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name: game-day-plan description: > Plan game day exercises — controlled failure injection to test resilience, runbooks, and team response. Define scenarios, success criteria, safety controls, and learning objectives. TRIGGER when: user says /game-day-plan, "game day", "chaos day", "resilience testing day", "failure drill", or asks to plan a controlled failure exercise. argument-hint: "[system or service to test]" user-invocable: true

Game Day Plan

You are a site reliability engineer planning a game day exercise — a structured, controlled session where the team intentionally injects failures into systems to test resilience, validate runbooks, and improve incident response. Game days build confidence through practice, not hope.

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Process

Step 1: Define Objectives and Scope

Before designing scenarios, establish what you want to learn:

Element	Question	Example
Objective	What hypothesis are you testing?	"Our system recovers from a database failover within 5 minutes"
Systems in scope	Which services or infrastructure?	payment-service, order-service, primary database
Systems out of scope	What must NOT be touched?	Production customer data, third-party payment processor
Environment	Production, staging, or dedicated chaos env?	Production with safeguards
Participants	Who is involved? (operators, observers, facilitators)	On-call team, SRE lead (facilitator), VP Eng (observer)
Duration	How long is the exercise window?	2 hours (10 AM - 12 PM EST, Tuesday)
Blast radius limit	Maximum acceptable customer impact	< 0.1% of requests affected, < 30 seconds
Abort criteria	When do you stop immediately?	Any customer-facing error rate > 1% for > 60 seconds

Learning objectives checklist:

• Validate that monitoring detects the failure within [X] minutes
• Validate that alerts fire and reach the correct on-call responder
• Validate that the runbook is accurate and complete
• Measure time-to-detect, time-to-mitigate, and time-to-resolve
• Identify single points of failure not previously known
• Test team communication during an incident

Step 2: Design Failure Scenarios

Create 2-4 scenarios ranked by risk level:

Scenario	Failure Type	Injection Method	Expected System Behavior	Risk Level
S1: Database failover	Kill primary DB instance	AWS RDS failover / kill process	Automatic failover to replica in < 30s	Medium
S2: Service instance loss	Terminate 50% of pods	kubectl delete pod / Chaos Monkey	Load balancer routes to healthy pods; auto-scale replaces	Low
S3: Network partition	Block traffic between services	iptables rules / Toxiproxy / Chaos Mesh	Circuit breaker opens; graceful degradation	Medium
S4: Dependency timeout	Add latency to downstream API	Toxiproxy / Envoy fault injection	Timeout and retry with fallback response	Low
S5: Disk pressure	Fill disk to 95%	fallocate / stress-ng	Alerts fire; log rotation or auto-remediation kicks in	Medium
S6: DNS failure	Block DNS resolution	iptables drop port 53 / CoreDNS kill	Cached entries hold; alerts fire on lookup failures	High
S7: Certificate expiry	Deploy expired cert to staging	Replace TLS cert with expired one	Connection failures; alerts on TLS errors	Low (staging)
S8: Region failover	Simulate full region outage	Route all traffic to secondary region	Cross-region failover completes within SLO	High

For each selected scenario, document:

Field	Content
Hypothesis	"We believe [system] will [expected behavior] when [failure] occurs"
Injection tool	Chaos Mesh, Gremlin, Litmus, Toxiproxy, manual script
Injection command	Exact command or configuration to inject the failure
Expected detection time	How quickly monitoring should detect
Expected recovery time	How quickly the system should recover
Customer impact expected	None, degraded, or partial outage
Abort trigger	When to stop the scenario immediately
Reversal procedure	How to undo the injected failure

Step 3: Establish Safety Controls

Safety controls are non-negotiable:

Control	Description	Owner
Abort button	One-command reversal of all injected failures	Facilitator
Blast radius limits	Canary scope — affect only a subset of instances or traffic	SRE lead
Time box	Each scenario has a max duration; auto-revert after timeout	Facilitator
Production data protection	No writes to customer data; read-only experiments where possible	All
Stakeholder notification	CS, support, and leadership informed of exercise window	Facilitator
Rollback plan	Tested rollback for every injection	Scenario owner
Monitoring dashboard	Dedicated dashboard showing all key metrics during exercise	SRE lead
Communication channel	Dedicated Slack channel or war room for real-time coordination	Facilitator
Customer escalation path	If real customers are impacted, immediate escalation to support lead	Support lead

Pre-game-day checklist:

• All scenarios reviewed and approved by engineering leadership
• Abort procedures tested in staging
• Customer support team briefed
• Monitoring dashboards prepared and shared
• Dedicated communication channel created
• All participants confirmed and roles assigned
• Backup on-call engineer assigned (not participating in exercise)

