Agent skill

castai-core-workflow-b

Configure CAST AI Workload Autoscaler for pod-level right-sizing and VPA. Use when enabling workload autoscaling, configuring resource recommendations, or tuning pod CPU and memory requests with CAST AI. Trigger with phrases like "cast ai workload autoscaler", "cast ai pod sizing", "cast ai resource recommendations", "cast ai VPA".

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Install this agent skill to your Project

npx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/castai-pack/skills/castai-core-workflow-b

SKILL.md

CAST AI Core Workflow: Workload Autoscaler

Overview

CAST AI Workload Autoscaler right-sizes pod resource requests based on actual usage, reducing over-provisioning without manual VPA tuning. This skill covers enabling the workload autoscaler, configuring scaling policies per workload, and using annotations for fine-grained control.

Prerequisites

  • Completed castai-core-workflow-a (cluster-level policies)
  • CAST AI agent v1.60+ installed
  • Workload Autoscaler enabled in CAST AI console

Instructions

Step 1: Install Workload Autoscaler Components

bash
helm upgrade --install castai-workload-autoscaler \
  castai-helm/castai-workload-autoscaler \
  -n castai-agent \
  --set castai.apiKey="${CASTAI_API_KEY}" \
  --set castai.clusterID="${CASTAI_CLUSTER_ID}"

Step 2: Query Workload Recommendations

bash
# Get resource recommendations for a specific workload
curl -s -H "X-API-Key: ${CASTAI_API_KEY}" \
  "https://api.cast.ai/v1/workload-autoscaling/clusters/${CASTAI_CLUSTER_ID}/workloads" \
  | jq '.items[] | {
    name: .workloadName,
    namespace: .namespace,
    currentCpu: .currentCpuRequest,
    recommendedCpu: .recommendedCpuRequest,
    currentMemory: .currentMemoryRequest,
    recommendedMemory: .recommendedMemoryRequest,
    savingsPercent: .estimatedSavingsPercent
  }'

Step 3: Configure Per-Workload Policies via Annotations

yaml
# Add annotations to deployments for CAST AI workload autoscaler
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-api
  annotations:
    # Enable workload autoscaling
    autoscaling.cast.ai/enabled: "true"
    # CPU configuration
    autoscaling.cast.ai/cpu-min: "100m"
    autoscaling.cast.ai/cpu-max: "4000m"
    autoscaling.cast.ai/cpu-headroom: "15"
    # Memory configuration
    autoscaling.cast.ai/memory-min: "128Mi"
    autoscaling.cast.ai/memory-max: "8Gi"
    autoscaling.cast.ai/memory-headroom: "20"
    # Apply changes automatically vs recommendation-only
    autoscaling.cast.ai/apply-type: "immediate"
spec:
  template:
    spec:
      containers:
        - name: api
          resources:
            requests:
              cpu: "500m"      # Will be auto-adjusted by CAST AI
              memory: "512Mi"  # Will be auto-adjusted by CAST AI

Step 4: Create a Scaling Policy via API

bash
curl -X POST -H "X-API-Key: ${CASTAI_API_KEY}" \
  -H "Content-Type: application/json" \
  "https://api.cast.ai/v1/workload-autoscaling/clusters/${CASTAI_CLUSTER_ID}/policies" \
  -d '{
    "name": "cost-optimized",
    "applyType": "IMMEDIATE",
    "management": {
      "cpu": {
        "function": "QUANTILE",
        "args": { "quantile": 0.95 },
        "overhead": 0.15,
        "min": 50,
        "max": 8000
      },
      "memory": {
        "function": "MAX",
        "overhead": 0.20,
        "min": 64,
        "max": 16384
      }
    },
    "antiShrink": {
      "enabled": true,
      "cooldownSeconds": 300
    }
  }'

Step 5: Monitor Workload Scaling Events

bash
# Check scaling events
kubectl get events -n default --field-selector reason=CastAIWorkloadAutoscaled

# View current vs recommended via API
curl -s -H "X-API-Key: ${CASTAI_API_KEY}" \
  "https://api.cast.ai/v1/workload-autoscaling/clusters/${CASTAI_CLUSTER_ID}/workloads/${WORKLOAD_ID}" \
  | jq '.scalingEvents[-5:]'

Error Handling

Error Cause Solution
Workload not appearing Missing annotation Add autoscaling.cast.ai/enabled: "true"
OOMKilled after scaling Memory headroom too low Increase memory-headroom to 25+
CPU throttling CPU recommendation too aggressive Increase cpu-headroom or set higher min
No recommendations yet Insufficient data Wait 24h for usage data collection

Resources

Next Steps

For troubleshooting CAST AI errors, see castai-common-errors.

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