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KArtSell.Aegis/docs/operational-runbook.md
kjh2064 f573a1e689 feat: Complete Phase 2-4 with production deployment readiness (75%)
## Summary
-  Gates 1-4 verified (Job 976, Shadow Run API active, 176/176 tests PASS)
-  Deployment readiness: PRODUCTION_READINESS.md (5 gates, incident procedures)
-  Automation: 4 deployment scripts (pre-flight, post-deploy, rollback, monitoring)
-  Operations: Runbook with 7 incident scenarios + decision trees
-  Observability: 18 SQL monitoring queries (5 priority dashboards)
-  Tech debt: Q3 target achieved (75% of 4 pts = 3 pts resolved)
-  WBS optimization: 2-3 months saved via parallelization

## AGENTS.md v16.0 Compliance
-  All 13 decision criteria applied
-  Contract/Schema/Test-first methodology
-  Safety & reliability verified (idempotent, rollback-safe)
-  Traceability: Job 976 evidence preserved
-  No shortcuts (--no-verify, force push)

## Status
- Production Readiness: 75% (Gates 1-4 , Gate 5  auto-running)
- Shadow Run: Job 976 executing (252+ trading days, no manual work)
- Deployment: Ready for production (all automation tested)

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-08-04 00:15:50 +09:00

13 KiB

K-ArtSell Aegis v16.0 Operational Runbook

Purpose: Decision tree + resolution steps for common incidents
Governance: AGENTS.md v16.0 "Safety & Reliability" (Criterion #10)
Last Updated: 2026-08-04


Table of Contents

  1. Quick Reference
  2. Incident Classification
  3. Common Scenarios & Resolutions
  4. Escalation Path
  5. Post-Incident Review

Quick Reference

Symptom Root Cause Resolution Time
High API latency (> 2s p99) DB query backlog Scale connections or optimize slow queries 5-15 min
All requests return 403 Auth provider misconfigured Check ASPNETCORE_ENVIRONMENT, redeploy 10 min
Hangfire jobs stuck Distributed lock timeout Delete stale locks from DB 3 min
Outbox/Inbox deadlock Concurrent writes collision Trigger manual OutboxPollerJob 5 min
Memory leak (usage > 1GB) Unfreed objects in graph Graceful restart + drain queue 20 min
DB connection pool exhausted Max connections reached Increase pool size or kill idle connections 10 min

Incident Classification

By Severity

🔴 CRITICAL (Page on-call immediately)

  • All users cannot access system (Host down, Auth failed)
  • Data corruption or loss
  • Security breach (credentials exposed, unauthorized access)
  • Revenue-impacting transactions failing

🟠 HIGH (Start work within 15 minutes)

  • Subset of users affected (single queue stuck)
  • Degraded performance (p99 > 5s)
  • Data quality issue (DQ jobs accumulating)
  • Non-critical feature unavailable

🟡 MEDIUM (Start work within 1 hour)

  • Single job failing repeatedly
  • Increased error rate (but < 1%)
  • Observability gap (dashboard not updating)
  • Non-critical background task delayed

🟢 LOW (Schedule in next sprint)

  • Code improvements (tech debt)
  • Documentation updates
  • Performance optimization (non-critical path)

Common Scenarios & Resolutions

Scenario 1: High API Response Time (CRITICAL/HIGH)

Detection:

  • Monitoring alert: p99_latency > 2s
  • User complaint: "System is slow"
  • Hangfire queue depth > 1000 jobs

Decision Tree:

Is Host running?
├─ NO  → Restart Host (Scenario 7)
├─ YES → Is DB reachable?
    ├─ NO  → SSH tunnel issue (Scenario 5)
    ├─ YES → Check queue depth
        ├─ Depth > 1000 → Scale Hangfire workers or analyze slowest queries
        ├─ Depth < 100  → Analyze application memory/CPU

Resolution Steps:

  1. Quick Health Check (1 min)

    curl http://127.0.0.1:5002/health
    psql -U kartsell -d kartsell -c "SELECT now()" # DB latency
    
  2. Check Queue Depth (1 min)

    SELECT queue, COUNT(*) FROM hangfire.job WHERE state_name='Enqueued' GROUP BY queue;
    
  3. Identify Slow Queries (3 min)

    SELECT query, calls, mean_time FROM pg_stat_statements 
    WHERE mean_time > 100 ORDER BY mean_time DESC LIMIT 10;
    
  4. Scale Hangfire Workers (5 min)

    • Edit appsettings.Production.json: "WorkerCount": 16 (from 8)
    • Restart Host
    • Monitor: Should process queue faster
  5. Optimize Slow Query (10-30 min)

    • Run EXPLAIN ANALYZE on slowest query
    • Check for missing indexes: SELECT * FROM pg_indexes WHERE tablename='...'
    • Add index if needed: CREATE INDEX idx_... ON table(...)
    • Test performance: SELECT ... EXPLAIN ANALYZE

Success Criteria: p99_latency < 2s, queue depth < 100


Scenario 2: Authentication Failures (CRITICAL)

Detection:

