Disaster Recovery Runbook

# Q1: Is the service accessible?
curl -v https://api.vapora.com/health

# Q2: How many pods are running?
kubectl get pods -n vapora

# Q3: Can we access the database?
kubectl exec -n vapora pod/<name> -- \
  surreal query "SELECT * FROM projects LIMIT 1"

# Q4: Are backups available?
aws s3 ls s3://vapora-backups/

Decision Tree:

Can access service normally?
  YES → No disaster, escalate to incident response
  NO → Continue

Can reach any pods?
  YES → Partial disaster (Level 2-3)
  NO → Likely total disaster (Level 1)

Can reach database?
  YES → Application issue, not data issue
  NO → Database issue, need restoration

Are backups accessible?
  YES → Recovery likely possible
  NO → Critical situation, activate backup locations

Step 2: Severity Assignment

Based on assessment:

# Level 1 Criteria (Critical)
- 0 pods running in vapora namespace
- Database completely unreachable
- All backup locations inaccessible
- Service down >30 minutes

# Level 2 Criteria (Major)
- <50% pods running
- Database reachable but degraded
- Primary backups inaccessible but secondary available
- Service down 5-30 minutes

# Level 3 Criteria (Minor)
- >75% pods running
- Database responsive but with errors
- Backups accessible
- Service down <5 minutes

Assignment: Level ___

If Level 1: Activate full DR plan
If Level 2: Activate partial DR plan
If Level 3: Use normal incident response

Step 3: Notify Key Personnel

# For Level 1 (Critical) DR
send_message_to = [
  "@cto",
  "@ops-manager",
  "@database-team",
  "@infrastructure-team",
  "@product-manager"
]

message = """
🔴 DISASTER DECLARED - LEVEL 1 CRITICAL

Service: VAPORA (Complete Outage)
Severity: Critical
Time Declared: [UTC]
Status: Assessing

Actions underway:
1. Activating disaster recovery procedures
2. Notifying stakeholders
3. Engaging full team

Next update: [+5 min]

/cc @all-involved
"""

post_to_slack("#incident-critical")
page_on_call_manager(urgent=true)

Disaster Scenario Procedures

Scenario 1: Complete Cluster Failure

Symptoms:

kubectl commands time out or fail
No pods running in any namespace
Nodes unreachable
All services down

Recovery Steps:

Step 1: Assess Infrastructure (5 min)

# Try basic cluster operations
kubectl cluster-info
# If: "Unable to connect to the server"

# Check cloud provider status
# AWS: Check AWS status page, check EC2 instances
# GKE: Check Google Cloud console
# On-prem: Check infrastructure team

# Determine: Is infrastructure failed or just connectivity?

Step 2: If Infrastructure Failed

Activate Secondary Infrastructure (if available):

# 1. Access backup/secondary infrastructure
export KUBECONFIG=/path/to/backup/kubeconfig

# 2. Verify it's operational
kubectl cluster-info
kubectl get nodes

# 3. Prepare for database restore
# (See: Scenario 2 - Database Recovery)

If No Secondary: Activate failover to alternate region

# 1. Contact cloud provider
# AWS: Open support case - request emergency instance launch
# GKE: Request cluster creation in different region

# 2. While infrastructure rebuilds:
# - Retrieve backups
# - Prepare restore scripts
# - Brief team on ETA

Step 3: Restore Database (See Scenario 2)

Step 4: Deploy Services

# Once infrastructure ready and database restored

# 1. Apply ConfigMaps
kubectl apply -f vapora-configmap.yaml

# 2. Apply Secrets
kubectl apply -f vapora-secrets.yaml

# 3. Deploy services
kubectl apply -f vapora-deployments.yaml

# 4. Wait for pods to start
kubectl rollout status deployment/vapora-backend -n vapora --timeout=10m

# 5. Verify health
curl http://localhost:8001/health

Step 5: Verification

# 1. Check all pods running
kubectl get pods -n vapora
# All should show: Running, 1/1 Ready

# 2. Verify database connectivity
kubectl logs deployment/vapora-backend -n vapora | tail -20
# Should show: "Successfully connected to database"

# 3. Test API
curl http://localhost:8001/api/projects
# Should return project list

# 4. Check data integrity
# Run validation queries:
SELECT COUNT(*) FROM projects;          # Should > 0
SELECT COUNT(*) FROM users;             # Should > 0
SELECT COUNT(*) FROM tasks;             # Should > 0

Scenario 2: Database Corruption/Loss

Symptoms:

