google-agents-cli-scaffold
Project scaffolding, deployment configuration, and CI/CD setup for Google ADK agents.
design-on-call-rotation
Design sustainable on-call rotations with balanced schedules, clear escalation policies, fatigue management, and handoff procedures. Minimize burnout while maintaining incident response coverage. Use when setting up on-call for the first time, scaling a team from 2-3 to 5+ engineers, addressing o...
Full skill instructions
Create a sustainable on-call schedule that balances coverage with engineer well-being.
Choose rotation length based on team size:
## Rotation Models
### Weekly Rotation (5+ person team)
- **Length**: 7 days (Monday 09:00 to Monday 09:00)
- **Pros**: Predictable, easy to plan around
- **Cons**: Whole week disrupted if alerts are frequent
### 12-Hour Split (3-4 person team)
- **Day shift**: 08:00-20:00 local time
- **Night shift**: 20:00-08:00 local time
- **Pros**: Shared burden, night coverage paid differently
- **Cons**: More handoffs, coordination needed
### Follow-the-Sun (Global team)
- **APAC**: 00:00-08:00 UTC
- **EMEA**: 08:00-16:00 UTC
- **Americas**: 16:00-00:00 UTC
- **Pros**: No night shifts, timezone-aligned
- **Cons**: Requires distributed team
### Two-Tier (Senior/Junior split)
- **Primary**: Junior engineers (first responder)
- **Secondary**: Senior engineers (escalation)
- **Pros**: Training opportunity, lighter senior load
- **Cons**: Risk of junior burnout
Example schedule for 5-person team:
Week 1: Alice (Primary), Bob (Secondary)
Week 2: Charlie (Primary), Diana (Secondary)
Week 3: Eve (Primary), Alice (Secondary)
Week 4: Bob (Primary), Charlie (Secondary)
Week 5: Diana (Primary), Eve (Secondary)
Expected: Schedule that rotates fairly and provides 24/7 coverage.
On failure: If coverage gaps exist, add more engineers or reduce SLA to business hours only.
Set up tiered escalation in PagerDuty/Opsgenie:
# PagerDuty escalation policy (YAML representation)
escalation_policy:
name: "Production Services"
repeat_enabled: true
num_loops: 3
escalation_rules:
- id: primary
escalation_delay_in_minutes: 0
targets:
- type: schedule
id: primary_on_call_schedule
- id: secondary
escalation_delay_in_minutes: 15
targets:
- type: schedule
id: secondary_on_call_schedule
- id: manager
escalation_delay_in_minutes: 30
targets:
- type: user
id: engineering_manager
Create escalation flowchart:
Alert Fires
↓
Primary On-Call Paged
↓
Wait 15 minutes (no ack)
↓
Secondary On-Call Paged
↓
Wait 15 minutes (no ack)
↓
Manager Paged
↓
Repeat cycle (max 3 times)
Expected: Clear escalation path with reasonable delays.
On failure: If escalations fire too often, shorten ack windows or check alert quality.
Create a structured handoff checklist:
## On-Call Handoff Checklist
### Outgoing On-Call
- [ ] Update incident log with any ongoing issues
- [ ] Document any workarounds or known issues
- [ ] Share any alerts that are "noisy but safe to ignore" temporarily
- [ ] Note any upcoming deploys or maintenance windows
- [ ] Provide context on any flapping alerts
### Incoming On-Call
- [ ] Review incident log from previous shift
- [ ] Check for any ongoing incidents
- [ ] Verify PagerDuty/Opsgenie has correct contact info
- [ ] Test alert delivery (send test page to yourself)
- [ ] Review recent deploys and release notes
- [ ] Check capacity metrics for any concerning trends
### Handoff Meeting (15 min)
- Review any incidents from past week
- Discuss any changes to systems or runbooks
- Questions and clarifications
Automate handoff reminders:
# Slack reminder script
curl -X POST https://slack.com/api/chat.postMessage \
-H "Authorization: Bearer $SLACK_BOT_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"channel": "#on-call",
"text": "On-call handoff in 1 hour. Outgoing: @alice, Incoming: @bob. Please use the handoff checklist: https://wiki.company.com/oncall-handoff"
}'
Expected: Smooth knowledge transfer, no information loss between shifts.
On failure: If incidents recur because incoming engineer didn't know about workarounds, make handoff mandatory.