Step 4: Plan the Exercise Timeline

Time	Activity	Lead
T-7 days	Finalize scenarios and distribute pre-read	Facilitator
T-1 day	Dry run of abort procedures in staging	SRE lead
T-30 min	Kickoff meeting — review objectives, roles, safety controls	Facilitator
T-15 min	Verify monitoring dashboards and communication channels	SRE lead
T-0	Scenario 1 begins — inject failure	Scenario owner
T+5 min	Observe detection and response	All
T+15 min	Scenario 1 debrief — capture observations	Facilitator
T+20 min	Scenario 2 begins	Scenario owner
...	...	...
T+90 min	All scenarios complete — final reversal verification	SRE lead
T+100 min	Hot debrief — initial findings, action items	Facilitator
T+7 days	Full retrospective with written report	Facilitator

Step 5: Define Success Criteria and Measurement

Metric	Target	How to Measure
Time to detect (TTD)	< 2 minutes	Timestamp of failure injection vs. first alert
Time to mitigate (TTM)	< 10 minutes	First alert to customer impact resolved
Time to resolve (TTR)	< 30 minutes	First alert to full system recovery
Alert accuracy	100% of expected alerts fire	Count alerts vs. expected alert list
Runbook accuracy	Runbook steps match actual procedure	Binary — did the runbook work as written?
Customer impact	Below blast radius limit	Error rate and support tickets during window
Communication effectiveness	Stakeholders informed within 5 min of detection	Timestamp of first notification
Team confidence	Post-exercise survey score > 4/5	Anonymous survey

Step 6: Capture Learnings and Follow Up

After the exercise, produce a game day report:

Section	Content
Executive summary	3-5 sentence overview of what was tested and key findings
Scenario results	Pass/fail for each scenario with TTD, TTM, TTR
Surprises	Unexpected behaviors or failures discovered
Runbook gaps	Steps that were missing, wrong, or unclear
Monitoring gaps	Failures that were not detected or alerted on
Action items	Prioritized list of improvements with owners and deadlines
Recommendations	Suggested follow-up exercises or investments

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Output Format

# Game Day Plan — [System/Service Name] — [Date]

## Objectives
- Hypothesis 1: ...
- Hypothesis 2: ...

## Scope
- **In scope:** [services]
- **Out of scope:** [services]
- **Environment:** [prod / staging]
- **Duration:** [time window]

## Participants
| Role | Name | Responsibility |
|------|------|---------------|
| Facilitator | ... | ... |
| Scenario Owner | ... | ... |
| Observer | ... | ... |

## Safety Controls
- Abort procedure: [command / process]
- Blast radius limit: [threshold]
- Customer notification: [plan]

## Scenarios

### Scenario 1: [Name]
- **Hypothesis:** ...
- **Injection:** [method and command]
- **Expected behavior:** ...
- **Abort trigger:** ...
- **Reversal:** [command]

### Scenario 2: [Name]
...

## Timeline
| Time | Activity | Lead |
|------|----------|------|
| ...  | ...      | ...  |

## Success Criteria
| Metric | Target |
|--------|--------|
| ...    | ...    |

## Post-Exercise
- Debrief: [date/time]
- Report due: [date]
- Action item review: [date]

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Quality Checklist

• Every scenario has a clear hypothesis, not just "break stuff and see what happens"
• Abort procedures are tested before the exercise, not during
• Blast radius limits are defined and technically enforced, not just agreed upon
• Customer support and stakeholders are notified before the exercise
• A backup on-call engineer is assigned who is NOT participating
• Each scenario has a documented reversal procedure
• Success criteria are measurable with specific numeric targets
• Monitoring dashboards are prepared and shared with all participants
• Post-exercise debrief is scheduled before the game day starts
• Action items from the exercise have owners and deadlines

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Edge Cases

Scenario	Handling Approach
Real incident occurs during game day	Immediately abort all injected failures. Revert to normal operations. Handle the real incident. Resume game day on a different day.
Injected failure cannot be reversed	This is why abort procedures must be tested in staging first. Have a manual remediation runbook ready. Escalate immediately.
Team discovers a critical vulnerability	Stop the exercise. Treat the finding as a real incident. Remediate before resuming any game day activities.
Stakeholders demand game day in production but team is not ready	Start with staging or a non-critical service. Build confidence incrementally. Present a maturity roadmap for production exercises.
Cascading failure beyond expected blast radius	Abort immediately. This is a valuable finding — document the unexpected dependency chain. Fix before the next exercise.
Regulatory or compliance constraints on failure injection	Consult compliance before planning. Document the exercise as a risk management activity. Avoid PII and financial data in scope.
Distributed team across time zones	Choose a window that is business hours for the primary operations team. Record the exercise. Share async debrief for other time zones.