On Call Handoff Patterns

Mode: Cognitive/Prompt-Driven — No standalone utility script; use via agent context.

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

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

• Runbooks
• Service Catalog
• Incident Slack
• PagerDuty

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

## Resources

- Incident channel: #inc-20240122-payment
- Dashboard: [Payment Service](https://grafana/d/payments)
- Runbook: [Payment Degradation](https://wiki/runbooks/payments)

---

**Incoming on-call (@bob) - Please confirm you have:**

- [ ] Joined #inc-20240122-payment
- [ ] Access to dashboards
- [ ] Understand current state
- [ ] Know escalation path

Handoff Sync Meeting

Agenda (15 minutes)

## Handoff Sync: @alice → @bob

1. **Active Issues** (5 min)
   - Walk through any ongoing incidents
   - Discuss investigation status
   - Transfer context and theories

2. **Recent Changes** (3 min)
   - Deployments to watch
   - Config changes
   - Known regressions

3. **Upcoming Events** (3 min)
   - Maintenance windows
   - Expected traffic changes
   - Releases planned

4. **Questions** (4 min)
   - Clarify anything unclear
   - Confirm access and alerting
   - Exchange contact info

On-Call Best Practices

Before Your Shift

## Pre-Shift Checklist

### Access Verification

- [ ] VPN working
- [ ] kubectl access to all clusters
- [ ] Database read access
- [ ] Log aggregator access (Splunk/Datadog)
- [ ] PagerDuty app installed and logged in

### Alerting Setup

- [ ] PagerDuty schedule shows you as primary
- [ ] Phone notifications enabled
- [ ] Slack notifications for incident channels
- [ ] Test alert received and acknowledged

### Knowledge Refresh

- [ ] Review recent incidents (past 2 weeks)
- [ ] Check service changelog
- [ ] Skim critical runbooks
- [ ] Know escalation contacts

### Environment Ready

- [ ] Laptop charged and accessible
- [ ] Phone charged
- [ ] Quiet space available for calls
- [ ] Secondary contact identified (if traveling)

During Your Shift

## Daily On-Call Routine

### Morning (start of day)

- [ ] Check overnight alerts
- [ ] Review dashboards for anomalies
- [ ] Check for any P0/P1 tickets created
- [ ] Skim incident channels for context

### Throughout Day

- [ ] Respond to alerts within SLA
- [ ] Document investigation progress
- [ ] Update team on significant issues
- [ ] Triage incoming pages

### End of Day

- [ ] Hand off any active issues
- [ ] Update investigation docs
- [ ] Note anything for next shift

After Your Shift

## Post-Shift Checklist

- [ ] Complete handoff document
- [ ] Sync with incoming on-call
- [ ] Verify PagerDuty routing changed
- [ ] Close/update investigation tickets
- [ ] File postmortems for any incidents
- [ ] Take time off if shift was stressful

Escalation Guidelines

When to Escalate

## Escalation Triggers

### Immediate Escalation

- SEV1 incident declared
- Data breach suspected
- Unable to diagnose within 30 min
- Customer or legal escalation received

### Consider Escalation

- Issue spans multiple teams
- Requires expertise you don't have
- Business impact exceeds threshold
- You're uncertain about next steps

### How to Escalate

1. Page the appropriate escalation path
2. Provide brief context in Slack
3. Stay engaged until escalation acknowledges
4. Hand off cleanly, don't just disappear

Best Practices

Do's

• Document everything - Future you will thank you
• Escalate early - Better safe than sorry
• Take breaks - Alert fatigue is real
• Keep handoffs synchronous - Async loses context
• Test your setup - Before incidents, not during

Don'ts

• Don't skip handoffs - Context loss causes incidents
• Don't hero - Escalate when needed
• Don't ignore alerts - Even if they seem minor
• Don't work sick - Swap shifts instead
• Don't disappear - Stay reachable during shift

Resources

• Google SRE - Being On-Call
• PagerDuty On-Call Guide
• Increment On-Call Issue

Iron Laws

1. ALWAYS write a handoff document before ending a shift — sync calls alone are insufficient; spoken context is forgotten within hours; the document is the durable record the incoming engineer can return to at 3am.
2. NEVER skip the sync call for on-call handoffs — async-only handoffs lose nuance, tone, and the ability to answer questions; 15 minutes of overlap prevents hours of confusion for the incoming engineer.
3. ALWAYS escalate within 30 minutes of being stuck on an incident — spending hours debugging alone delays resolution and exhausts the on-call engineer; escalation is a sign of good judgment, not weakness.
4. NEVER skip verification of alerting setup before a shift begins — discovering a misconfigured PagerDuty routing during an active incident is too late; test the full alert path before every shift.
5. ALWAYS document every open investigation with explicit next steps — handing off without next steps forces the incoming engineer to restart from zero; written action items reduce handoff ramp-up from hours to minutes.

Anti-Patterns

Memory Protocol (MANDATORY)

Before starting: Read .claude/context/memory/learnings.md

After completing:

• New pattern -> .claude/context/memory/learnings.md
• Issue found -> .claude/context/memory/issues.md
• Decision made -> .claude/context/memory/decisions.md

ASSUME INTERRUPTION: If it's not in memory, it didn't happen.