An application exposes an API that returns workload metrics. The company must collect, analyze, and visualize those metrics at scale to identify issues. Which set of actions will satisfy these requirements? (Pick three.)

The first correct option describes collecting metrics by using EventBridge to schedule a Lambda function that calls the API and stores the data in S3. This is a scalable and common pattern for data ingestion. The second correct option explains how to prepare the data for analysis by using an AWS Glue crawler to catalog the S3 data, making it queryable via Amazon Athena. This enables SQL-based analysis without managing servers. The third correct option details visualizing the data by building Amazon QuickSight datasets from Athena views and creating a QuickSight analysis. QuickSight is a fully managed BI service for creating interactive dashboards. The incorrect option involving DynamoDB streams is unsuitable because Glue crawlers do not directly attach to DynamoDB streams for cataloging. The CloudWatch dashboard option is less efficient for complex analysis and visualization of large datasets compared to QuickSight, and querying Athena directly from CloudWatch widgets is not a standard or scalable pattern.