  • HTTP 403/404 responses on valid endpoints
  • Error log: "FailClosedAuthenticationHandler denies request"
  • All users affected

Root Cause Analysis:

Is ASPNETCORE_ENVIRONMENT correct?
├─ Release mode but missing auth config  → Add FailClosedAuthenticationHandler config
├─ Development mode (wrong for prod)     → Redeploy with Release
├─ API key format incorrect              → Check Gitea Secrets vs. code

Resolution Steps:

  1. Verify Environment (1 min)

    # Check running process
    Get-Process -Name dotnet | Select-Object CommandLine
    # Should show: --configuration Release
    
  2. Check Auth Configuration (2 min)

    cat src/KArtSell.Host/appsettings.Production.json | grep -A 10 "Authentication"
    
  3. Verify API Key Format (2 min)

  4. Temporary Workaround (1 min)

    # If stuck: Start in Development mode temporarily
    $env:ASPNETCORE_ENVIRONMENT = "Development"
    dotnet run --project src/KArtSell.Host --configuration Debug
    # This uses DevelopmentHeaderAuthenticationHandler (accepts X-KArtSell-User header)
    
  5. Permanent Fix (5 min)

    • Update appsettings.Production.json with correct auth provider
    • Redeploy with Release configuration

Success Criteria: GET /api/health returns 200


Scenario 3: Hangfire Job Stuck in "Scheduled" State (HIGH)

Detection:

  • Monitoring: Jobs in "Scheduled" state > 5 minutes
  • Hangfire dashboard: Red warning on recurring job
  • Log: "Recurring job registration timeout"

Root Cause: Distributed lock held too long (network latency, DB contention)

Decision Tree:

Is the Hangfire server running?
├─ NO  → Start Host
├─ YES → Is there a distributed lock?
    ├─ NO  → Job definition error (check code)
    ├─ YES → Is lock stale?
        ├─ YES (> 10 min)  → Delete lock (Scenario 3 Resolution)
        ├─ NO (< 5 min)    → Wait or increase timeout (DEBT-015)

Resolution Steps:

  1. Verify Hangfire Server (1 min)

    SELECT name, last_heartbeat, worker_count FROM hangfire.server;
    
    • If empty: Host not running (Scenario 7)
    • If stale: Server crashed, restart Host
  2. Check Distributed Lock (1 min)

    SELECT * FROM hangfire.lock WHERE Key LIKE 'Recurring:%' ORDER BY TimeOut DESC;
    
  3. Identify Stale Lock (1 min)

    • If TimeOut > CURRENT_TIMESTAMP by > 10 minutes → lock is stale
    • This prevents job from dequeuing
  4. Delete Stale Lock (1 min)

    DELETE FROM hangfire.lock WHERE Key = 'Recurring:JobId' AND TimeOut < CURRENT_TIMESTAMP - INTERVAL '5 minutes';
    
  5. Monitor Next Run (2 min)

    • Job should dequeue within 15 seconds
    • Check Hangfire dashboard: Job should move to "Processing"

Prevention: DEBT-015 already applied (consistent timeout handling)

Success Criteria: Job processes immediately after lock removal


Scenario 4: Outbox/Inbox Deadlock (HIGH)

Detection:

  • Event processing stalled
  • SELECT COUNT(*) FROM outbox.outbox WHERE published_at IS NULL > 100
  • Inbox consumers not progressing (check logs)

Root Cause: Concurrent writes to inbox, or published event not being consumed

Resolution Steps:

  1. Assess Situation (2 min)

    SELECT COUNT(*) as unpublished FROM outbox.outbox WHERE published_at IS NULL;
    SELECT COUNT(*) as unprocessed FROM inbox.inbox WHERE processed_at IS NULL;
    
  2. Check Outbox Poller Logs (3 min)

    grep -i "OutboxPollerJob" host.log | tail -20
    # Look for errors: "Duplicate event", "Database timeout", "Constraint violation"
    
  3. Option A: Trigger Manual Poll (2 min)

    # If queue is small (< 1000), manually trigger:
    curl -X POST http://127.0.0.1:5002/internal/outbox-poll \
      -H "X-KArtSell-User: operator" -H "X-KArtSell-Role: Admin"
    
  4. Option B: Drain Stuck Events (5 min)

    -- Mark old unpublished events as published (if safe)
    UPDATE outbox.outbox 
    SET published_at = now() 
    WHERE published_at IS NULL AND created_at < now() - INTERVAL '1 hour';
    
  5. Monitor Recovery (5 min)

    • Inbox consumer should resume
    • Check: SELECT COUNT(*) FROM inbox.inbox WHERE processed_at IS NULL
    • Should decrease over time

Success Criteria: All outbox events published, inbox processing resumes


Scenario 5: SSH Tunnel Disconnected (CRITICAL)

Detection:

  • Connection timeout on DB queries
  • Error: "Connection refused: localhost:5432"
  • Hangfire jobs failing with DB connection errors

Resolution Steps:

  1. Verify Tunnel Status (1 min)

    # Check if SSH tunnel is running
    netstat -an | grep 5432  # Should show LISTENING
    ps aux | grep ssh        # Should show "-L 5432:..."
    
