Release Branches with Extensive Backporting

What This Looks Like

The team has branches named release/2.1, release/2.2, and release/2.3, each representing a version in active use. When a developer fixes a bug on trunk, the fix needs to go into all three release branches because customers are running all three versions. The developer fixes the bug once, then applies the same fix three times via cherry-pick, one branch at a time. Each cherry-pick requires a separate review, a separate CI run, and a separate deployment.

If the bug fix applies cleanly, the process takes an afternoon. If any of the release branches has diverged enough that the cherry-pick conflicts, the developer must manually resolve the conflict in a version of the code they are not familiar with. When the conflict is non-trivial, the fix on the older branch may need to be reimplemented from scratch because the surrounding code is different enough that the original approach does not apply.

Common variations:

• The customer-pinned version. A major enterprise customer is on version 2.1 and cannot upgrade due to internal approval processes. Every security fix must be backported to 2.1 until the customer eventually migrates - which takes years. One customer extends your maintenance obligations indefinitely.
• The parallel feature tracks. Separate release branches carry different feature sets for different customer segments. A fix to a shared component must go into every feature track. The team has effectively built multiple products that share a codebase but diverge continuously.
• The release-then-hotfix cycle. A release branch is created for stabilization, bugs are found during stabilization, fixes are applied to the release branch, those fixes are then backported to trunk. Then the next release branch is created, and the cycle repeats.
• The version cemetery. Branches for old versions are never officially retired. The team has vague commitments to “support” old versions. Backporting requests arrive sporadically. Developers fix bugs in version branches they have never worked in, without understanding the full context of why the code looked the way it did.

The telltale sign: when a developer fixes a bug, the first question is “which branches does this need to go into?” - and the answer is usually more than one.

Why This Is a Problem

Release branches with backporting look like a reasonable support strategy. Customers want stability in the version they have deployed. But the branch strategy trades customer stability for developer instability: the team can never move cleanly forward because they are always partially living in the past.

It reduces quality

A fix that works on trunk introduces a new bug on the release branch because the surrounding code is different enough that the original approach no longer applies. That regression appears in a version the team tests less rigorously, and is reported by a customer weeks later. Backporting a fix to a different codebase version is not the same as applying the fix in context. The release branch may have a different version of the code surrounding the bug. The fix that correctly handles the problem on trunk may be incorrect, incomplete, or inapplicable on the release branch. The developer doing the backport must evaluate the fix in a context they did not write and may not fully understand.

This creates a category of bugs unique to backporting: fixes that work on trunk but introduce new problems on the release branch. By the time a customer reports the regression, the developer who did the backport has moved on and may not even remember the original fix.

When a team runs a single releasable trunk, every fix is applied once, in context, by the developer who understands the change. The quality of the fix is limited only by that developer’s understanding

• not by the combinatorial complexity of applying it across multiple code states.

It increases rework

The rework in a backporting workflow is structural. Every fix done once on trunk becomes multiple units of work: one cherry-pick per maintained release branch, each with its own review and CI run. Three branches means three times the work. Five branches means five times the work. The rework is not optional - it is built into the process.

Conflict resolution compounds the rework. A backport that conflicts requires the developer to understand the conflict, decide how to resolve it, and verify the resolution is correct. Each of these steps can be as expensive as the original fix. A one-hour bug fix can become three hours of backporting work, much of it spent reworking the fix in unfamiliar code.

Backport tracking is also rework. Someone must maintain the record of which fixes have been applied to which branches. When the record is incomplete - which it always is - bugs that were fixed on trunk reappear in release branches, requiring diagnosis to confirm they were fixed and investigation to understand why the fix did not propagate.

It makes delivery timelines unpredictable

When a critical security vulnerability is disclosed, the team must patch all supported release branches simultaneously. The time required is a multiple of the number of branches times the complexity of each backport. That time cannot be estimated in advance because conflicts are unpredictable. A patch that takes two hours to develop can take two days to backport if release branches have diverged significantly.

For planned features and improvements, the release branch strategy introduces a ceiling on development velocity. The team can only move as fast as they can service all their active branches. As branches accumulate, the overhead per feature grows until the team is spending more time backporting than developing. At that point, the team is maintaining the past rather than building the future.

Planning also becomes unreliable because backport work is interrupt-driven. A customer escalation against an old version stops forward work. The interrupt is not predictable in advance, so sprint commitments cannot account for it.

It creates maintenance debt that compounds over time

New developers join and find release branches full of code that looks nothing like trunk, written by people who have left, with no tests and no documentation. That is not a warning sign of future problems - it is the current state of teams with five active release branches. Each additional release branch increases the maintenance surface. Two branches is twice the maintenance of one. Five branches is five times the maintenance. As branches age, the code on them diverges further from trunk, making future backports increasingly difficult. The team can never retire a branch safely because they do not know who is using it or what they would break.