Database queries return errors
Data integrity issues
Corruption detected in logs

Recovery Steps:

Step 1: Assess Database State (10 min)

# 1. Try to connect
kubectl exec -n vapora pod/surrealdb-0 -- \
  surreal sql --conn ws://localhost:8000 \
  --user root --pass "$DB_PASSWORD" \
  "SELECT COUNT(*) FROM projects"

# 2. Check for error messages
kubectl logs -n vapora pod/surrealdb-0 | tail -50 | grep -i error

# 3. Assess damage
# Is it:
# - Connection issue (might recover)
# - Data corruption (need restore)
# - Complete loss (restore from backup)

Step 2: Backup Current State (for forensics)

# Before attempting recovery, save current state

# Export what's remaining
kubectl exec -n vapora pod/surrealdb-0 -- \
  surreal export --conn ws://localhost:8000 \
  --user root --pass "$DB_PASSWORD" \
  --output /tmp/corrupted-export.sql

# Download for analysis
kubectl cp vapora/surrealdb-0:/tmp/corrupted-export.sql \
  ./corrupted-export-$(date +%Y%m%d-%H%M%S).sql

Step 3: Identify Latest Good Backup

# Find most recent backup before corruption
aws s3 ls s3://vapora-backups/database/ --recursive | sort

# Latest backup timestamp
# Should be within last hour

# Download backup
aws s3 cp s3://vapora-backups/database/2026-01-12/vapora-db-010000.sql.gz \
  ./vapora-db-restore.sql.gz

gunzip vapora-db-restore.sql.gz

Step 4: Restore Database

# Option A: Restore to same database (destructive)
# WARNING: This will overwrite current database

kubectl exec -n vapora pod/surrealdb-0 -- \
  rm -rf /var/lib/surrealdb/data.db

# Restart pod to reinitialize
kubectl delete pod -n vapora surrealdb-0
# Pod will restart with clean database

# Import backup
kubectl exec -n vapora pod/surrealdb-0 -- \
  surreal import --conn ws://localhost:8000 \
  --user root --pass "$DB_PASSWORD" \
  --input /tmp/vapora-db-restore.sql

# Wait for import to complete (5-15 minutes)

Option B: Restore to temporary database (safer)

# 1. Create temporary database pod
kubectl run -n vapora restore-test --image=surrealdb/surrealdb:latest \
  -- start file:///tmp/restore-test

# 2. Restore to temporary
kubectl cp ./vapora-db-restore.sql vapora/restore-test:/tmp/
kubectl exec -n vapora restore-test -- \
  surreal import --conn ws://localhost:8000 \
  --user root --pass "$DB_PASSWORD" \
  --input /tmp/vapora-db-restore.sql

# 3. Verify restored data
kubectl exec -n vapora restore-test -- \
  surreal sql "SELECT COUNT(*) FROM projects"

# 4. If good: Restore production
kubectl delete pod -n vapora surrealdb-0
# Wait for pod restart
kubectl cp ./vapora-db-restore.sql vapora/surrealdb-0:/tmp/
kubectl exec -n vapora surrealdb-0 -- \
  surreal import --conn ws://localhost:8000 \
  --user root --pass "$DB_PASSWORD" \
  --input /tmp/vapora-db-restore.sql

# 5. Cleanup test pod
kubectl delete pod -n vapora restore-test

Step 5: Verify Recovery

# 1. Database responsive
kubectl exec -n vapora pod/surrealdb-0 -- \
  surreal sql "SELECT COUNT(*) FROM projects"

# 2. Application can connect
kubectl logs deployment/vapora-backend -n vapora | tail -5
# Should show successful connection

# 3. API working
curl http://localhost:8001/api/projects

# 4. Data valid
# Check record counts match pre-backup
# Check no corruption in key records

Scenario 3: Configuration Corruption

Symptoms:

Application misconfigured
Pods failing to start
Wrong values in environment

Recovery Steps:

Step 1: Identify Bad Configuration

# 1. Get current ConfigMap
kubectl get configmap -n vapora vapora-config -o yaml > current-config.yaml

# 2. Compare with known-good backup
aws s3 cp s3://vapora-backups/configs/2026-01-12/configmaps.yaml .

# 3. Diff to find issues
diff configmaps.yaml current-config.yaml

Step 2: Restore Previous Configuration

# 1. Get previous ConfigMap from backup
aws s3 cp s3://vapora-backups/configs/2026-01-11/configmaps.yaml ./good-config.yaml

