AWS SQS Scenario based Questions ❓

Question: You have an application that uses Amazon SQS to decouple different components. How can you ensure that messages are processed at least once?

Answer: By using the default SQS configuration where messages are delivered at least once. Implement idempotency in the processing logic to handle duplicate messages.

Question: How would you handle a situation where the processing of a message fails? What happens to the message in the SQS queue?

Answer: If processing fails and the message is not deleted, it becomes visible again after the visibility timeout. The message will be retried until it is successfully processed or reaches the maximum retention period.

Question: What is the difference between standard and FIFO queues in SQS?

Answer: Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. FIFO queues ensure exactly-once processing, in-order message delivery, and limited throughput.

Question: What is visibility timeout in SQS, and how does it impact message processing?

Answer: Visibility timeout is the period during which a message is invisible to other consumers after being retrieved by one consumer. If not processed within this time, it becomes visible again and can be reprocessed.

Question: How can you optimize the cost and efficiency of polling messages from an SQS queue?

Answer: By using long polling, which reduces the number of empty responses and lowers the cost associated with frequent short polls.

Question: Describe a scenario where you need to change the visibility timeout of a specific message dynamically.

Answer: When processing a message that takes longer than expected, you can extend the visibility timeout to prevent the message from becoming visible and being processed by another consumer.

Question: How can you ensure that a message is processed only once in a distributed system using SQS?

Answer: By using FIFO queues and incorporating message deduplication with a unique message ID or implementing idempotent processing logic in the consumer application.

Question: What is a Dead Letter Queue (DLQ) in SQS, and when would you use it?

Answer: A DLQ is used to handle messages that cannot be processed successfully after multiple attempts. It helps in isolating and debugging problematic messages.

Question: How do you configure a DLQ for an existing SQS queue?

Answer: By specifying a DLQ in the main queue’s settings and defining the maximum receive count, after which messages are automatically moved to the DLQ.

Question: How do you control access to an SQS queue?

Answer: By using IAM policies and SQS queue policies to grant or deny permissions for specific actions (e.g., SendMessage, ReceiveMessage) to users or roles.

Question: What measures can you take to secure messages in transit and at rest in SQS?

Answer: Use HTTPS for secure transmission and enable server-side encryption (SSE) with AWS KMS to encrypt messages at rest.

Question: How can you integrate SQS with AWS Lambda to process messages automatically?

Answer: By creating an event source mapping between the SQS queue and the Lambda function, enabling the function to be triggered when new messages are available.

Question: Describe a use case where you would use SQS in conjunction with Amazon SNS.

Answer: Use SNS to broadcast messages to multiple SQS queues to distribute workloads or deliver notifications to multiple systems simultaneously.

Question: How can you monitor the health and performance of your SQS queues?

Answer: By using Amazon CloudWatch metrics such as ApproximateNumberOfMessagesVisible, ApproximateAgeOfOldestMessage, and NumberOfMessagesDeleted.

Question: How do you troubleshoot issues with message delivery in SQS?

Answer: Check CloudWatch metrics, review DLQ for problematic messages, verify IAM policies, and use CloudTrail logs to track API calls.

Question: What is the purpose of message attributes in SQS, and how would you use them?

Answer: Message attributes provide additional metadata about the message. Use them to pass custom data without affecting the message body, enabling more complex processing logic.

Question: Explain the role of batching in SQS and how it improves performance.

Answer: Batching allows sending, receiving, and deleting multiple messages in a single request, reducing the number of API calls and improving throughput and efficiency.

Question: How would you handle message ordering in a distributed system with SQS?

Answer: Use FIFO queues to preserve message order. If using standard queues, implement application-level logic to handle ordering.

Question: How do you ensure your SQS queue scales to handle a large influx of messages?

Answer: Use standard queues for unlimited throughput, enable long polling to reduce costs, and design your consumers to scale horizontally based on the number of messages.

Question: What are the best practices for designing a resilient system using SQS?

Answer: Implement DLQs for message failure handling, use visibility timeout adjustments for long-running tasks, enable monitoring and alerting, and design idempotent message processing.

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