QuestionQ72

Data Ingestion and Transformation

An ecommerce company uses AWS Glue ETL to process and analyze orders. The company wants to create an extract, transform, and load (ETL) pipeline that handles placed, shipped, delivered, and canceled orders differently.

The company integrates the order-processing system with Amazon EventBridge. It configures EventBridge Scheduler rules for each order status to invoke different AWS Glue workflows. When examining Amazon CloudWatch metrics for the workflow, the company observes that the FailedInvocations metric has a high value for canceled orders.

The company must identify the cause of the failed invocations.

Which solution meets this requirement?

  • A Configure a dead-letter queue in EventBridge Scheduler to store failed events. Analyze the failed order events.
  • B Use the archive and replay features in EventBridge Scheduler to investigate the issue.
  • C Change the retry policy in EventBridge Scheduler to reduce the value for maximum retries.
  • D Change the retry policy in EventBridge Scheduler to increase the value for maximum age of event.
Explanation

An EventBridge Scheduler dead-letter queue stores events that could not be delivered to the target after retries are exhausted. Each dead-letter event includes target invocation details, including ERROR_CODE and ERROR_MESSAGE, which can be analyzed to identify the failure cause.

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