# 2. Apply previous configuration
kubectl apply -f good-config.yaml

# 3. Restart pods to pick up new config
kubectl rollout restart deployment/vapora-backend -n vapora
kubectl rollout restart deployment/vapora-agents -n vapora

# 4. Monitor restart
kubectl get pods -n vapora -w

Step 3: Verify Configuration

# 1. Pods should restart and become Running
kubectl get pods -n vapora
# All should show: Running, 1/1 Ready

# 2. Check pod logs
kubectl logs deployment/vapora-backend -n vapora | tail -10
# Should show successful startup

# 3. API operational
curl http://localhost:8001/health

Scenario 4: Data Center/Region Outage

Symptoms:

Entire region unreachable
Multiple infrastructure components down
Network connectivity issues

Recovery Steps:

Step 1: Declare Regional Failover

# 1. Confirm region is down
ping production.vapora.com
# Should fail

# Check status page
# Cloud provider should report outage

# 2. Declare failover
declare_failover_to_region("us-west-2")

Step 2: Activate Alternate Region

# 1. Switch kubeconfig to alternate region
export KUBECONFIG=/path/to/backup-region/kubeconfig

# 2. Verify alternate region up
kubectl cluster-info

# 3. Download and restore database
aws s3 cp s3://vapora-backups/database/latest/ . --recursive

# 4. Restore services (as in Scenario 1, Step 4)

Step 3: Update DNS/Routing

# Update DNS to point to alternate region
aws route53 change-resource-record-sets \
  --hosted-zone-id Z123456 \
  --change-batch '{
    "Changes": [{
      "Action": "UPSERT",
      "ResourceRecordSet": {
        "Name": "api.vapora.com",
        "Type": "A",
        "AliasTarget": {
          "HostedZoneId": "Z987654",
          "DNSName": "backup-region-lb.elb.amazonaws.com",
          "EvaluateTargetHealth": false
        }
      }
    }]
  }'

# Wait for DNS propagation (5-10 minutes)

Step 4: Verify Failover

# 1. DNS resolves to new region
nslookup api.vapora.com

# 2. Services accessible
curl https://api.vapora.com/health

# 3. Data intact
curl https://api.vapora.com/api/projects

Step 5: Communicate Failover

Post to #incident-critical:

✅ FAILOVER TO ALTERNATE REGION COMPLETE

Primary Region: us-east-1 (Down)
Active Region: us-west-2 (Restored)

Status:
- All services running: ✓
- Database restored: ✓
- Data integrity verified: ✓
- Partial data loss: ~30 minutes of transactions

Estimated Data Loss: 30 minutes (11:30-12:00 UTC)
Current Time: 12:05 UTC

Next steps:
- Monitor alternate region closely
- Begin investigation of primary region
- Plan failback when primary recovered

Questions? /cc @ops-team

Post-Disaster Recovery

Phase 1: Stabilization (Ongoing)

# Continue monitoring for 4 hours minimum

# Checks every 15 minutes:
✓ All pods Running
✓ API responding
✓ Database queries working
✓ Error rates normal
✓ Performance baseline

Phase 2: Root Cause Analysis

Start within 1 hour of service recovery:

Questions to answer:

1. What caused the disaster?
   - Hardware failure
   - Software bug
   - Configuration error
   - External attack
   - Human error

2. Why wasn't it detected earlier?
   - Monitoring gap
   - Alert misconfiguration
   - Alert fatigue

3. How did backups perform?
   - Were they accessible?
   - Restore time as expected?
   - Data loss acceptable?

4. What took longest in recovery?
   - Finding backups
   - Restoring database
   - Redeploying services
   - Verifying integrity

5. What can be improved?
   - Faster detection
   - Faster recovery
   - Better documentation
   - More automated recovery

Phase 3: Recovery Documentation

Create post-disaster report:

Timeline:
- 11:30 UTC: Disaster detected
- 11:35 UTC: Database restore started
- 11:50 UTC: Services redeployed
- 12:00 UTC: All systems operational
- Duration: 30 minutes

Impact:
- Users affected: [X]
- Data lost: [X] transactions
- Revenue impact: $[X]

Root cause: [Description]

Contributing factors:
1. [Factor 1]
2. [Factor 2]

Preventive measures:
1. [Action] by [Owner] by [Date]
2. [Action] by [Owner] by [Date]

Lessons learned:
1. [Lesson 1]
2. [Lesson 2]

Phase 4: Improvements Implementation

Due date: Within 2 weeks

Checklist for improvements:

