Claude-code-plugins-plus-skills castai-deploy-integration

install

source · Clone the upstream repo

git clone https://github.com/jeremylongshore/claude-code-plugins-plus-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/jeremylongshore/claude-code-plugins-plus-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/saas-packs/castai-pack/skills/castai-deploy-integration" ~/.claude/skills/jeremylongshore-claude-code-plugins-plus-skills-castai-deploy-integration && rm -rf "$T"

manifest: plugins/saas-packs/castai-pack/skills/castai-deploy-integration/SKILL.md

CAST AI Deploy Integration

Overview

Deploy CAST AI to EKS, GKE, and AKS clusters using official Terraform modules. Each cloud provider has a dedicated CAST AI module that handles IAM roles, node configuration, and autoscaler setup.

Prerequisites

Terraform 1.0+
CAST AI Full Access API key
Cloud provider credentials configured
Existing Kubernetes cluster

Instructions

EKS Deployment

# main.tf -- EKS cluster onboarding
module "castai_eks" {
  source  = "castai/eks-cluster/castai"
  version = "~> 3.0"

  api_token           = var.castai_api_token
  aws_account_id      = data.aws_caller_identity.current.account_id
  aws_cluster_region  = var.region
  aws_cluster_name    = var.cluster_name

  # IAM role for CAST AI to manage nodes
  aws_instance_profile_arn = aws_iam_instance_profile.castai.arn

  # Autoscaler configuration
  autoscaler_policies_json = jsonencode({
    enabled = true
    unschedulablePods = { enabled = true }
    nodeDownscaler = {
      enabled = true
      emptyNodes = { enabled = true, delaySeconds = 300 }
    }
    spotInstances = {
      enabled = true
      spotDiversityEnabled = true
    }
    clusterLimits = {
      enabled = true
      cpu = { minCores = 4, maxCores = 200 }
    }
  })

  # Node templates
  default_node_configuration = module.castai_eks.castai_node_configurations["default"]
}

GKE Deployment

module "castai_gke" {
  source  = "castai/gke-cluster/castai"
  version = "~> 2.0"

  api_token            = var.castai_api_token
  project_id           = var.gcp_project_id
  gke_cluster_name     = var.cluster_name
  gke_cluster_location = var.region

  gke_credentials = base64decode(
    google_container_cluster.this.master_auth[0].cluster_ca_certificate
  )

  autoscaler_policies_json = jsonencode({
    enabled = true
    unschedulablePods = { enabled = true }
    nodeDownscaler = {
      enabled = true
      emptyNodes = { enabled = true, delaySeconds = 300 }
    }
  })
}

AKS Deployment

module "castai_aks" {
  source  = "castai/aks/castai"
  version = "~> 1.0"

  api_token              = var.castai_api_token
  aks_cluster_name       = var.cluster_name
  aks_cluster_region     = var.region
  node_resource_group    = azurerm_kubernetes_cluster.this.node_resource_group
  azure_subscription_id  = data.azurerm_subscription.current.subscription_id
  azure_tenant_id        = data.azurerm_client_config.current.tenant_id

  autoscaler_policies_json = jsonencode({
    enabled = true
    unschedulablePods = { enabled = true }
    spotInstances = { enabled = true }
  })
}

Multi-Cluster Deployment Pattern

# Deploy CAST AI across all clusters with a for_each
variable "clusters" {
  type = map(object({
    name     = string
    provider = string  # eks, gke, aks
    region   = string
    max_cpu  = number
  }))
}

# Then reference the appropriate module per provider

Error Handling

Issue	Cause	Solution
IAM role error	Missing permissions	Check CAST AI IAM docs for required policies
Module version conflict	Terraform lock	Run `terraform init -upgrade`
Cluster not appearing	Wrong credentials	Verify cloud provider auth
Policies not applying	JSON encoding error	Validate `jsonencode()` output

Resources

Next Steps

For webhook-based automation, see

castai-webhooks-events