castai-core-workflow-a

name	castai-core-workflow-a
description	Configure CAST AI autoscaler policies and node templates for cost optimization. Use when enabling Phase 2 automation, setting spot instance policies, or configuring node downscaler and evictor settings. Trigger with phrases like "cast ai autoscaler", "cast ai policies", "cast ai spot instances", "cast ai node optimization".
allowed-tools	Read, Write, Edit, Bash(curl:*), Bash(kubectl:*), Grep
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","kubernetes","cost-optimization","castai"]
compatible-with	claude-code

CAST AI Core Workflow: Autoscaler & Policies

Overview

Primary workflow for CAST AI: configure autoscaler policies to optimize cluster costs. Covers enabling spot instances, configuring the node downscaler and evictor, setting cluster CPU/memory limits, and creating node templates for workload-specific requirements.

Prerequisites

• Completed castai-install-auth with Phase 2 (cluster controller + evictor)
• CASTAI_API_KEY and CASTAI_CLUSTER_ID set
• Cluster in "ready" status

Instructions

Step 1: Read Current Policies

curl -s -H "X-API-Key: ${CASTAI_API_KEY}" \
  "https://api.cast.ai/v1/kubernetes/clusters/${CASTAI_CLUSTER_ID}/policies" \
  | jq .

Step 2: Enable Cost-Optimized Autoscaling

curl -X PUT -H "X-API-Key: ${CASTAI_API_KEY}" \
  -H "Content-Type: application/json" \
  "https://api.cast.ai/v1/kubernetes/clusters/${CASTAI_CLUSTER_ID}/policies" \
  -d '{
    "enabled": true,
    "unschedulablePods": {
      "enabled": true,
      "headroom": {
        "cpuPercentage": 10,
        "memoryPercentage": 10,
        "enabled": true
      }
    },
    "nodeDownscaler": {
      "enabled": true,
      "emptyNodes": {
        "enabled": true,
        "delaySeconds": 180
      }
    },
    "spotInstances": {
      "enabled": true,
      "clouds": ["aws"],
      "spotDiversityEnabled": true,
      "spotDiversityPriceIncreaseLimitPercent": 20
    },
    "clusterLimits": {
      "enabled": true,
      "cpu": {
        "minCores": 4,
        "maxCores": 100
      }
    }
  }'

Step 3: Configure Node Templates via Terraform

resource "castai_node_template" "spot_workers" {
  cluster_id = castai_eks_cluster.this.id
  name       = "spot-workers"
  is_default = false
  is_enabled = true

  constraints {
    min_cpu               = 2
    max_cpu               = 16
    min_memory            = 4096
    max_memory            = 65536
    spot                  = true
    use_spot_fallbacks    = true
    fallback_restore_rate_seconds = 600

    instance_families {
      include = ["m5", "m6i", "c5", "c6i", "r5", "r6i"]
    }

    architectures = ["amd64"]
  }

  custom_labels = {
    "workload-type" = "batch"
  }
}

resource "castai_node_template" "gpu_ondemand" {
  cluster_id = castai_eks_cluster.this.id
  name       = "gpu-ondemand"
  is_default = false
  is_enabled = true

  constraints {
    spot                  = false
    gpu_manufacturers     = ["NVIDIA"]

    instance_families {
      include = ["p3", "p4d", "g4dn", "g5"]
    }
  }

  custom_labels = {
    "workload-type" = "gpu"
  }
}