Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

You manage an Amazon EKS cluster that runs containerized Apache Spark batch jobs that transform data in Amazon S3. The cluster uses a fixed managed node group of twenty m5.xlarge On-Demand instances. During nightly runs CPU utilization exceeds 80 percent and jobs slow, but daytime utilization is under 10 percent. You must boost performance and cut idle costs with minimal operations effort. Which approach meets these goals?

  • Increase the existing node group to forty m5.xlarge instances and enable vertical pod autoscaling for Spark executors to remove resource contention.

  • Install the Kubernetes Cluster Autoscaler on the EKS cluster, create a managed node group that mixes On-Demand and Spot Instances, and set CPU and memory requests for all Spark pods.

  • Migrate the Spark containers to Amazon ECS and enable Service Auto Scaling based on average CPU utilization across tasks.

  • Create an EKS Fargate profile for the Spark namespace so every Spark pod runs on Fargate while keeping the existing node group for system pods.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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