AWS Lambda is a serverless compute service that enables developers to build event-driven applications without provisioning or managing infrastructure resources. It automatically scales instances based on the number of incoming requests, and its pricing model is based on the execution time, memory size, and number of requests for each function. To effectively monitor Lambda, it's essential to understand how your functions are used, the type of resources they need to run efficiently, and how other services interact with them. Monitoring key metrics such as duration, billed duration, memory size, max memory used, errors, invocations, concurrency, provisioned concurrency utilization, and spillover invocations can help you optimize your Lambda code, manage costs, and troubleshoot issues. Additionally, using distributed tracing and APM tools like AWS X-Ray and Datadog can provide valuable insights into performance bottlenecks in your serverless architecture.