Postmortem Writing

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.

References

• Connection Pool Best Practices
• Deployment Runbook

### 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.

---

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.

---

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.

---

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.

---

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

### 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

### Running a Postmortem Meeting

Meeting Structure (60 minutes)

1. Opening (5 min)

• Remind everyone of blameless culture
• "We're here to learn, not to blame"
• Review meeting norms

2. Timeline Review (15 min)

• Walk through events chronologically
• Ask clarifying questions
• Identify gaps in timeline

3. Analysis Discussion (20 min)

• What failed?
• Why did it fail?
• What conditions allowed this?
• What would have prevented it?

4. Action Items (15 min)

• Brainstorm improvements
• Prioritize by impact and effort
• Assign owners and due dates

5. Closing (5 min)

• Summarize key learnings
• Confirm action item owners
• Schedule follow-up if needed

Facilitation Tips

• Keep discussion on track
• Redirect blame to systems
• Encourage quiet participants
• Document dissenting views
• Time-box tangents

## Anti-Patterns to Avoid

| Anti-Pattern            | Problem                    | Better Approach                 |
| ----------------------- | -------------------------- | ------------------------------- |
| **Blame game**          | Shuts down learning        | Focus on systems                |
| **Shallow analysis**    | Doesn't prevent recurrence | Ask "why" 5 times               |
| **No action items**     | Waste of time              | Always have concrete next steps |
| **Unrealistic actions** | Never completed            | Scope to achievable tasks       |
| **No follow-up**        | Actions forgotten          | Track in ticketing system       |

## Best Practices

### Do's

- **Start immediately** - Memory fades fast
- **Be specific** - Exact times, exact errors
- **Include graphs** - Visual evidence
- **Assign owners** - No orphan action items
- **Share widely** - Organizational learning

### Don'ts

- **Don't name and shame** - Ever
- **Don't skip small incidents** - They reveal patterns
- **Don't make it a blame doc** - That kills learning
- **Don't create busywork** - Actions should be meaningful
- **Don't skip follow-up** - Verify actions completed

postmortem-writing — templates and worked examples

Templates

Template 1: Standard Postmortem

# 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
- Error rate alert fired within 8 minutes of deployment
- Grafana dashboard clearly showed connection spike
- On-call response was swift (2 minute acknowledgment)

### What Didn't Work
- Database connection metric alert threshold too high
- No deployment-correlated alerting
- Canary deployment would have caught this earlier

### Detection Gap
The deployment completed at 14:23, but the first alert didn't fire until 14:31 (8 minutes). A deployment-aware alert could have detected the issue faster.

## Response

### What Worked
- On-call engineer quickly identified database as the issue
- Rollback decision was made decisively
- Clear communication in incident channel

### What Could Be Improved
- Took 10 minutes to correlate issue with recent deployment
- Had to manually check deployment history
- Rollback took 12 minutes (could be faster)

## Impact

### Customer Impact
- 12,000 unique customers affected
- Average impact duration: 35 minutes
- 847 support tickets (23% of affected users)
- Customer satisfaction score dropped 12 points

### Business Impact
- Estimated revenue loss: $45,000
- Support cost: ~$2,500 (agent time)
- Engineering time: ~8 person-hours

### Technical Impact
- Database primary experienced elevated load
- Some replica lag during incident
- No permanent damage to systems

## Lessons Learned

### What Went Well
1. Alerting detected the issue before customer reports
2. Team collaborated effectively under pressure
3. Rollback procedure worked smoothly
4. Communication was clear and timely

### What Went Wrong
1. Code review missed critical change
2. Test coverage gap for connection pooling
3. Staging environment doesn't reflect production traffic
4. Alert thresholds were not tuned properly

### Where We Got Lucky
1. Incident occurred during business hours with full team available
2. Database handled the load without failing completely
3. No other incidents occurred simultaneously

## Action Items

| Priority | Action | Owner | Due Date | Ticket |
|----------|--------|-------|----------|--------|
| P0 | Add integration test for connection pool behavior | @alice | 2024-01-22 | ENG-1234 |
| P0 | Lower database connection alert threshold to 70% | @bob | 2024-01-17 | OPS-567 |
| P1 | Document connection management patterns | @alice | 2024-01-29 | DOC-89 |
| P1 | Implement deployment-correlated alerting | @bob | 2024-02-05 | OPS-568 |
| P2 | Evaluate canary deployment strategy | @charlie | 2024-02-15 | ENG-1235 |
| P2 | Load test staging with production-like traffic | @dave | 2024-02-28 | QA-123 |

## Appendix

### Supporting Data

#### Error Rate Graph
[Link to Grafana dashboard snapshot]

#### Database Connection Graph
[Link to metrics]

### Related Incidents
- 2023-11-02: Similar connection issue in User Service (POSTMORTEM-42)

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