When it comes to resource management and autoscaling in Kubernetes, users have traditionally gone with Cluster Autoscaler, although users on AWS are now increasingly looking at Karpenter. Both platforms set out to accomplish the same end result through widely different approaches to the problem, with Karpenter offering new exciting capabilities and features. This is why clear clarity on the offerings is needed to determine the right fit.
This blog will explore the primary differences between Karpenter and Cluster Autoscaler. Simultaneously, it introduces nKS to the picture – a platform that addresses the limitations of both. Read through!
What Are the Primary Differences Between Cluster Autoscaler,Karpenter and nKS – nOps Karpenter Solution?
| Feature | Cluster Autoscaler | Karpenter | nKS-nOps Karpenter Solution |
| Resource Management | Based on the resource utilization of existing nodes, Cluster Autoscaler takes a reactive approach to scale nodes. | Based on the current resource requirements of unscheduled pods, Karpenter takes a proactive approach to provisioning nodes. | Uses Karpenter to handle what it does best while providing extra signals to Karpenter to supercharge its capabilities. |
| Node management | Cluster Autoscaler manages nodes based on the resource demands of the present workload, using predefined autoscaling groups. | Karpenter scales, provisions, and manages nodes based on the configuration of custom Provisioners. | Manages your Karpenter Provisioner configuration for you to optimize availability and ensure you use the lowest-cost compute. |
| Scaling | Cluster Autoscaler is more focused on node-level scaling, which means it can effectively add more nodes to meet any increase in demand. But this also means it may be less effective in downscaling resources. | Karpenter offers more effective and granular scaling functionalities based on specific workload requirements. In other words, it scales according to the actual usage. It also allows users to specify particular scaling policies or rules to match their requirements. | Scaling with nKS adds RI, Savings plan, and Organization awareness to Karpenter’s already advanced scaling capabilities. In addition, continuous reconsideration means that your nodes may be descheduled and your workloads can be moved to the more cost-optimal resources. |
| Scheduling | With Cluster Autoscaler, scheduling is more simple as it is designed to scale up or down based on the present requirements of the workload. | Karpenter can effectively schedule workloads based on different factors like availability zones and resource requirements. It can try to optimize for the cheapest pricing via spot but is unaware of any commitments like RI’s or Savings Plans. | It goes beyond Karpenter’s single cluster view to watch your entire AWS ecosystem to automatically schedule EKS resources and maximize savings via RI, Savings Plans, and Spot. |
Cluster Autoscaler Vs. Karpenter Vs. nKS – nOps Karpenter Solution
Besides the above-mentioned aspects of the three platforms, they differ in the availability and unavailability of certain features. So, here’s a comprehensive list of haves and have-nots for Karpenter Vs. Cluster Autoscaler Vs. nOps Karpenter Solution (nKS).
nOps Karpenter Solution (nKS) is a powerful solution that addresses several of Karpenter’s and Cluster Autoscaler’s limitations, providing organizations with a more efficient and cost-effective Kubernetes cluster autoscaling solution.
Here’s how nKS is an easier and more effective approach because with nKS you can:
- Have a 60-minute advance Spot termination prediction
- Automatically schedule EKS resources to available RI, Savings Plans, and Spot to maximize savings
- Reconsider price in real-time for maximum savings
- Leverage AWS’ modern and open-sourced Karpenter as your autoscale
Upgrade to nOps Karpenter Solution (nKS)and start automatically optimizing your environment for spot, RI, and savings plans today. Reduce your EKS infrastructure costs by up to 60% with nKS.
Explore more about nOps Karpenter Solution (nKS) here!
