Kubernetes Skills

Kubernetes Autoscaling

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

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: apply_manifest(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"

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.

Queue-Based Scaling (AWS SQS)

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

• 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

• 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

StrategyToolUse CaseCPU/MemoryHPASteady traffic patternsCustom metricsHPA v2Business metricsEvent-drivenKEDAQueue processing, cronVerticalVPARight-size requestsScale to zeroKEDACost savings, idle workloads

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:
• # 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")

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

SymptomCheckResolutionHPA unknownMetrics serverInstall metrics-serverKEDA no scaleTrigger authCheck TriggerAuthenticationVPA not updatingUpdate modeSet updateMode: AutoScale down slowStabilizationAdjust 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 Use activation threshold

Related Skills

k8s-cost - Cost optimization k8s-troubleshoot - Debug scaling issues