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1). What are the key performance metrics to monitor for an SQS queue, and how do you optimize based on these metrics??
A) ApproximateNumberOfMessagesVisible, ApproximateNumberOfMessagesNotVisible, Throughput.
B) Message size, message retention period, dead-letter queue size.
C) Consumer count, message delivery rate, error rate.
D) All of the above.
2). How do you handle large-scale message processing with SQS, considering factors like throughput, latency, and error handling??
A) Batching messages, using multiple consumer instances, and implementing exponential backoff.
B) Increasing message visibility timeout, reducing message size, and using dead-letter queues.
C) Sharding the queue, using FIFO queues, and increasing message retention period.
D) None of the above.
3). Explain the trade-offs between using SQS and Amazon Kinesis for a specific use case.?
A) SQS is better for low-throughput, high-latency applications, while Kinesis is for high-throughput, low-latency applications.
B) SQS is better for batch processing, while Kinesis is for real-time processing.
C) SQS is more cost-effective, while Kinesis is more expensive.
D) All of the above.
4). How can you implement a fan-out pattern using SQS to distribute messages to multiple consumers??
A) By creating multiple queues and using SQS fanout.
B) By using SQS message groups and multiple consumer instances.
C) By using SNS to publish messages to multiple SQS queues.
D) All of the above.
5). What are the best practices for using SQS dead-letter queues (DLQs) to handle message processing errors??
A) Configuring a DLQ for each main queue.
B) Implementing retry logic with exponential backoff.
C) Analyzing DLQ messages to identify error patterns.
D) All of the above.
6). How can you optimize SQS costs for a large-scale, low-latency application with varying message volumes??
A) Using SQS Standard queues.
B) Implementing dynamic scaling of consumer instances.
C) Leveraging SQS serverless architecture.
D) All of the above.
7). Describe the challenges of using SQS for exactly-once processing and potential solutions.?
A) Idempotency, retries, and error handling.
B) Message ordering, deduplication, and consistency.
C) Throughput, latency, and cost optimization.
D) All of the above.
8). How can you implement a circuit breaker pattern with SQS to handle transient failures??
A) By using SQS message attributes to track failure counts.
B) By implementing a custom retry mechanism with exponential backoff.
C) By using a third-party circuit breaker library.
D) All of the above.
9). What are the key factors to consider when choosing between SQS and Amazon EventBridge for a messaging use case??
A) Message delivery guarantees, message ordering, and message schema.
B) Integration with other AWS services, scalability, and cost.
C) Message retention, dead-letter queues, and message deduplication.
D) All of the above.
10). How can you optimize SQS performance for applications with high message volumes and low latency requirements??
A) Using SQS FIFO queues.
B) Increasing the number of consumer instances.
C) Batching messages for both sending and receiving.
D) All of the above.
11). Explain the concept of SQS message visibility timeout and how it impacts message processing.?
A) The duration a message is invisible to other consumers.
B) The time a message is retained in the queue.
C) The time it takes for a message to be delivered to a consumer.
D) The time a message is processed by a consumer.
12). How can you monitor and troubleshoot SQS queue performance issues??
A) Using Amazon CloudWatch metrics and alarms.
B) Analyzing SQS logs and metrics.
C) Using SQS dead-letter queues to identify error patterns.
D) All of the above.
13). What are the best practices for using SQS in serverless architectures??
A) Leveraging AWS Lambda as a consumer.
B) Using SQS triggers for Lambda functions.
C) Implementing retry mechanisms and dead-letter queues.
D) All of the above.
14). How can you ensure data security and compliance when using SQS??
A) Using SQS encryption at rest and in transit.
B) Implementing access controls using IAM.
C) Complying with relevant data protection regulations.
D) All of the above.
15). What are the potential challenges and limitations of using SQS for real-time data processing applications??
A) Message ordering guarantees, latency, and throughput.
B) Scalability, cost, and integration with other AWS services.
C) Data consistency, durability, and security.
D) All of the above.
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