Resolving EKS Node Scaling Issues with Cluster Autoscaler

SAA-C03 By islever Editorial Last updated

Design scalable and loosely coupled architectures.

Short answer

B Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.

Question

A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS) and the Kubernetes Horizontal Pod Autoscaler. The workload is not consistent throughout the day. A solutions architect notices that the number of nodes does not automatically scale out when the existing nodes have reached maximum capacity in the cluster, which causes performance issues. Which solution will resolve this issue with the LEAST administrative overhead?
  1. Scale out the nodes by tracking the memory usage.
  2. Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster. Correct Answer
  3. Use an AWS Lambda function to resize the EKS cluster automatically.
  4. Use an Amazon EC2 Auto Scaling group to distribute the workload.

Key Takeaways

The core concept tested is the distinction between Horizontal Pod Autoscaler (pods) and Cluster Autoscaler (nodes), with the common trap being confusion over which component handles infrastructure scaling.

This question addresses the failure of Amazon EKS nodes to scale out when capacity is reached, requiring a solution that manages node count automatically. The correct approach leverages the Kubernetes Cluster Autoscaler to add nodes based on pending pods.

Common mistake: Candidates often select Lambda or EC2 Auto Scaling Group options, failing to recognize that the Kubernetes Cluster Autoscaler is the native, low-overhead standard for managing EKS node pools.

Expert Analysis

Why the Answer Is Correct

The Kubernetes Cluster Autoscaler is designed specifically to adjust the number of nodes in a cluster when pods fail or are rescheduled. In this scenario, since the Pods have already scaled but nodes haven't, the Cluster Autoscaler detects unschedulable pods and requests new instances from the underlying Auto Scaling Groups, resolving the bottleneck with minimal administrative effort.

Why the Other Options Are Wrong

Option A is incorrect because tracking memory usage does not trigger node scaling; it might trigger pod scaling, which has already failed due to lack of resources. Option C introduces unnecessary complexity by requiring custom code maintenance via Lambda. Option D misses the Kubernetes-specific context; while EC2 ASG is the underlying mechanism, using it directly without the Cluster Autoscaler logic does not automatically respond to pod scheduling constraints.

Community Comment Notes

Community consensus strongly supports Option B. As Naveena_Devanga noted, "B is the correct answer" because the Cluster Autoscaler uses Auto Scaling groups to manage node counts. FlyingHawk added nuance by mentioning Karpenter as a modern alternative, but confirmed the validity of the Cluster Autoscaler principle for this exam question.

Official Reference

https://docs.aws.amazon.com/eks/latest/userguide/autoscaling.html

This link opens the official vendor documentation in a new tab.

Exam Strategy

Always distinguish between scaling workloads (HPA/VPA) and scaling infrastructure (Cluster Autoscaler). For EKS questions involving node shortages despite pod demand, look for the Cluster Autoscaler or managed node group auto-scaling features.

Frequently Asked Questions

What is the difference between HPA and Cluster Autoscaler?

HPA scales the number of pod replicas within existing nodes, while Cluster Autoscaler adds or removes nodes from the cluster when pods cannot be scheduled.

Is Karpenter better than Cluster Autoscaler?

Karpenter is a newer, faster alternative, but Cluster Autoscaler remains the standard exam answer for general Kubernetes autoscaling scenarios unless specified otherwise.

More SAA-C03 FAQ →

Community Votes

B
100%

100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 8 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 8

  1. Naveena_Devanga 👍 4
    B is the correct answer. The Kubernetes Cluster Autoscaler automatically adjusts the number of nodes in your cluster when pods fail or are rescheduled onto other nodes. The Cluster Autoscaler uses Auto Scaling groups
  2. Andy_09 👍 4
    Kubernetes Cluster Autoscaler looks correct
  3. alawada 👍 2 Answered B
    When the workload increases and existing nodes reach maximum capacity, the Cluster Autoscaler detects the need for additional nodes and requests them from the underlying AWS infrastructure.
  4. Scheldon 👍 2 Answered B
    AnswerB Using of Kubernetes Cluster Autoscaler seems to be the best solution here
  5. MatAlves 👍 2 Answered B
    Refer to a public discussion thread on this question
Show 3 more comments
  1. FlyingHawk 👍 1
    I think the better solution now is using Karpenter or turn on EKS Auto mode https://docs.aws.amazon.com/eks/latest/userguide/autoscaling.html
  2. jaswantn 👍 2
    option B.
  3. osmk 👍 2 Answered B
    Bcorrect

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