Template preview · Software
Incident postmortem
Learn from an incident without turning the record into blame.
A blameless postmortem for a fictional service disruption.
Sample purpose
Learn from an incident without turning the record into blame.
Audience: SRE, Engineering manager- Structure
- 4 sections
- Criteria
- 16
- Sources
- 12
- Watches
- 3
- Default approach
- Review first
Set the purpose first. Then change every section, criterion, and agent setting before anything runs.
Fictional sample
Structure and criteria
Sample content shows the shape of a useful document. Copying it is optional.
01 Review firstIncident summary
State customer impact and duration plainly.
Criteria
- Gives start and end times in one format (2026-02-18T09:02Z)
- Gives the affected count or share (84 customers)
- States whether data was lost, delayed or corrupted
- Names systems, not people
Sources
- Lantern Cloud incident record (fictional) api.lantern-cloud.exampleDetection time and customer impact.
- Lantern Cloud export latency (fictional) api.lantern-cloud.exampleMetric window confirming duration.
- Google SRE: postmortem culture sre.googleBlameless framing.
Sample content
On 2026-02-18, Lantern Cloud invoice exports were delayed for 47 minutes after a queue consumer deployment. 84 fictional customers received exports late; no invoices were lost.
02 Review firstWhat happened
Reconstruct meaningful events and decisions.
Criteria
- Each event has a timestamp in one format, with no gap over 10 minutes during the incident
- Detection is separate from onset
- Recovery event is verified, e.g. test export succeeded
- Observations (alert value 45 s) are separate from guesses
Sources
- Lantern Cloud consumer logs (fictional) api.lantern-cloud.exampleRaw events during the incident.
- Lantern Cloud release record (fictional) api.lantern-cloud.exampleExact deploy time and change.
- Lantern Cloud alert archive (fictional) api.lantern-cloud.exampleWhen alerts fired and with what values.
Watches
- Follows Incident summary
Sample content
- 09:02 · DeploymentConsumer version 3.4 released.
- 09:11 · AlertQueue delay alert fired.
- 09:49 · RecoveryRollback drained backlog.
03 Review firstContributing factors
Explain conditions that made the incident more likely or harder to resolve.
Criteria
- Each factor is a condition that existed before the incident, not an action during it
- Effect ties the factor to a timeline impact (nine-minute correlation delay)
- Each factor can be fixed with a process, test or system change
- No factor names a person
Sources
- Lantern Cloud consumer rollback runbook (fictional) api.lantern-cloud.exampleWhat the rollback procedure covered.
- Lantern Cloud alert configuration (fictional) api.lantern-cloud.exampleWhether alerts carried deployment context.
- Google SRE: postmortem culture sre.googleSeparating conditions from decisions.
Watches
- Follows What happened
Sample content
Factor Effect Rollback rehearsal omitted queue backlog Team lacked a quick drain estimate. Alert lacked deployment annotation Correlation took nine minutes. 04 ManualFollow-up actions
Turn learning into owned work with verification.
Criteria
- Owner is a named person or role with authority to complete it
- Due date is a calendar date or tied milestone
- Completion evidence is testable (backlog rollback drill passes)
- Each action traces to a contributing factor
Sources
- Lantern Cloud postmortem action template (fictional) api.lantern-cloud.exampleRequired fields for tracking.
- Lantern Cloud closed actions (fictional) api.lantern-cloud.exampleWhich actions finish, to set realistic dates.
- Google SRE: postmortem culture sre.googleMaking follow-up concrete.
Watches
- Follows Contributing factors
Sample content
- ☐ Omar adds backlog rollback drill by 2026-03-12
- ☐ Tess annotates deployment alerts by 2026-03-05