AWS Certified Data Engineer Associate DEA-C01 Practice Question
Your company runs several Amazon EMR clusters that execute nightly Spark jobs. The engineering team wants a managed solution to aggregate application and step logs from every cluster, retain the data for 30 days, and provide near-real-time search and interactive dashboards to troubleshoot performance issues. Which approach meets these requirements with the least operational overhead?
Stream logs from the EMR master node to Amazon Kinesis Data Streams, invoke AWS Lambda to load the records into Amazon DynamoDB, and build Amazon QuickSight analyses on the table.
Install Filebeat on every EMR node to forward logs to an ELK stack running on a separate always-on EMR cluster and delete indices older than 30 days.
Enable log archiving to Amazon S3, run Amazon Athena queries against the logs, and visualize the results in Amazon QuickSight with a 30-day lifecycle policy on the S3 bucket.
Configure each EMR cluster to publish its logs to CloudWatch Logs, create a CloudWatch Logs subscription that streams the logs to an Amazon OpenSearch Service domain, and set a 30-day retention policy on the log groups.
Streaming each EMR cluster's application and step logs to Amazon CloudWatch Logs is fully managed and eliminates node-level agents. A CloudWatch Logs subscription can forward the data to an Amazon OpenSearch Service domain, which automatically indexes the events so engineers can query them and build dashboards in OpenSearch Dashboards. Retention policies on the CloudWatch log groups enforce the 30-day requirement. The other options either require self-managed analytics infrastructure, lack near-real-time search, or add unnecessary data-flow components.
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AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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