Skills Development Multi-Cloud Kubernetes Deployment for CAST AI

Multi-Cloud Kubernetes Deployment for CAST AI

v20260423
castai-deploy-integration
Automate the deployment of CAST AI across various multi-cloud Kubernetes clusters, including EKS, GKE, and AKS. This module uses Terraform Infrastructure as Code (IaC) patterns to reliably configure necessary components like IAM roles, node autoscaling policies, and cluster resources, ensuring standardized onboarding across different cloud environments.
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Overview

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.

Info
Category Development
Name castai-deploy-integration
Version v20260423
Size 4.26KB
Updated At 2026-04-26
Language