postmortem-writing

SKILL.md 节选

# 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

| Blame-Focused | Blameless |
|---------------|-----------|
| "Who caused this?" | "What conditions allowed this?" |
| "Someone made a mistake" | "The system allowed this mistake" |
| Punish individuals | Improve systems |
| Hide information | Share learnings |
| Fear of speaking up | Psychological safety |

### 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

### Template 1: Standard Postmortem

```markdown
# Postmortem: [Incident Title]

**Date**: 2024-01-15
**Authors**: @alice, @bob
**Status**: Draft | In Review | Final
**Incident Severity**: SEV2
**Incident Duration**: 47 minutes

## Executive Summary

On January 15, 2024, the payment processing service experienced a 47-minute outage affecting approximately 12,000 customers. The root cause was a database connection pool exhaustion triggered by a configuration change in deployment v2.3.4. The incident was resolved by rolling back to v2.3.3 and increasing connection pool limits.

**Impact**:
- 12,000 customers unable to complete purchases
- Estimated revenue loss: $45,000
- 847 support tickets created
- No data loss or security implications

## Timeline (All times UTC)

| Time | Event |
|------|-------|
| 14:23 | Deployment v2.3.4 completed to production |
| 14:31 | First alert: `payment_error_rate > 5%` |
| 14:33 | On-call engineer @alice acknowledges alert |
| 14:35 | Initial investigation begins, error rate at 23% |
| 14:41 | Incident declared SEV2, @bob joins |
| 14:45 | Database connection exhaustion identified |
| 14:52 | Decision to rollback deployment |
| 14:58 | Rollback to v2.3.3 initiated |
| 15:10 | Rollback complete, error rate dropping |
| 15:18 | Service fully recovered, incident resolved |

## Root Cause Analysis

### What Happened

The v2.3.4 deployment included a change to the database query pattern that inadvertently removed connection pooling for a frequently-called endpoint. Each request opened a new database connection instead of reusing pooled connections.

### Why It Happened

1. **Proximate Cause**: Code change in `PaymentRepository.java` replaced pooled `DataSource` with direct `DriverManager.getConnection()` calls.

2. **Contributing Factors**:
   - Code review did not catch the connection handling change
   - No integration tests specifically for connection pool behavior
   - Staging environment has lower traffic, masking the issue
   - Database connection metrics alert threshold was too high (90%)

3. **5 Whys Analysis**:
   - Why did the service fail? → Database connections exhausted
   - Why were connections exhausted? → Each request opened new connection
   - Why did each request open new connection? → Code bypassed connection pool
   - Why did code bypass connection pool? → Developer unfamiliar with codebase patterns
   - Why was developer unfamiliar? → No documentation on connection management patterns

### System Diagram

```
[Client] → [Load Balancer] → [Payment Service] → [Database]
                                    ↓
                            Connection Pool (broken)
                                    ↓
                            Direct connections (cause)
```

## Detection

### What Worked

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