Kubernetes Autoscaling

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

When to Apply

Use this skill when:

• User mentions: "HPA", "VPA", "KEDA", "autoscale", "scale to zero"

• Operations: configuring autoscaling, checking scaling status

• Keywords: "scale automatically", "event-driven", "right-size"

Priority Rules

Priority Rule Impact Tools

1 Verify metrics-server for HPA CRITICAL get_resource_metrics

2 Set resource requests before HPA CRITICAL describe_pod

3 Use KEDA for scale-to-zero HIGH keda_scaledobjects_list_tool

4 Check VPA recommendations MEDIUM get_resource_recommendations

Quick Reference

Task Tool Example

List KEDA ScaledObjects keda_scaledobjects_list_tool

keda_scaledobjects_list_tool(namespace)

Get ScaledObject keda_scaledobject_get_tool

keda_scaledobject_get_tool(name, namespace)

List ScaledJobs keda_scaledjobs_list_tool

keda_scaledjobs_list_tool(namespace)

Check KEDA keda_detect_tool

keda_detect_tool()

HPA (Horizontal Pod Autoscaler)

Basic CPU-based scaling:

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:

kubectl_apply(hpa_yaml, namespace) get_hpa(namespace)

VPA (Vertical Pod Autoscaler)

Right-size resource requests:

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)

apiVersion: keda.sh/v1alpha1 kind: ScaledObject metadata: name: sqs-scaler spec: scaleTargetRef: name: queue-processor minReplicaCount: 0 maxReplicaCount: 100 triggers:

• type: aws-sqs-queue metadata: queueURL: https://sqs.region.amazonaws.com/... queueLength: "5"

Cron-Based Scaling

triggers:

• type: cron metadata: timezone: America/New_York start: 0 8 * * 1-5 end: 0 18 * * 1-5 desiredReplicas: "10"

Prometheus Metrics

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)

Right-Size with VPA

Get recommendations and apply:

get_resource_recommendations(namespace)

Troubleshooting

HPA Not Scaling

get_hpa(namespace) get_pod_metrics(name, namespace) describe_pod(name, namespace)

KEDA Not Triggering

keda_scaledobject_get_tool(name, namespace) get_events(namespace)

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

• Always Set Resource Requests - HPA requires requests to calculate utilization

• Use Multiple Metrics - Combine CPU + custom metrics for accuracy

• Stabilization Windows - Prevent flapping with scaleDown stabilization

• Scale to Zero Carefully - Consider cold start time

Related Skills

• k8s-cost - Cost optimization

• k8s-troubleshoot - Debug scaling issues