Postmortem Writing

Comprehensive guide to writing effective, blameless postmortems that drive organizational learning and prevent incident recurrence.

When to Use This Skill

• Conducting post-incident reviews
• Writing postmortem documents
• Facilitating blameless postmortem meetings
• Identifying root causes and contributing factors
• Creating actionable follow-up items
• Building organizational learning culture

Core Concepts

1. Blameless Culture

2. Postmortem Triggers

• SEV1 or SEV2 incidents
• Customer-facing outages > 15 minutes
• Data loss or security incidents
• Near-misses that could have been severe
• Novel failure modes
• Incidents requiring unusual intervention

Quick Start

Postmortem Timeline

Day 0: Incident occurs
Day 1-2: Draft postmortem document
Day 3-5: Postmortem meeting
Day 5-7: Finalize document, create tickets
Week 2+: Action item completion
Quarterly: Review patterns across incidents

Templates and detailed worked examples

Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.

Template 2: 5 Whys Analysis

# 5 Whys Analysis: [Incident]

## Problem Statement

Payment service experienced 47-minute outage due to database connection exhaustion.

## Analysis

### Why #1: Why did the service fail?

**Answer**: Database connections were exhausted, causing all new requests to fail.

**Evidence**: Metrics showed connection count at 100/100 (max), with 500+ pending requests.

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### Why #2: Why were database connections exhausted?

**Answer**: Each incoming request opened a new database connection instead of using the connection pool.

**Evidence**: Code diff shows direct `DriverManager.getConnection()` instead of pooled `DataSource`.

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### Why #3: Why did the code bypass the connection pool?

**Answer**: A developer refactored the repository class and inadvertently changed the connection acquisition method.

**Evidence**: PR #1234 shows the change, made while fixing a different bug.

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### Why #4: Why wasn't this caught in code review?

**Answer**: The reviewer focused on the functional change (the bug fix) and didn't notice the infrastructure change.

**Evidence**: Review comments only discuss business logic.

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### Why #5: Why isn't there a safety net for this type of change?

**Answer**: We lack automated tests that verify connection pool behavior and lack documentation about our connection patterns.

**Evidence**: Test suite has no tests for connection handling; wiki has no article on database connections.

## Root Causes Identified

1. **Primary**: Missing automated tests for infrastructure behavior
2. **Secondary**: Insufficient documentation of architectural patterns
3. **Tertiary**: Code review checklist doesn't include infrastructure considerations

## Systemic Improvements

| Root Cause    | Improvement                       | Type       |
| ------------- | --------------------------------- | ---------- |
| Missing tests | Add infrastructure behavior tests | Prevention |
| Missing docs  | Document connection patterns      | Prevention |
| Review gaps   | Update review checklist           | Detection  |
| No canary     | Implement canary deployments      | Mitigation |

Template 3: Quick Postmortem (Minor Incidents)

# Quick Postmortem: [Brief Title]

**Date**: 2024-01-15 | **Duration**: 12 min | **Severity**: SEV3

## What Happened

API latency spiked to 5s due to cache miss storm after cache flush.

## Timeline

- 10:00 - Cache flush initiated for config update
- 10:02 - Latency alerts fire
- 10:05 - Identified as cache miss storm
- 10:08 - Enabled cache warming
- 10:12 - Latency normalized

## Root Cause

Full cache flush for minor config update caused thundering herd.

## Fix

- Immediate: Enabled cache warming
- Long-term: Implement partial cache invalidation (ENG-999)

## Lessons

Don't full-flush cache in production; use targeted invalidation.

Facilitation Guide

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