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Question 420 - SAA-C03 discussion

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A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS). The company's workload is not consistent throughout the day The company wants Amazon EKS to scale in and out according to the workload.

Which combination of steps will meet these requirements with the LEAST operational overhead? {Select TWO.)

A.
Use an AWS Lambda function to resize the EKS cluster
Answers
A.
Use an AWS Lambda function to resize the EKS cluster
B.
Use the Kubernetes Metrics Server to activate horizontal pod autoscaling.
Answers
B.
Use the Kubernetes Metrics Server to activate horizontal pod autoscaling.
C.
Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
Answers
C.
Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
D.
Use Amazon API Gateway and connect it to Amazon EKS
Answers
D.
Use Amazon API Gateway and connect it to Amazon EKS
E.
Use AWS App Mesh to observe network activity.
Answers
E.
Use AWS App Mesh to observe network activity.
Suggested answer: B, C

Explanation:

https://docs.aws.amazon.com/eks/latest/userguide/horizontal-pod-autoscaler.html

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

Horizontal pod autoscaling is a feature of Kubernetes that automatically scales the number of pods in a deployment, replication controller, or replica set based on that resource's CPU utilization. It requires a metrics source such as the Kubernetes Metrics Server to provide CPU usage data1. Cluster autoscaling is a feature of Kubernetes that automatically adjusts the number of nodes in a cluster when pods fail or are rescheduled onto other nodes. It requires an integration with AWS Auto Scaling groups to manage the EC2 instances that join the cluster2. By using both horizontal pod autoscaling and cluster autoscaling, the solution can ensure that Amazon EKS scales in and out according to the workload.

asked 16/09/2024
Katrina Allangba
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