works with a single main branch representing production. Development teams create feature branches from main, develop changes, merge back via pull request, and deploy immediately. This eliminates coordination complexity entirely.
main o---------o--------o
\ / \ /
feature o-----o o-o--o
This git branching strategy works well when your team has solid automated testing and can tolerate briefly buggy versions whilst fixes deploy. The fast feedback loop and minimal overhead make it ideal for development teams with good testing discipline and acceptable risk tolerance.
The limitation: No formal release process for stakeholder review or coordinated deployments. If your team needs testing phases or scheduled releases, GitHub Flow becomes problematic.
Trunk-Based Development: Minimal Branching
Trunk-based development means your entire team commits directly to main. Only viable for solo developers or very small, highly coordinated teams (2-3 people doing pair programming). Most development teams should start with GitHub Flow instead.
main o-o-o-o-o-o-o-o-o
Simplified Git Flow: The Middle Ground
Based on my experience with Git Flow’s coordination problems across multiple development teams, I invented this simplified approach. It keeps the release structure whilst eliminating the dual-branch complexity. Your team works directly with main as the integration branch, creating release branches when ready for formal testing and stakeholder review.
main o-----o---o---o---o---o-----o---o
\ / \ / \ / /
feature o-o \ / o-o /
\ / /
release-1.0 o-o / (tag v1.0, deploy, delete branch)
\ /
hotfix-1.0.1 o-------o (tag v1.0.1, merge back to main)
The workflow for development teams: Branch from main when ready to create a release. Test and review on the release branch. Tag the release branch commit itself. Deploy from that tagged commit, then delete the release branch. For hotfixes, branch from the specific tag you need to fix, then merge back to main.
Benefits for your team: Formal release process without dual-branch coordination. Works with basic tooling. Eliminates the develop/main synchronisation overhead. Tools like changeset can help manage versioning, tags, and changelogs automatically. You get Git Flow’s structure with much simpler coordination.
Don’t Fear Changing Your Workflow
The technical part of switching git workflows is trivial for development teams – Git doesn’t care about your branch names or merging patterns. The real challenge is organisational: achieving team acceptance, retraining habits, and managing the transition period.
The most important measure for any development team: does your git branching strategy help your team or constantly fight against you? Some friction is normal – that’s the price of having a versioning tool, and it’s worth it. But if your team is fighting the workflow more than benefiting from it, it’s time to evolve.
Start somewhere reasonable for your team, learn what works for your specific situation, then adjust based on reality rather than theory. Your development team isn’t locked into the first choice forever.
This content originally appeared on DEV Community and was authored by Wolfgang Rathgeb