Karpenter is a Kubernetes autoscaling tool used in DevOps to automatically create and remove cloud VMs (nodes) based on what your workloads actually need.
Karpenter is an intelligent Kubernetes node autoscaler that provides exactly the infrastructure your workloads need, when they need it.
smarter replacement for Cluster Autoscaler, especially popular with Kubernetes on AWS (EKS).
Problems karpenter solve?
In Kubernetes, pods often get stuck in Pending because:
- No node has enough CPU or memory
- Instance type is wrong
- Scaling is slow or inefficient
Traditional autoscaling:
- Works with fixed node groups
- Scales slowly
- Often wastes money
Karpenter fixes this by provisioning the right node at the right time.
When Kubernetes sees a pod that cannot be scheduled:
- Karpenter watches the cluster
- It looks at pod requirements (CPU, memory, GPU, labels, taints)
- It launches a best-fit cloud instance automatically
- When pods are gone, it terminates unused nodes
No predefined node groups. No manual tuning.
Some of the features it gives
1. Faster scaling
Nodes come up in seconds, not minutes.
2. Cost optimization
- Chooses cheapest instance types
- Mixes spot and on-demand
- Removes idle nodes aggressively
3. Flexible scheduling
Supports:
- GPUs
- ARM vs x86
- Zone-aware placement
- Workload-specific nodes
4. Less YAML pain
You define policies, not node groups.
Karpenter vs Cluster Autoscaler.
| Feature | Cluster Autoscaler | Karpenter |
| Node groups | Required | Not needed |
| Instance choice | Limited | Any instance |
| Scaling speed | Slow | Very fast |
| Cost efficiency | Medium | High |
| Spot instances | Basic | First-class |
Where Karpenter is used
- EKS production clusters
- AI / ML workloads
- Microservices with burst traffic
- Cost-sensitive startups
- High-scale platforms
Example use case
You deploy an AI inference pod that needs:
- 8 CPU
- 32 GB RAM
- GPU
Karpenter will:
- Pick a suitable GPU instance
- Launch it immediately
- Delete it when load drops
No human intervention.