castai-performance-tuning

# CAST AI Performance Tuning ## Overview Tune CAST AI for faster node provisioning, more responsive autoscaling, and efficient API usage. Covers headroom configuration, instance family selection, and API caching for multi-cluster dashboards. ## Prerequisites - CAST AI Phase 2 (full automation) enabled - Understanding of workload scheduling patterns - Access to autoscaler policy configuration ## Instructions ### Step 1: Optimize Node Provisioning Speed ```bash # Configure headroom for proactive scaling (avoids waiting for pending pods) 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": { "enabled": true, "cpuPercentage": 15, "memoryPercentage": 15 } } }' ``` Headroom pre-provisions spare capacity so pods schedule immediately instead of waiting 2-5 minutes for new nodes. ### Step 2: Instance Family Optimization ```hcl # Terraform: Prefer instance families with fast launch times resource "castai_node_template" "fast_launch" { cluster_id = castai_eks_cluster.this.id name = "fast-launch-workers" constraints { spot = true use_spot_fallbacks = true fallback_restore_rate_seconds = 300 # Newer instance types launch faster and have better availability instance_families { i...