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Complete Example

This example demonstrates a full CloudPilot AI deployment with both Node Autoscaler and Workload Autoscaler, including custom nodeclasses, nodepools, recommendation policies, autoscaling policies, and proactive optimization filters.

What This Example Does

• Installs the CloudPilot AI Node Autoscaler with rebalance enabled
• Configures a custom NodeClass (cloudpilot) with 30 GiB system disk
• Configures a NodePool (cloudpilot-general) with spot and on-demand capacity
• Defines a workload for optimization
• Deploys the Workload Autoscaler with:
  • Two recommendation policies (balanced and cost-savings)
  • Two autoscaling policies (default-ap with inplace mode and readonly with off mode)
  • Proactive optimization enabled for default and my-namespace namespaces
  • Proactive optimization disabled for kube-system namespace

Prerequisites

• Terraform >= 1.0
• AWS CLI configured with EKS permissions
• kubectl for cluster operations
• A CloudPilot AI API key -- see Getting API Keys

Usage

1. Create a terraform.tfvars file:

   cloudpilot_api_key  = "your-api-key"
   cluster_name        = "my-eks-cluster"
   region              = "us-west-2"
   restore_node_number = 3
   enable_rebalance    = true

2. Apply the configuration:

   terraform init
   terraform plan
   terraform apply

Customization

• Modify recommendation_policies and autoscaling_policies in main.tf to tune optimization behavior
• Adjust nodeclasses and nodepools for different instance types, architectures, or capacity strategies
• Update enable_proactive / disable_proactive to control which namespaces get proactive optimization