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To find “failure DNA” in old incidents, compare consistent postmortem records across time: separate each trigger from the conditions that allowed it to cause harm, then look for recurring mechanisms and turn them into owned prevention, detection, or response work. “Failure DNA” is a practical metaphor for those recurring patterns—not a single hidden cause or a formal scientific category.
What to preserve in each incident record
Pattern-finding depends on records that are both comparable and detailed enough to explain what happened. Use a consistent structure, but keep the narrative context: categories alone can conceal important differences between incidents. Google recommends recording trigger and root cause in a standard postmortem template so teams can analyze trends later (Google SRE Workbook: Incident Management: Postmortem Analysis).
- Timeline: when the event began, was detected, escalated, mitigated, and resolved.
- Service and impact: what failed and which users or systems were affected.
- Trigger: the event that activated the weakness, such as a change or a shift in user behavior.
- Contributing conditions: the software behavior, process, dependency, capacity, monitoring, or other circumstances that shaped the outcome.
- Detection and evidence: what first exposed the incident and which alerts, logs, or records clarified the mechanism.
- Response and resolution: what responders did, how impact was reduced, and how service was restored.
- Follow-up actions: what will prevent recurrence, improve detection, reduce impact, or strengthen response—and who owns each action.
Writing should be blameless without becoming vague about responsibility for system improvements. Google’s SRE guidance says, “A blamelessly written postmortem assumes that everyone involved in an incident had good intentions and did the right thing with the information they had.” The chapter by John Lunney and Sue Lueder emphasizes examining the information and conditions available at the time, rather than indicting an individual (Google SRE: Postmortem Culture: Learning from Failure).
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Review incidents as a collection, not just as isolated stories. Google’s guidance recommends aggregating structured postmortem data to surface trends and areas where larger investment may be needed (Google SRE: Incident Management Guide).
Separate triggers from contributing conditions
Ask what activated the weakness, then ask why the system was vulnerable to it and why the impact reached users. A deployment may be the trigger; a latent software defect, inadequate safeguards, or a fragile dependency may be among the contributing conditions. Recording these separately helps avoid treating the most visible event as the whole explanation.
Group by mechanism, not just by headline
Compare software behavior, development or deployment processes, complex system interactions, network behavior, capacity, and other categories supported by the evidence in the records. Preserve nuance when an incident spans several mechanisms; do not force it into a convenient label just to make a chart cleaner.
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Compare detection, impact, response, and recurrence
Look for patterns in what first revealed an incident, which evidence established its mechanism, who or what was affected, and how mitigation or coordination influenced the duration. Then connect the follow-up actions to later records: did the same condition appear again, or is there evidence the relevant risk changed?
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What Google’s historical postmortem data shows
Google’s SRE Workbook reports an analysis of thousands of postmortems across the period 2010–2017. Its figures illustrate how one organization categorized incidents; they are historical shares from Google’s dataset, not current outage rates or an industry benchmark (Google SRE Workbook: Incident Management: Postmortem Analysis).
| Measure | Google category | Share | Scope |
|---|---|---|---|
| Triggers | Binary push | 37% | Google postmortem analysis, 2010–2017; reported in the 2018 Google SRE Workbook |
| Triggers | Configuration push | 31% | Google postmortem analysis, 2010–2017; reported in the 2018 Google SRE Workbook |
| Triggers | User behavior change | 9% | Google postmortem analysis, 2010–2017; reported in the 2018 Google SRE Workbook |
| Contributing categories | Software | 41.35% | Google’s categories and analysis, reported in the 2018 Google SRE Workbook |
| Contributing categories | Development process failure | 20.23% | Google’s categories and analysis, reported in the 2018 Google SRE Workbook |
| Contributing categories | Complex system behaviors | 16.90% | Google’s categories and analysis, reported in the 2018 Google SRE Workbook |
The useful lesson is methodological: a structured archive can reveal recurring triggers and broader contributing categories that are difficult to see one incident at a time. These figures do not establish that the same distribution applies to another organization, or that a particular trigger is more likely in a current environment.
What the Shakespeare Search incident reveals
Google’s Shakespeare Search postmortem shows why incident context matters when looking for recurring mechanisms. After news of a newly discovered sonnet drove a sudden traffic surge, searches for a term absent from the index activated a latent resource leak. The leak was usually infrequent enough to go unnoticed; under high load, it contributed to cascading failure. Logs showed file-descriptor exhaustion, while the timeline connected the traffic increase to mitigation and recovery (Google SRE: Example Postmortem: Shakespeare Sonnet++).
The follow-up work included fixing the leak, adding regression testing, load shedding, updating a playbook, and conducting a cascading-failure exercise. The example is useful not because every incident follows this sequence, but because it ties a trigger to latent conditions, observable evidence, impact, response, and actions.
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A trend is valuable when it changes what a team does. For each pattern worth acting on, choose an intervention that addresses the mechanism: prevent a failure class, make it easier to detect, limit its blast radius, or improve response and communication. Assign an owner and a completion target, and put the action into the team’s backlog; Google’s incident-management guidance recommends agreed completion targets for postmortem actions (Google SRE: Incident Management Guide).
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Track completion, but do not treat a finished document or closed ticket as proof that risk has fallen. Review subsequent incidents and relevant system evidence to see whether the condition persisted or changed. Google’s SRE guidance captures the principle: “You can’t ‘fix’ people, but you can fix systems and processes to better support people making the right choices when designing and maintaining complex systems” (Google SRE: Postmortem Culture: Learning from Failure).
For more on the practice, see Google’s Site Reliability Engineering book chapter on postmortem culture.
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