All Tools
K
Dev ToolsFreeOpen Source
KARPENTER
Just-in-time Kubernetes nodes for bursty ML workloads
Apache-2.0
ABOUT
Cluster Autoscaler and fixed node groups lag when a training Job needs a specific GPU type now. Karpenter reads pending pod constraints and launches fitting instances in seconds, then drains them when the queue is empty so you stop paying for idle accelerators.
INTEGRATION GUIDE
1. Scale GPU nodes when training Jobs go pending, then drain them when idle
2. Mix CPU inference and GPU training on one cluster without pre-baked node groups
3. Bin-pack bursty agent or batch workloads onto cheaper spot capacity
4. Cut idle node cost versus keeping always-on GPU autoscaling groups
TAGS
kubernetesautoscalinggpucloudprovisioningdevops