DEA-C01 Question 535
Single answerYou are working as a data engineer for a company that processes large amounts of streaming data. The company uses Amazon Kinesis Data Streams to ingest data and requires real-time analytics on the incoming data. However, you notice that the downstream application is unable to keep up with the volume of data being processed, leading to throttling. What is the best solution to address this issue?
- A
Increase the number of shards in the Kinesis Data Stream.
- B
Enable enhanced fan-out for the Kinesis Data Stream.
- C
Switch to Amazon SQS for data ingestion instead of Kinesis Data Streams.
- D
Use AWS Glue to preprocess the data before sending it to Kinesis Data Streams.
Show answer and explanation
Correct answer: A
Explanation
The issue of throttling in Amazon Kinesis Data Streams typically occurs when the number of records being ingested exceeds the throughput capacity of the stream. By increasing the number of shards in the stream, you increase the total capacity for both data ingestion and data retrieval, addressing the throttling issue effectively. Enhanced fan-out and other options mentioned do not directly resolve the problem of the stream's throughput capacity.
- A. Correct.
Increasing the number of shards in the Kinesis Data Stream increases the overall throughput capacity, which can handle a higher volume of data and prevent throttling. This is the correct solution.
- B. Incorrect.
Enhanced fan-out improves the read throughput for consumers by providing dedicated throughput for each consumer, but it does not address the issue of the stream itself being overloaded.
- C. Incorrect.
Amazon SQS is not ideal for real-time streaming use cases. It is designed for message queuing rather than high-throughput real-time data ingestion.
- D. Incorrect.
AWS Glue is used for ETL (Extract, Transform, Load) processes and is not suited for real-time streaming data ingestion or resolving throttling issues in Kinesis Data Streams.