on-call-handoff-patterns
SKILL.md
On-Call Handoff Patterns
Effective patterns for on-call shift transitions, ensuring continuity, context transfer, and reliable incident response across shifts.
When to Use This Skill
- Transitioning on-call responsibilities
- Writing shift handoff summaries
- Documenting ongoing investigations
- Establishing on-call rotation procedures
- Improving handoff quality
- Onboarding new on-call engineers
Core Concepts
1. Handoff Components
| Component | Purpose |
|---|---|
| Active Incidents | What's currently broken |
| Ongoing Investigations | Issues being debugged |
| Recent Changes | Deployments, configs |
| Known Issues | Workarounds in place |
| Upcoming Events | Maintenance, releases |
2. Handoff Timing
Recommended: 30 min overlap between shifts
Outgoing:
├── 15 min: Write handoff document
└── 15 min: Sync call with incoming
Incoming:
├── 15 min: Review handoff document
├── 15 min: Sync call with outgoing
└── 5 min: Verify alerting setup
Templates
Template 1: Shift Handoff Document
# On-Call Handoff: Platform Team
**Outgoing**: @alice (2024-01-15 to 2024-01-22)
**Incoming**: @bob (2024-01-22 to 2024-01-29)
**Handoff Time**: 2024-01-22 09:00 UTC
---
## 🔴 Active Incidents
### None currently active
No active incidents at handoff time.
---
## 🟡 Ongoing Investigations
### 1. Intermittent API Timeouts (ENG-1234)
**Status**: Investigating
**Started**: 2024-01-20
**Impact**: ~0.1% of requests timing out
**Context**:
- Timeouts correlate with database backup window (02:00-03:00 UTC)
- Suspect backup process causing lock contention
- Added extra logging in PR #567 (deployed 01/21)
**Next Steps**:
- [ ] Review new logs after tonight's backup
- [ ] Consider moving backup window if confirmed
**Resources**:
- Dashboard: [API Latency](https://grafana/d/api-latency)
- Thread: #platform-eng (01/20, 14:32)
---
### 2. Memory Growth in Auth Service (ENG-1235)
**Status**: Monitoring
**Started**: 2024-01-18
**Impact**: None yet (proactive)
**Context**:
- Memory usage growing ~5% per day
- No memory leak found in profiling
- Suspect connection pool not releasing properly
**Next Steps**:
- [ ] Review heap dump from 01/21
- [ ] Consider restart if usage > 80%
**Resources**:
- Dashboard: [Auth Service Memory](https://grafana/d/auth-memory)
- Analysis doc: [Memory Investigation](https://docs/eng-1235)
---
## 🟢 Resolved This Shift
### Payment Service Outage (2024-01-19)
- **Duration**: 23 minutes
- **Root Cause**: Database connection exhaustion
- **Resolution**: Rolled back v2.3.4, increased pool size
- **Postmortem**: [POSTMORTEM-89](https://docs/postmortem-89)
- **Follow-up tickets**: ENG-1230, ENG-1231
---
## 📋 Recent Changes
### Deployments
| Service | Version | Time | Notes |
| ------------ | ------- | ----------- | -------------------------- |
| api-gateway | v3.2.1 | 01/21 14:00 | Bug fix for header parsing |
| user-service | v2.8.0 | 01/20 10:00 | New profile features |
| auth-service | v4.1.2 | 01/19 16:00 | Security patch |
### Configuration Changes
- 01/21: Increased API rate limit from 1000 to 1500 RPS
- 01/20: Updated database connection pool max from 50 to 75
### Infrastructure
- 01/20: Added 2 nodes to Kubernetes cluster
- 01/19: Upgraded Redis from 6.2 to 7.0
---
## ⚠️ Known Issues & Workarounds
### 1. Slow Dashboard Loading
**Issue**: Grafana dashboards slow on Monday mornings
**Workaround**: Wait 5 min after 08:00 UTC for cache warm-up
**Ticket**: OPS-456 (P3)
### 2. Flaky Integration Test
**Issue**: `test_payment_flow` fails intermittently in CI
**Workaround**: Re-run failed job (usually passes on retry)
**Ticket**: ENG-1200 (P2)
---
## 📅 Upcoming Events
| Date | Event | Impact | Contact |
| ----------- | -------------------- | ------------------- | ------------- |
| 01/23 02:00 | Database maintenance | 5 min read-only | @dba-team |
| 01/24 14:00 | Major release v5.0 | Monitor closely | @release-team |
| 01/25 | Marketing campaign | 2x traffic expected | @platform |
---
## 📞 Escalation Reminders
| Issue Type | First Escalation | Second Escalation |
| --------------- | -------------------- | ----------------- |
| Payment issues | @payments-oncall | @payments-manager |
| Auth issues | @auth-oncall | @security-team |
| Database issues | @dba-team | @infra-manager |
| Unknown/severe | @engineering-manager | @vp-engineering |
---
## 🔧 Quick Reference
### Common Commands
```bash
# Check service health
kubectl get pods -A | grep -v Running
# Recent deployments
kubectl get events --sort-by='.lastTimestamp' | tail -20
# Database connections
psql -c "SELECT count(*) FROM pg_stat_activity;"
# Clear cache (emergency only)
redis-cli FLUSHDB
```
Important Links
Handoff Checklist
Outgoing Engineer
- Document active incidents
- Document ongoing investigations
- List recent changes
- Note known issues
- Add upcoming events
- Sync with incoming engineer
Incoming Engineer
- Read this document
- Join sync call
- Verify PagerDuty is routing to you
- Verify Slack notifications working
- Check VPN/access working
- Review critical dashboards
### Template 2: Quick Handoff (Async)
```markdown
# Quick Handoff: @alice → @bob
## TL;DR
- No active incidents
- 1 investigation ongoing (API timeouts, see ENG-1234)
- Major release tomorrow (01/24) - be ready for issues
## Watch List
1. API latency around 02:00-03:00 UTC (backup window)
2. Auth service memory (restart if > 80%)
## Recent
- Deployed api-gateway v3.2.1 yesterday (stable)
- Increased rate limits to 1500 RPS
## Coming Up
- 01/23 02:00 - DB maintenance (5 min read-only)
- 01/24 14:00 - v5.0 release
## Questions?
I'll be available on Slack until 17:00 today.
Template 3: Incident Handoff (Mid-Incident)
# INCIDENT HANDOFF: Payment Service Degradation
**Incident Start**: 2024-01-22 08:15 UTC
**Current Status**: Mitigating
**Severity**: SEV2
---
## Current State
- Error rate: 15% (down from 40%)
- Mitigation in progress: scaling up pods
- ETA to resolution: ~30 min
## What We Know
1. Root cause: Memory pressure on payment-service pods
2. Triggered by: Unusual traffic spike (3x normal)
3. Contributing: Inefficient query in checkout flow
## What We've Done
- Scaled payment-service from 5 → 15 pods
- Enabled rate limiting on checkout endpoint
- Disabled non-critical features
## What Needs to Happen
1. Monitor error rate - should reach <1% in ~15 min
2. If not improving, escalate to @payments-manager
3. Once stable, begin root cause investigation
## Key People
- Incident Commander: @alice (handing off)
- Comms Lead: @charlie
- Technical Lead: @bob (incoming)
## Communication
- Status page: Updated at 08:45
- Customer support: Notified
- Exec team: Aware
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