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I shipped a change expecting it to resolve a visible production problem. The symptom remained, so the change did not fix what users could see. Keeping it was still a decision worth examining: a mitigation can reduce risk or reveal useful information without repairing the underlying defect—but neither benefit should be assumed. The right call depends on what the change actually did, how risky it was to leave in place, and what evidence would show whether it helped.
Why didn’t the fix work?
A change can fail to remove a symptom for several different reasons: it may not address the underlying cause, it may only have been intended to limit impact, or the available signal may not yet show whether it changed anything. The title alone does not establish which explanation applied here, so the useful distinction is between what the change was expected to do and what was observed after it shipped.
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Before calling a production change successful, define the outcome it was meant to produce and the signal that would demonstrate it. That could be a user-visible symptom improving, an operational risk being contained, or a new piece of evidence narrowing the cause. If the expected signal did not change, say so plainly. Do not describe the root cause as fixed unless it was identified and the repair was verified.
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Stabilize service without repairing the defect
A mitigation and a root-cause repair are different outcomes. A mitigation may reduce immediate user impact while leaving the underlying defect intact. Microsoft’s incident-management guidance separates choosing a mitigation from verifying resolution, a distinction that helps avoid presenting temporary stabilization as a complete fix: Develop an Incident Management Practice to Recover from Disruptions.
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Provide evidence—or no meaningful benefit
A change can also function as a diagnostic probe: its effect, or lack of effect, may help narrow the possibilities. But that value should be stated only when the observation actually informs a next step. If the change neither improved the symptom, contained risk, nor produced actionable evidence, keeping it requires a different justification—and a clear explanation of the remaining risk.
Mitigation does not have to mean a code change
In Microsoft Research’s 2022 study of high-severity incidents, the reported mitigation categories were 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 figures describe that study’s sample; they are not general industry rates. They do illustrate why “we shipped a fix” and “we fixed the root cause” are not interchangeable claims: Microsoft Research: What Are the Main Causes of High-Severity Incidents in Cloud Services?
Should I roll back a change that didn’t fix the issue?
Often, a recently shipped change is the safest first suspect when the user impact began around the time it was deployed. Microsoft’s Azure Well-Architected guidance recommends assuming the change is likely responsible and rolling it back rather than spending a long time investigating first. That is operational guidance, not a rule that fits every system: Microsoft Learn’s incident-management guidance.
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Rollback can be a fast recovery action, but it is not automatically safe or complete. A study of incident response describes rollback as potentially blunt and notes that reverting software may not restore persistent state. In one case, responders later thought a rollback might also have provided useful diagnostic information. Consider what a reversal would do to data, state, and user impact before treating it as a clean undo: USENIX: Incident Management in Practice.
Compare the available actions
Use these questions to make the choice legible. They are a practical decision framework, not a universal formula.
- Keep it: Is there evidence it contains risk or provides actionable information? What user impact and blast radius remain if it stays?
- Revert it: Is the change plausibly connected to the incident? Can it be reversed safely, including any persistent-state effects?
- Replace it: Is there a more targeted mitigation or repair with a smaller blast radius and a signal you can verify quickly?
- Set a decision trigger: What observation, risk threshold, or time limit would make you change course?
The stronger the causal evidence and the greater the ongoing user impact, the more urgent a corrective action becomes. If the change is difficult to reverse or may have altered persistent state, account for that before acting. Record what evidence would have changed the decision; otherwise, “we kept it” can sound like a conclusion without a test.
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How do I know whether a production fix worked?
Choose a verification signal before or as the change is made, then check it against the expected outcome. The signal should correspond to the original problem—not just to the fact that deployment completed. State what was observed and over what period only when those details are known; do not imply success from the absence of a new report or from a change being live.
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Can a failed fix still teach you something?
Yes, if the incident record captures what happened and turns it into a useful next action. A postmortem should distinguish impact, mitigation, root cause, and follow-up work. That structure makes it possible to say that a mitigation was attempted, the symptom remained, and the cause is still unresolved without overstating what the change accomplished.
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Google’s SRE postmortem guidance calls for a blameless account: one that assumes people acted with good intentions and the information they had. Blamelessness does not mean avoiding accountability for decisions; it means investigating the conditions, information, and processes behind them so the organization can learn: Google SRE: Postmortem Culture: Learning from Failure.
A useful record should identify the user impact, the mitigation attempted, the evidence available at the time, the reason for keeping or reverting the change, and the follow-up that will test the next hypothesis. If the evidence did not establish that the symptom improved, say that directly. The lesson may be that the change was a useful containment step—or that it should not have remained in production. Either conclusion needs evidence, not hindsight alone.
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