Over time, the team accumulates branches they cannot merge back to trunk - the divergence is too large - and cannot delete without risking customer impact. The branches become frozen artifacts that must be preserved indefinitely.

Impact on continuous delivery

CD requires a single path to production through trunk. Release branches with backporting create multiple parallel paths, each with its own test results, its own deployments, and its own risks. The pipeline cannot provide a single authoritative signal about system health because there are multiple systems, each evolving independently.

The backporting overhead also limits how fast the team can respond to production issues. When a bug is found in production, the fix must pass through multiple branch-specific pipelines before all affected versions are patched. In CD, a fix from commit to production can take minutes. In a multi-branch environment, the same fix might not reach all affected versions for days, because each branch has its own queue of testing and deployment.

How to Fix It

Eliminating release branches requires changing how versioning and customer support commitments are handled. The technical changes are straightforward. The harder changes are organizational: how the team handles customer upgrade requests, how compatibility is maintained, and how support commitments are scoped.

Step 1: Inventory all active release branches and their consumers (Week 1)

Before retiring any branch, understand who depends on it.

1. List every active release branch and when it was created.
2. For each branch, identify what customers or systems are running that version.
3. Identify the date of the last backport to each branch.
4. Assess how far each branch has diverged from trunk.

This inventory usually reveals that some branches have no known active consumers and can be retired immediately. Others have consumers who could upgrade but have not been prompted to. Only a small number typically have consumers with genuine constraints on upgrading.

Step 2: Define and communicate a version support policy (Week 2)

The underlying driver of branch proliferation is the absence of a clear policy on how long versions are supported. Without a policy, support obligations are open-ended.

1. Define a maximum support window. Common choices are N-1 (only the previous major version is supported alongside the current), a fixed time window (12 or 18 months), or a fixed number of minor releases.
2. Communicate the policy to customers. Give them a migration timeline.
3. Apply the policy retroactively: branches outside the support window are retired, with notice.

This is a business decision, not a technical one. Engineering leadership needs to align with product and customer success teams. But without a policy, the technical remediation of the branching problem cannot proceed.

Step 3: Invest in backward compatibility to reduce upgrade friction (Weeks 2-6)

Many customers stay on old versions because upgrades are painful. If every upgrade requires configuration changes, API updates, and re-testing, customers defer upgrades indefinitely. Reducing upgrade friction reduces the business pressure to maintain old versions.

1. Identify the most common upgrade blockers from customer escalations.
2. Add backward compatibility layers: deprecated API endpoints that still work, configuration migration tools, clear upgrade guides.
3. For breaking changes, use API versioning rather than code branching. The API maintains the old contract while the implementation moves forward.

The goal is that upgrading from N-1 to N is low-risk and well-supported. Customers who can upgrade easily will, which reduces the population on old versions.

Step 4: Replace backporting with forward-only fixes on supported versions (Weeks 4-8)

For versions within the support window, stop cherry-picking from trunk. Instead, fix on the oldest supported version and merge forward.

1. When a bug is reported against version 2.1, fix it on the release/2.1 branch.
2. Merge the fix forward: 2.1 to 2.2 to 2.3 to trunk.
3. Forward merges are less likely to conflict than backports because the forward merge builds on the older fix rather than trying to apply a trunk-context fix to older code.

This is still more work than a single fix on trunk, but it eliminates the class of bugs caused by backporting a trunk-context fix to incompatible older code.

Step 5: Reduce to one supported release branch alongside trunk (Weeks 6-12)

Work toward a state where only the most recent release branch is maintained, with all others retired.

1. Accelerate customer migrations for all versions outside the N-1 policy.
2. Retire branches as their consumer count reaches zero.
3. For the last remaining release branch, evaluate whether it can be eliminated by using feature flags on trunk to manage staged rollouts instead of a separate branch.

Once the team is running trunk and at most one release branch, the maintenance overhead drops dramatically. Backporting one version is manageable. Backporting five is not.

Step 6: Move to trunk-only with feature flags and staged rollouts (Ongoing)

The end state is trunk-only. Customers on “the current version” get staged access to new features through flags. There is one codebase to maintain, one pipeline to run, and one set of tests to pass.

Measuring Progress

Related Content

• Trunk-Based Development - The model that eliminates the need for release branches
• Cherry-Pick Releases - The earlier-stage pattern that often precedes extensive release branching
• Small Batches - Small releases reduce the business pressure to maintain old versions
• Work Decomposition - Decomposing work for safe incremental delivery without version branching
• Single Path to Production - Why multiple release branches undermine pipeline effectiveness