The Tool Desk
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A change can fail to remove a visible symptom and still be worth keeping—but only if it reduced risk, improved the evidence, or served another clear purpose. Those are different outcomes from fixing the underlying cause. In this account, the specific incident and reason for retaining the change are not established, so the decision should be judged by what the change demonstrably did, what it risked, and how quickly it could be verified.
Why didn’t the fix work?
A deployed change and a resolved incident are not the same thing. A mitigation can stabilize a service without removing the defect that triggered the problem. Microsoft’s incident-management guidance separates selecting a mitigation from verifying resolution, a useful distinction when reporting what a change accomplished. Microsoft Learn: Develop an Incident Management Practice to Recover from Disruptions
To explain a fix that appeared to do nothing, state three things separately: the symptom it was intended to affect, the signal used to judge success, and the observed result. If the symptom persisted, the change did not resolve that symptom. It may nevertheless have contained risk or clarified how the system behaves; those claims need their own evidence. Without incident-specific measurements or a stated mechanism, no particular root cause or benefit can be inferred.
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What could the change have achieved?
“Fixed nothing” can describe the visible outcome while overlooking a useful operational outcome. A change might have limited exposure, bought time for a safer repair, or tested a hypothesis. If it did none of these, retaining it needs another concrete justification; sunk effort alone is not one.
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Mitigation often does not require a code change. In Microsoft Research’s 2022 analysis of high-severity incidents, the reported responses included rollback (22.4%), infrastructure change (21.1%), external fix (15.8%), configuration fix (13.2%), ad-hoc fix (11.8%), code fix (7.9%), and transient mitigation (7.9%). The authors concluded that nearly 80% of the incidents they analyzed were mitigated without a code or configuration fix. These are findings from that study’s sample, not general industry rates. Microsoft Research: What Are the Main Causes of Cloud Service Outages?
Should I roll back a change that didn’t fix the issue?
Not automatically. If a user-impacting issue begins around the time a deployment starts, Microsoft advises assuming the change is a likely cause and rolling it back rather than spending a long time investigating first. That is operational guidance, not a rule that rollback is always safe or sufficient. Microsoft Learn: Develop an Incident Management Practice to Recover from Disruptions
Rank #2
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Rollback can be blunt, and reverting software may not undo persistent state changes. An incident-response study also describes a case in which responders later considered whether rollback might have yielded useful diagnostic information. The practical choice is therefore between restoring a safer state quickly and preserving a change that may contain evidence or reduce risk—not between “always revert” and “always keep.” USENIX: Incident Management in Practice
- User impact: Which option is expected to reduce harm fastest?
- Blast radius: How many users or components could the change affect if it is wrong?
- Reversibility and state: Can the software be reverted cleanly, and could the change have altered data or other persistent state?
- Causal evidence: How strongly does timing or an observed mechanism connect the change to the symptom?
- Verification speed: How soon can you tell whether keeping, reverting, or replacing it improved the relevant signal?
When the user impact is growing and the deployment is a plausible cause, fast rollback may be the safer first move. When rollback risks leaving incompatible state or removing a useful containment measure, the safer action may be a replacement or a narrower change. Record what evidence would make you switch decisions.
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How do I know whether a production fix worked?
Define the success signal before treating the change as a fix. Monitor the symptom users experienced, the scope of affected service, and any relevant error or reliability signal. Compare observations before and after the change over a period appropriate to the system’s behavior; a momentary improvement is not proof that the cause is gone. If the signal remains unhealthy, call the change a mitigation only if it demonstrably reduced impact; otherwise, say that it did not resolve the issue.
Reduce the cost of being wrong. Google Cloud recommends progressive rollouts for non-emergency changes—“don’t change everything at once”—so a harmful deployment affects less of production. A tested rollback path also helps teams mitigate problems quickly. Google Cloud: How incident management is done at Google
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Can a failed fix still teach you something?
Yes, if the team captures what it expected, what happened, and what that changes about the next decision. A useful postmortem records impact, mitigation, root cause, and follow-up actions. A blameless account examines the conditions and information behind decisions rather than assigning personal fault. Google SRE describes the principle this way: “A blamelessly written postmortem assumes that everyone involved in an incident had good intentions and did the right thing with the information they had.” Google SRE: Postmortem Culture: Learning from Failure
Quick Recap
- Record the user impact and the timeline of the symptom, change, and response.
- Separate what was mitigated from what root cause was confirmed.
- Note the evidence for keeping, reverting, or replacing the change, including any persistent-state concerns.
- Assign follow-up actions that can be verified, such as a targeted test, a safer rollout, or a rollback-path check.
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