DEA-C01 · Question #283
A company needs to build an extract, transform, and load (ETL) pipeline that has separate stages for batch data ingestion, transformation, and storage. The pipeline must store the transformed data…
The correct answer is B. Deploy AWS Step Functions workflows to orchestrate AWS Lambda functions that ingest data. AWS Step Functions provides managed orchestration with per-step retries, error handling, and execution history. Orchestrating Lambda for ingestion and AWS Glue jobs for transformation to S3 delivers a serverless, low-maintenance pipeline with built-in visibility into each…
Question
A company needs to build an extract, transform, and load (ETL) pipeline that has separate stages for batch data ingestion, transformation, and storage. The pipeline must store the transformed data in an Amazon S3 bucket. Each stage must automatically retry failures. The pipeline must provide visibility into the success or failure of individual stages. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AChain AWS Glue jobs that perform each stage together by using job triggers. Set the MaxRetries
- BDeploy AWS Step Functions workflows to orchestrate AWS Lambda functions that ingest data.
- CBuild an Amazon EventBridge based pipeline that invokes AWS Lambda functions to perform
- DSchedule Apache Airflow directed acyclic graphs (DAGs) on Amazon Manages Workflows tor
How the community answered
(47 responses)- A15% (7)
- B72% (34)
- C9% (4)
- D4% (2)
Explanation
AWS Step Functions provides managed orchestration with per-step retries, error handling, and execution history. Orchestrating Lambda for ingestion and AWS Glue jobs for transformation to S3 delivers a serverless, low-maintenance pipeline with built-in visibility into each stage’s success
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