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"
category: engineering-core
source_repo: jeremylongshore/claude-code-plugins-plus-skills
source_path: "plugins/saas-packs/castai-pack/skills/castai-core-workflow-a/SKILL.md"
source_url: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/HEAD/plugins/saas-packs/castai-pack/skills/castai-core-workflow-a/SKILL.md
---

# 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

```bash
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

```bash
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

```hcl
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"
  }
}
```

### Step 4: Verify Autoscaler is Working

```bash
# Check if the autoscaler is processing nodes
curl -s -H "X-API-Key: ${CASTAI_API_KEY}" \
  "https://api.cast.ai/v1/kubernetes/external-clusters/${CASTAI_CLUSTER_ID}/nodes" \
  | jq '[.items[] | {name, instanceType, lifecycle, castaiManaged: .castaiManaged}]
        | group_by(.lifecycle)
        | map({lifecycle: .[0].lifecycle, count: length})'

# Expected: mix of spot and on-demand nodes
```

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Policy update returns 400 | Invalid policy JSON | Validate with `jq` before sending |
| Nodes not scaling | Policy not enabled | Verify `.enabled: true` in policy |
| Spot instances not used | Provider not configured | Add cloud provider to `spotInstances.clouds` |
| Evictor too aggressive | Low delay threshold | Increase `emptyNodes.delaySeconds` |
| Cluster limit hit | `maxCores` too low | Increase `clusterLimits.cpu.maxCores` |

## Resources

- [Autoscaler Policies](https://docs.cast.ai/docs/autoscaler-settings)
- [Node Configuration](https://docs.cast.ai/docs/node-configuration)
- [Terraform Node Templates](https://registry.terraform.io/providers/castai/castai/latest/docs/resources/node_template)

## Next Steps

For workload-level autoscaling, see `castai-core-workflow-b`.

---

**Source:** [`jeremylongshore/claude-code-plugins-plus-skills`](https://github.com/jeremylongshore/claude-code-plugins-plus-skills) → `plugins/saas-packs/castai-pack/skills/castai-core-workflow-a/SKILL.md`