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Adds tooling and documentation for Day 2 cluster operations: - scripts/rotate-nodes.sh: interactive node-rotation driver that applies terraform to pick up the latest SSM-resolved EKS AMI and watches the rolling replacement. - scripts/demo-schema-change.sh: end-to-end demo of the zero-downtime is_favorited column migration via helm upgrade + migration hook. - scripts/verify-deployment.sh: post-deploy health check across pods, per-service HTTP health endpoints, rollout status, and PDBs. - docs/chaos-runbook.md: failure-mode playbook with simulate / Grafana / Loki / recovery steps for six scenarios (pod kill, node failure, DB pool exhaustion, inference OOM, high latency, SSL issues) plus a Loki quick-reference. - terraform/modules/eks: expose current_node_ami_id output, add update_config.max_unavailable_percentage (configurable, default 33) so node-group rolls are controlled. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
6.5 KiB
6.5 KiB
samosaChaat — Chaos Testing Runbook
This runbook covers failure scenarios for live defense. Each scenario includes how to simulate it, how to detect it via Grafana/Loki, and recovery steps.
Prerequisites
- kubectl configured for the target cluster
- Grafana accessible at https://grafana.samosachaat.art
- Loki datasource configured in Grafana
Scenario 1: Pod Crash / Kill
Simulate:
kubectl delete pod -l app.kubernetes.io/name=chat-api -n samosachaat-prod
Detect (Grafana):
- Dashboard: Application Performance → look for gap in request rate
- Alert: container restart count spike
- Panel query:
kube_pod_container_status_restarts_total{namespace="samosachaat-prod"}
Detect (Loki):
{namespace="samosachaat-prod"} | json | level="error"
{namespace="samosachaat-prod",app="chat-api"} | json | message=~".*startup.*|.*shutdown.*"
Recovery:
- Kubernetes auto-restarts the pod (restartPolicy: Always)
- HPA scales up if CPU threshold exceeded during recovery
- PDB ensures other pods kept running during the kill
- No manual action needed unless crash-looping (check logs for root cause)
Verify recovered:
kubectl get pods -n samosachaat-prod -l app.kubernetes.io/name=chat-api
curl -s https://samosachaat.art/api/health | jq .
Scenario 2: Node Failure
Simulate:
# Get a node instance ID
INSTANCE_ID=$(kubectl get nodes -o jsonpath='{.items[0].spec.providerID}' | cut -d/ -f5)
aws ec2 terminate-instances --instance-ids $INSTANCE_ID
Detect (Grafana):
- Dashboard: Node Health → node disappears from CPU/Memory panels
- Alert: HighCPU or HighMemory may fire on remaining nodes as pods redistribute
- Panel query:
kube_node_status_condition{condition="Ready",status="true"}
Detect (Loki):
{namespace="kube-system"} | json | message=~".*NotReady.*|.*node.*removed.*"
Recovery:
- EKS auto-scaling group launches a replacement node (2-5 minutes)
- Pods on the failed node are rescheduled to healthy nodes
- PDBs prevent more than 1 pod per service from being unavailable
- No manual action needed
Verify recovered:
kubectl get nodes # New node should appear with STATUS Ready
kubectl get pods -n samosachaat-prod -o wide # All pods Running
Scenario 3: Database Connection Pool Exhaustion
Simulate:
# Run a load test that exceeds the connection pool limit
kubectl run loadtest --image=busybox --restart=Never -n samosachaat-prod -- \
sh -c 'for i in $(seq 1 200); do wget -q -O- http://chat-api:8002/api/health & done; wait'
Detect (Grafana):
- Dashboard: Application Performance → spike in p99 latency, increase in 5xx errors
- Alert: High5xxRate fires
Detect (Loki):
{app=~"auth|chat-api"} | json | message=~".*connection.*pool.*|.*timeout.*|.*asyncpg.*|.*QueuePool.*overflow.*"
