Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesTo take a bad change back, you first stop it from spreading, then pick the right recovery tool for where the change lives: committed source, a running deployment, or a feature flag. Good source history, staged exposure, monitoring, and a rehearsed recovery path cannot guarantee that nobody notices. What they do is limit how many users are affected and shorten the time to recovery.
Three recovery tools that solve different problems
People often use “rollback” for three separate actions. They overlap, but each one repairs a different layer of the system.
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| Recovery tool | What it reverses | What it does not do |
|---|---|---|
Source revert (git revert) |
A committed change, by recording a new commit that undoes it | Does not redeploy anything or undo data, infrastructure, or artifacts produced by the bad build |
| Deployment rollback | The version that is running in an environment, by redeploying an earlier known-good version through the platform’s procedure | Does not rewrite history, and does not automatically return database state or generated artifacts to a safe state |
| Feature disablement | The behavior of new code that already shipped, by turning a flag off | Does not remove the code, and does not help if the fault lives in a change that is not behind a flag |
In practice, containment usually comes first (stop exposure or disable the feature), then the team chooses between reverting the source and rolling back the deployment, or fixing forward.
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Prepare before the change ships
Most of the work that determines how fast you recover happens before the bad change reaches production. Three preparations matter most.
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- Keep changes small enough to reason about. A small commit is easier to identify, revert, and explain than a bundled release.
- Deploy through an approved, repeatable workflow. If the only way to deploy is a manual sequence that exists in one engineer’s memory, rollback will be a manual sequence too.
- Define the stop signal in advance. Decide which health indicators (error rate, latency, a key business transaction) will halt the rollout, and who is allowed to halt it.
The AWS Well-Architected Framework, in its operational practice OPS06-BP01, states: “In either situation, a fix forward or rollback plan should be well documented and tested before deployment to live production so that the time it takes to revert a change is minimized.” The guidance also recommends measuring outage duration and change data so that the next recovery is faster than the last.
Microsoft’s Azure guidance on safe deployments takes the same line on stopping: when a rollout group reports an issue, the rollout should stop immediately, and the team then investigates cause and severity. The point is to stop first and diagnose second.
Revert a bad commit in Git
Use git revert when the intent is to record a compensating change in the history rather than erase the bad one. Git’s documentation describes it as creating a new commit that reverses an earlier commit, which keeps the record of both the change and the correction. Reset and restore are different: Git’s manual warns that those commands can discard uncommitted changes, so they are not a safe substitute for a revert on shared history.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware match- Identify the faulty commit with
git logand confirm its scope withgit show <commit>. - Confirm the working tree is clean with
git status. Git requires a clean working tree for revert, so stash or commit anything in progress first. - Run
git revert <commit>. Git opens the commit message editor; write a message that states the bad change, the symptom, and why the revert is the chosen fix. - If the commit is a merge, add
-m 1(or the parent number of the mainline) so Git knows which side to keep. Understand that reverting a merge changes what later merges bring in. Reverting a merge does not remove the changes from the branch that was merged, so a later merge of that branch may not reapply them until the situation is handled deliberately. - If conflicts occur, resolve them, then run
git revert --continue. Usegit revert --skipto drop the current commit from the sequence, orgit revert --abortto return the branch to its state before the revert started. - Push the revert through the normal review and pipeline path. Reverting in Git changes source only; it does not change what is running in production until a deployment carries it out.
Roll back a deployed version
When the bad version is already in an environment, first identify the version that is actually running. The commit you think is live and the artifact that is live are not always the same. Then run the rollback procedure your deployment platform defines. Do not assume that returning the application code also returns data, infrastructure, configuration, or generated artifacts to a safe state.
Job-based rollbacks in GitLab
GitLab’s deployment documentation describes a rollback as creating a new deployment that points to an earlier commit. The deployment script must define how that deployment happens, so a rollback only works if the rollback logic is present in the job script. GitLab also notes that some artifact-producing jobs from earlier pipelines may need to be run again separately, because the earlier build outputs are not necessarily what the rollback needs. Check this during rehearsal, not during the incident.
Rolling back with stateful changes
Rollback is hardest when the bad change touched a database, a schema, a queue, or another stateful system. If the new version wrote data in a format the old version cannot read, returning the code can make the failure worse. In that situation a safe fix-forward may be the better path, or the rollback plan must include the data steps explicitly. Azure’s guidance on safe deployments makes the same point: the recovery procedure has to account for data changes and workload design.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use staged exposure to limit the damage
Staged rollouts reduce how many users see a bad change before anyone can act. Canary, rolling, blue/green, traffic splitting, and feature flags all provide a way to limit exposure or to halt or reverse a rollout. The canary is the clearest example: the new version runs beside the stable deployment and receives a small share of traffic, and the team watches errors, performance, and unexpected behavior before increasing that share.
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Kubernetes’ canary tutorial shows the basic pattern. The canary Deployment runs alongside the stable Deployment, and the team can stop the canary by scaling it to zero with a command such as kubectl scale deployment <canary-name> --replicas=0. Scaling to zero keeps the Deployment object in place, so it can still be inspected after the fact, and stable capacity can be restored as needed. Production systems usually automate the sequence: shift traffic, monitor, then promote or roll back based on the health signals defined in advance.
Choose between rollback and fix-forward
Rollback returns the system to a known working configuration. Fix-forward applies a correction during the rollout. Neither is universally better, and the choice depends on three things: how severe the impact is, what state the system is in, and whether any stateful change can be reversed safely.
- Roll back when the previous version is known to work, the change is recent and self-contained, and reversing it does not require undoing data writes.
- Fix forward when the previous version cannot safely read the new data, when the fix is small and well understood, or when rolling back would itself cause an outage.
- Disable the feature first, when the new behavior sits behind a flag. This contains the impact quickly and leaves the decision about code for later.
Recovery checklist
- Identify the faulty change and its scope: which commit, which artifact, which environments, and which users.
- Stop or limit further rollout, and disable the feature if a flag controls it.
- Choose rollback or fix-forward based on the system and data state.
- Verify the restored behavior with monitoring, not only with a successful deployment status.
- Communicate the incident and record the reason for the chosen recovery path.
- Review the recovery time and update the procedure so the next recovery is faster.
No single statistic on rollback time or deployment failure rates is established across the official guidance cited here, so treat the recovery time you measure in your own system as the baseline that matters.
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