AWS Certified Data Engineer Associate · Free Practice Question Medium
Question 2
In designing a data pipeline for high availability and fault tolerance, which AWS services should be used together to ensure data is processed reliably and is resilient to failures? (Select TWO)
- A Amazon SQS with dead-letter queues
- B Amazon DynamoDB with global tables
- C Amazon EC2 Auto Scaling
- D Amazon S3
Reveal correct answers
Correct answers: A, D
Explanation
Amazon S3 provides highly durable storage, ensuring data is reliably stored and available across multiple facilities. Amazon SQS with dead-letter queues helps to manage message processing failures, allowing for the reprocessing of failed messages and thus increasing the resilience and fault tolerance of the data pipeline.A. Amazon SQS with dead-letter queues can be used to ensure reliable message processing in a data pipeline. Dead-letter queues help capture and store messages that cannot be processed successfully, allowing for easier troubleshooting and reprocessing of failed messages. This combination with Amazon S3 ensures data is processed reliably and is resilient to failures.
B. Amazon DynamoDB with global tables can be used for replicating data across multiple AWS regions to provide high availability and fault tolerance. However, it is not as directly related to ensuring data is processed reliably and resilient to failures as Amazon S3 and Amazon SQS with dead-letter queues.
C. Amazon EC2 Auto Scaling is not directly related to ensuring high availability and fault tolerance in a data pipeline. While it can help in automatically adjusting the number of EC2 instances based on demand, it does not provide the same level of data reliability and resilience as other services like Amazon S3 and Amazon SQS with dead-letter queues.
D. Amazon S3 is a highly durable and scalable object storage service that can be used to store data reliably in a data pipeline. It is designed to provide 99.999999999% durability and 99.99% availability, making it a suitable choice for ensuring data is processed reliably and resilient to failures.
Discussion
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