Recovery:
- Identify which service is affected from Loki logs
- Check current connection count:
kubectl exec deploy/chat-api -n samosachaat-prod -- python -c "..." - Restart affected pods:
kubectl rollout restart deploy/chat-api -n samosachaat-prod - If persistent: increase pool size in service config (
SQLALCHEMY_POOL_SIZEenv var) and redeploy - Check RDS max_connections:
aws rds describe-db-parameters --db-parameter-group-name default.postgres15
Scenario 4: Inference Service OOM
Simulate:
# Set a low memory limit and load a large model
kubectl set resources deploy/inference -n samosachaat-prod --limits=memory=512Mi
# Or trigger by sending many concurrent requests
Detect (Grafana):
- Dashboard: Inference Service → memory spike, then sudden drop (OOM kill)
- Dashboard: Node Health → memory spike on the node hosting inference
- Alert: HighMemory fires
Detect (Loki):
{app="inference"} | json | message=~".*OOMKilled.*|.*memory.*|.*killed.*"
# Also check events:
# kubectl get events -n samosachaat-prod --sort-by='.lastTimestamp' | grep -i oom
Recovery:
- Pod auto-restarts (but may crash-loop if model is too large for limit)
- Check what model is loaded:
curl http://inference:8003/stats - If model too large: swap to smaller model via
POST /models/swap - If limit too low: increase memory limit in values-prod.yaml and
helm upgrade - Restore original limits:
kubectl set resources deploy/inference -n samosachaat-prod --limits=memory=8Gi
Scenario 5: High Latency / Degraded Performance
Simulate:
# Flood inference with concurrent requests
kubectl run loadtest --image=curlimages/curl --restart=Never -n samosachaat-prod -- \
sh -c 'for i in $(seq 1 50); do curl -s -X POST http://chat-api:8002/api/conversations/test/messages -H "Content-Type: application/json" -d "{\"content\":\"tell me a story\"}" & done; wait'
Detect (Grafana):
- Dashboard: Application Performance → p99 latency > 5s
- Dashboard: Inference Service → worker pool utilization at 100%, queue depth growing
- Alert: HighP99Latency fires
Detect (Loki):
{app="chat-api"} | json | inference_time_ms > 5000
{app="inference"} | json | message=~".*queue.*full.*|.*timeout.*|.*worker.*busy.*"
Recovery:
- Check inference worker pool:
curl http://inference:8003/stats - If all workers busy: HPA should scale inference pods (check HPA status)
- Manual scale:
kubectl scale deploy/inference -n samosachaat-prod --replicas=5 - If single-pod bottleneck: check if model is too large for CPU inference, consider GPU nodes
- Verify recovery: watch latency dashboard return to normal
Scenario 6: SSL Certificate Issues
Detect:
- Users report "connection not secure" errors
curl -vI https://samosachaat.art 2>&1 | grep -i "expire\|ssl\|certificate"
Recovery:
- ACM certificates auto-renew — check ACM console for renewal status
- If DNS validation failed: check Route53 CNAME records match ACM requirements
terraform applyto reconcile if records drifted
Quick Reference: Diagnostic Loki Queries
# All errors across all services
{namespace="samosachaat-prod"} | json | level="error" | line_format "{{.service}}: {{.message}}"
# Trace a request across services
{namespace="samosachaat-prod"} | json | trace_id="<TRACE_ID>"
# Auth failures
{app="auth"} | json | level="error" | message=~".*oauth.*|.*jwt.*|.*unauthorized.*"
# Inference issues
{app="inference"} | json | message=~".*error.*|.*timeout.*|.*OOM.*|.*worker.*"
# Slow database queries
{app=~"auth|chat-api"} | json | message=~".*slow.*query.*|.*timeout.*"
# Recent pod restarts
{namespace="samosachaat-prod"} | json | message=~".*started.*|.*shutdown.*|.*ready.*"