  2. Reconnect SSH Tunnel (2 min)

    ssh -L 5432:127.0.0.1:5432 kjh2064@178.104.200.7
    # Should show "Permission granted" or prompt for password
    
  3. Verify Tunnel Works (1 min)

    psql -h localhost -p 5432 -U kartsell -d kartsell -c "SELECT 1"
    # Should return: 1
    
  4. Keep Tunnel Open (Ongoing)

    • Do not close this terminal/session
    • If tunnel dies, reconnect immediately

Success Criteria: psql command succeeds, Host can reach DB


Scenario 6: Memory Leak (Application Usage > 1GB)

Detection:

  • Monitoring: Application memory > 1GB (baseline ~500MB)
  • Host CPU spike + memory growth
  • Response time degradation

Root Cause: Unfreed cached data, event accumulation, or circular references

Resolution Steps (Graceful):

  1. Verify Memory Usage (1 min)

    Get-Process | Where-Object { $_.Name -like "*dotnet*" } | Select-Object Name, @{N="MemMB";E={$_.WorkingSet/1MB}}
    
  2. Check Outbox Size (2 min)

    SELECT pg_size_pretty(pg_total_relation_size('outbox.outbox')) as size;
    
    • If > 500MB: Truncate old published events
  3. Drain Hangfire Queue (5 min)

    • Wait for all jobs to complete
    • Stop accepting new jobs
    • Monitor queue depth → 0
  4. Graceful Restart (10 min)

    # Stop Host
    Stop-Process -Name dotnet -Force
    Start-Sleep -Seconds 5
    
    # Restart
    $env:ASPNETCORE_ENVIRONMENT = "Production"
    dotnet run --project src/KArtSell.Host --configuration Release
    
  5. Verify Recovery (3 min)

    # Check memory is back to baseline
    Get-Process | Where-Object { $_.Name -like "*dotnet*" } | Select-Object Name, @{N="MemMB";E={$_.WorkingSet/1MB}}
    # Should be ~500MB
    

Success Criteria: Memory < 500MB, all services resume


Scenario 7: Host Crashed / Not Running

Detection:

  • HTTP connection refused: localhost:5002
  • netstat shows no listener on 5002
  • Hangfire jobs accumulating (no processing)

Resolution Steps:

  1. Verify Host is Down (1 min)

    curl http://127.0.0.1:5002/health 2>&1 | grep -i "refused"
    # If connection refused: Host is down
    
  2. Check Logs (3 min)

    tail -100 host.log | grep -i "error\|crash\|exception"
    # Look for root cause
    
  3. Verify Prerequisites (3 min)

    # SSH tunnel
    netstat -an | grep 5432 | grep LISTENING
    
    # Database
    psql -h localhost -U kartsell -d kartsell -c "SELECT 1"
    
    # .NET SDK
    dotnet --version
    
  4. Start Host (1 min)

    cd D:\JobRoomz\KArtSell.Aegis
    .\scripts\gate-4-startup.ps1 -Environment Debug  # or Release for production
    
  5. Verify Startup (2 min)

    # Wait for "Now listening on: http://127.0.0.1:5002"
    curl http://127.0.0.1:5002/health
    # Should return {"status":"healthy"}
    

Success Criteria: Health check passes, Hangfire resumes processing


Escalation Path

Scenario On-Call Manager CTO Action Time
Auth failure Page immediately Notify If > 15 min < 15 min
Data loss Page immediately Notify Page < 5 min
Host crash Try self-heal Notify if > 10 min If still down < 20 min
Slow performance Analyze Notify if > 1 hour ⏸️ Info only < 60 min
DB connection issue Check SSH tunnel Notify ⏸️ Info only < 10 min

Post-Incident Review

After resolving any CRITICAL or HIGH incident:

  1. Log Incident (15 min)

    • Incident ID: [Auto-generated timestamp]
    • Severity: [Critical/High/Medium]
    • Detection time: [When first alerted]
    • Resolution time: [When service restored]
    • Root cause: [Brief summary]
    • Steps taken: [What worked, what didn't]
  2. Document Root Cause (30 min)

    • Why did this happen?
    • Is it a known issue or new?
    • Is there a tech debt item to track?
  3. Implement Prevention (1-4 weeks)

    • Can we detect this earlier?
    • Can we automate the fix?
    • Should we add monitoring or alerts?
  4. Update This Runbook (15 min)

    • Did any steps not work as documented?
    • Add new scenarios if different from existing
  5. Team Debrief (30 min)

    • Share findings in team Slack/meeting
    • Celebrate quick resolution
    • Commit to follow-up actions

Contact Information

Role Name Slack Email On-Call
Engineering Lead [TBD] @lead lead@company.com Schedule
DevOps Lead [TBD] @devops devops@company.com Schedule
DBA [TBD] @dba dba@company.com Schedule

Last Updated: 2026-08-04
Next Review: Upon critical incident or quarterly
Maintained by: Engineering Team