Amazon SQS is a lightweight, fully-managed message queueing service that decouples and scales microservices, serverless applications, and distributed systems. AWS Lambda offers a fully-managed serverless runtime, enabling developers to run code in multiple languages without provisioning servers. By configuring an SQS queue as an event source for a Lambda function, the function can automatically trigger and process messages from the queue, scaling with the workload. This setup provides several benefits, including fewer moving parts, reduced costs, improved fault tolerance, and enhanced user experience. However, it also introduces some limitations, such as visibility timeouts and SQS triggers being charged at regular prices. To mitigate these issues, developers can implement strategies like increasing concurrency limits, setting reserved concurrency, or using backpressure control in front of the SQS queue. Additionally, understanding failure modes like partial failures, SQS over-scaling, and SQS over-pulling is crucial to ensure a reliable system. By embracing curiosity and experimenting with learning experiments in AWS, developers can mitigate risks and create a scalable and resilient system.