Set rules to prevent burnout:
## Fatigue Prevention Rules
### Alert Volume Limits
- **Threshold**: Max 5 pages per night (22:00-06:00)
- **Action**: If exceeded, trigger incident review next day
- **Goal**: Reduce noisy alerts that disrupt sleep
### Time Off After Major Incident
- **Rule**: If on-call handles P1 incident >2 hours overnight, they get comp time
- **Amount**: Equal to incident duration (e.g., 3-hour incident = 3 hours off)
- **Scheduling**: Must be taken within 2 weeks
### Maximum Consecutive Weeks
- **Limit**: No more than 2 consecutive weeks on-call
- **Reason**: Prevents exhaustion from extended coverage
### Minimum Rest Between Rotations
- **Cooldown**: At least 2 weeks between primary rotations
- **Exception**: Emergency coverage (requires manager approval)
### Vacation Protection
- **Rule**: No on-call during scheduled vacation
- **Process**: Mark as "Out of Office" in PagerDuty 2 weeks in advance
- **Swap**: Coordinate swap with team, update schedule
Track alert fatigue metrics:
# Alerts per on-call engineer per week
count(ALERTS{alertstate="firing"}) by (oncall_engineer)
# Nighttime pages (22:00-06:00 local)
count(ALERTS{alertstate="firing", hour_of_day>=22 or hour_of_day<6})
# Time to acknowledge (should be <5 min during business hours)
histogram_quantile(0.95, rate(alert_ack_duration_seconds_bucket[7d]))
Expected: On-call load is sustainable, engineers not chronically exhausted.
On failure: If burnout occurs despite rules, reduce alert volume or hire more engineers.
Create an on-call reference guide:
# On-Call Quick Reference
## Emergency Contacts
- **Engineering Manager**: Alice Smith, +1-555-0100
- **CTO**: Bob Johnson, +1-555-0200
- **Security Team**: [email protected], +1-555-0300
- **Cloud Provider Support**: AWS Support Case Portal
## Common Runbooks
- [Database Connection Pool Exhaustion](https://wiki/runbook-db-pool)
- [High API Latency](https://wiki/runbook-api-latency)
- [Disk Space Full](https://wiki/runbook-disk-full)
- [SSL Certificate Expiration](https://wiki/runbook-ssl-renewal)
## Access & Credentials
- **Production AWS**: SSO via company.okta.com
- **Kubernetes**: `kubectl --context production`
- **Database**: Read-only access via Bastion host
- **Secrets**: 1Password vault "On-Call Production"
## Escalation Decision Tree
- **P1 (Service Down)**: Immediate response, escalate to manager after 30min
- **P2 (Degraded)**: Response within 15min, escalate if not resolved in 1 hour
- **P3 (Warning)**: Acknowledge, resolve during business hours
- **Security Incident**: Immediately escalate to Security Team, don't investigate alone
Expected: On-call engineer can find any needed information in <2 minutes.
On failure: If engineers repeatedly ask "where is X?", centralize documentation.
Review on-call experience monthly:
## On-Call Retrospective Agenda (Monthly)
### Metrics Review (15 min)
- Total alerts: [X] (target: <50/week)
- Nighttime pages: [Y] (target: <5/week)
- Mean time to acknowledge: [Z] (target: <5 min)
- Incidents by severity: P1: [A], P2: [B], P3: [C]
### Qualitative Feedback (20 min)
- What was the most challenging incident?
- Which alerts were noisy/low-value?
- Were runbooks helpful? Which need updates?
- Any gaps in monitoring or alerting?
### Action Items (10 min)
- Fix noisy alerts identified
- Update runbooks that were incomplete
- Adjust rotation schedule if needed
- Plan alert tuning work
### Recognition (5 min)
- Shout-outs for excellent incident response
- Share learnings from interesting incidents
Track improvement over time:
# Generate monthly on-call report
cat > oncall_report_2025-02.md <<EOF
# On-Call Report: February 2025
## Key Metrics
- **Total Alerts**: 38 (down from 52 in January)
- **Nighttime Pages**: 4 (within target)
- **P1 Incidents**: 1 (database outage, 45min MTTR)
- **P2 Incidents**: 3 (all resolved <1 hour)
## Improvements Made
- Tuned CPU alert threshold (reduced false positives by 40%)
- Added runbook for Redis cache failures
- Implemented log rotation (prevented disk full alerts)
## Upcoming Changes
- Migrate to follow-the-sun rotation (Q2)
- Add Slack alert integration (in progress)
EOF
Expected: On-call experience improves month-over-month, alert volume decreases.
On failure: If metrics don't improve, escalate to leadership. May need to pause feature work to fix operational issues.
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