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Auto Scaling for Amazon EMR

5 minutes 5 Questions

Auto Scaling in Amazon EMR helps to optimize performance and reduce costs by automatically adding or removing instances in response to varying workload demands. Users can set up scaling policies to define how instances are added or terminated depending on CloudWatch metrics or based on specialized …

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AWS Certified Solutions Architect - Auto Scaling for Amazon EMR Example Questions

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Question 1

A data processing pipeline needs an Amazon EMR cluster handling periodic heavy workloads. The instances are taking too long to spin up after the workload starts, delaying results. What is the best solution?

Correct Answer: Increase the minInstances configuration of Auto Scaling policy to keep a minimum number of instances always running

By increasing the minInstances configuration in the Auto Scaling policy, the cluster will always have a minimum number of instances running, resulting in faster response for periodic heavy workloads. Other options either risk aggressive scaling costs, decrease performance or have no relation to instance spin-up time.

Question 2

A company has an Amazon EMR cluster that processes large datasets. The processing time needs to be improved without doubling the infrastructure cost. What is the best solution?

Correct Answer: Enable Automatic Scaling for EMR with the proper scaling policy

The best solution is to enable Automatic Scaling for EMR with the proper scaling policy, as it will optimize resources and costs by scaling the cluster size based on processing needs. Just increasing the number of instances or memory will increase costs more significantly, while enabling Auto Scaling without a proper scaling policy might not improve processing time.

Question 3

An e-commerce company has an Amazon EMR cluster consuming events data from Kinesis Streams. During the flash sales period, the EMR cluster needs to handle a 5-fold increase in processing demands. What is the best way to handle this?

Correct Answer: Use Auto Scaling with custom CloudWatch metrics to scale out the EMR cluster

Using Auto Scaling with custom CloudWatch metrics and proper scaling policy will automatically scale out the EMR cluster based on the increased processing demands, without manual intervention. Other options either do not scale dynamically or focus on fundamental changes that do not address the increased processing demand during flash sales.

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