□ Update backup strategy (if needed)
□ Improve monitoring/alerting
□ Automate more recovery steps
□ Update runbooks with learnings
□ Train team on new procedures
□ Test improved procedures
□ Document for future reference
□ Incident retrospective meeting

Disaster Recovery Drill

Quarterly DR Drill

Purpose: Test DR procedures before real disaster

Schedule: Last Friday of each quarter at 02:00 UTC

def quarterly_dr_drill [] {
  print "=== QUARTERLY DISASTER RECOVERY DRILL ==="
  print $"Date: (date now | format date %Y-%m-%d %H:%M:%S UTC)"
  print ""

  # 1. Simulate database corruption
  print "1. Simulating database corruption..."
  # Create test database, introduce corruption

  # 2. Test restore procedure
  print "2. Testing restore from backup..."
  # Download backup, restore to test database

  # 3. Measure restore time
  let start_time = (date now)
  # ... restore process ...
  let end_time = (date now)
  let duration = $end_time - $start_time
  print $"Restore time: ($duration)"

  # 4. Verify data integrity
  print "3. Verifying data integrity..."
  # Check restored data matches pre-backup

  # 5. Document results
  print "4. Documenting results..."
  # Record in DR drill log

  print ""
  print "Drill complete"
}

Drill Checklist

Pre-Drill (1 week before):
□ Notify team of scheduled drill
□ Plan specific scenario to test
□ Prepare test environment
□ Have runbooks available

During Drill:
□ Execute scenario as planned
□ Record actual timings
□ Document any issues
□ Note what went well
□ Note what could improve

Post-Drill (within 1 day):
□ Debrief meeting
□ Review recorded times vs. targets
□ Discuss improvements
□ Update runbooks if needed
□ Thank team for participation
□ Document lessons learned

Post-Drill (within 1 week):
□ Implement identified improvements
□ Test improvements
□ Verify procedures updated
□ Archive drill documentation

Disaster Recovery Readiness

Recovery Readiness Checklist

Infrastructure:
□ Primary region configured
□ Backup region prepared
□ Load balancing configured
□ DNS failover configured

Data:
□ Hourly database backups
□ Backups encrypted
□ Backups tested (monthly)
□ Multiple backup locations

Configuration:
□ ConfigMaps backed up (daily)
□ Secrets encrypted and backed up
□ Infrastructure code in Git
□ Deployment manifests versioned

Documentation:
□ Disaster procedures documented
□ Runbooks current and tested
□ Team trained on procedures
□ Escalation paths clear

Testing:
□ Monthly restore test passes
□ Quarterly DR drill scheduled
□ Recovery times meet RTO/RPA

Monitoring:
□ Alerts for backup failures
□ Backup health checks running
□ Recovery procedures monitored

RTO/RPA Targets

Scenario	RTO	RPA
Single pod failure	5 min	0 min
Database corruption	1 hour	1 hour
Node failure	15 min	0 min
Region outage	2 hours	15 min
Complete cluster loss	4 hours	1 hour

Disaster Recovery Contacts

Role: Contact: Phone: Slack:
Primary DBA: [Name] [Phone] @[slack]
Backup DBA: [Name] [Phone] @[slack]
Infra Lead: [Name] [Phone] @[slack]
Backup Infra: [Name] [Phone] @[slack]
CTO: [Name] [Phone] @[slack]
Ops Manager: [Name] [Phone] @[slack]

Escalation:
Level 1: [Name] - notify immediately
Level 2: [Name] - notify within 5 min
Level 3: [Name] - notify within 15 min

Quick Reference: Disaster Steps

1. ASSESS (First 5 min)
   - Determine disaster severity
   - Assess damage scope
   - Get backup location access

2. COMMUNICATE (Immediately)
   - Declare disaster
   - Notify key personnel
   - Start status updates (every 5 min)

3. RECOVER (Next 30-120 min)
   - Activate backup infrastructure if needed
   - Restore database from latest backup
   - Redeploy applications
   - Verify all systems operational

4. VERIFY (Continuous)
   - Check pod health
   - Verify database connectivity
   - Test API endpoints
   - Monitor error rates

5. STABILIZE (Next 4 hours)
   - Monitor closely
   - Watch for anomalies
   - Verify performance normal
   - Check data integrity

6. INVESTIGATE (Within 1 hour)
   - Root cause analysis
   - Document what happened
   - Plan improvements
   - Update procedures

7. IMPROVE (Within 2 weeks)
   - Implement improvements
   - Test improvements
   - Update documentation
   - Train team

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