Kubernetes Skills

# Kubernetes Autoscaling

Comprehensive autoscaling using HPA, VPA, and KEDA with kubectl-mcp-server tools.

Quick Reference

HPA (Horizontal Pod Autoscaler)

Basic CPU-based scaling: ```yaml apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: my-app-hpa spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: my-app minReplicas: 2 maxReplicas: 10 metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 70 ```

Apply and verify: ``` apply_manifest(hpa_yaml, namespace) get_hpa(namespace) ```

VPA (Vertical Pod Autoscaler)

Right-size resource requests: ```yaml apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: my-app-vpa spec: targetRef: apiVersion: apps/v1 kind: Deployment name: my-app updatePolicy: updateMode: "Auto" ```

KEDA (Event-Driven Autoscaling)

Detect KEDA Installation ``` keda_detect_tool() ```

List ScaledObjects ``` keda_scaledobjects_list_tool(namespace) keda_scaledobject_get_tool(name, namespace) ```

List ScaledJobs ``` keda_scaledjobs_list_tool(namespace) ```

Trigger Authentication ``` keda_triggerauths_list_tool(namespace) keda_triggerauth_get_tool(name, namespace) ```

KEDA-Managed HPAs ``` keda_hpa_list_tool(namespace) ```

See KEDA-TRIGGERS.md for trigger configurations.

Common KEDA Triggers

Queue-Based Scaling (AWS SQS) ```yaml apiVersion: keda.sh/v1alpha1 kind: ScaledObject metadata: name: sqs-scaler spec: scaleTargetRef: name: queue-processor minReplicaCount: 0 # Scale to zero! maxReplicaCount: 100 triggers: - type: aws-sqs-queue metadata: queueURL: https://sqs.region.amazonaws.com/... queueLength: "5" ```

Cron-Based Scaling ```yaml triggers: - type: cron metadata: timezone: America/New_York start: 0 8 * * 1-5 # 8 AM weekdays end: 0 18 * * 1-5 # 6 PM weekdays desiredReplicas: "10" ```

Prometheus Metrics ```yaml triggers: - type: prometheus metadata: serverAddress: http://prometheus:9090 metricName: http_requests_total query: sum(rate(http_requests_total{app="myapp"}[2m])) threshold: "100" ```

Scaling Strategies

| Strategy | Tool | Use Case | |----------|------|----------| | CPU/Memory | HPA | Steady traffic patterns | | Custom metrics | HPA v2 | Business metrics | | Event-driven | KEDA | Queue processing, cron | | Vertical | VPA | Right-size requests | | Scale to zero | KEDA | Cost savings, idle workloads |

Cost-Optimized Autoscaling

Scale to Zero with KEDA Reduce costs for idle workloads: ``` keda_scaledobjects_list_tool(namespace) # ScaledObjects with minReplicaCount: 0 can scale to zero ```

Right-Size with VPA Get recommendations and apply: ``` get_resource_recommendations(namespace) # Apply VPA recommendations ```

Predictive Scaling Use cron triggers for known patterns: ```yaml # Scale up before traffic spike triggers: - type: cron metadata: start: 0 7 * * * # 7 AM end: 0 9 * * * # 9 AM desiredReplicas: "20" ```

Multi-Cluster Autoscaling

Configure KEDA across clusters: ``` keda_scaledobjects_list_tool(namespace, context="production") keda_scaledobjects_list_tool(namespace, context="staging") ```

Troubleshooting

HPA Not Scaling ``` get_hpa(namespace) get_pod_metrics(name, namespace) # Metrics available? describe_pod(name, namespace) # Resource requests set? ```

KEDA Not Triggering ``` keda_scaledobject_get_tool(name, namespace) # Check status get_events(namespace) # Check events ```

Common Issues

| Symptom | Check | Resolution | |---------|-------|------------| | HPA unknown | Metrics server | Install metrics-server | | KEDA no scale | Trigger auth | Check TriggerAuthentication | | VPA not updating | Update mode | Set updateMode: Auto | | Scale down slow | Stabilization | Adjust stabilizationWindowSeconds |

Best Practices

1. Always Set Resource Requests
2. - HPA requires requests to calculate utilization

1. Use Multiple Metrics
2. - Combine CPU + custom metrics for accuracy

1. Stabilization Windows
2. - Prevent flapping with scaleDown stabilization

1. Scale to Zero Carefully
2. - Consider cold start time
3. - Use activation threshold

Related Skills - [k8s-cost](../k8s-cost/SKILL.md) - Cost optimization - [k8s-troubleshoot](../k8s-troubleshoot/SKILL.md) - Debug scaling issues