Learn how to instrument AWS Lambda functions with OpenTelemetry to gain valuable insights and improve the performance of your serverless apps.

Amazon Web Services (AWS) offers over 200 services. But, AWS Lambda continues to stand out for several reasons. This AWS Lambda tutorial will help explain Lambda in simple terms so you can decide if the service suits your computing needs. We’ll cover AWS Lambda, how it works, how it compares to EC2, use cases, benefits, limitations, and more. Additionally, we’ll cover how you can monitor and manage your Lambda costs without the burden of cost management.

In 2021, we announced the release of the Datadog Lambda extension, a simplified, cost-effective way for customers to collect monitoring data from their AWS Lambda functions. This extension was a specialized build of our main Datadog Agent designed to monitor Lambda executions.

AWS Step Functions coordinate serverless workflows, integrating AWS services with visual state machines for scalable, resilient applications.

Serverless architectures are the rental tux of computing. If you’re using AWS to manage and scale your underlying infrastructure, you’re renting compute time or storage space. Your Lambda functions are the tie or cummerbund you purchase to customize your rental. Using the AWS event-driven architecture improves business agility, allowing you to move quickly. Lambda is the on-demand compute services that runs custom code driving an event’s response.

AWS Lambda is an event-driven compute service, which means it executes tasks automatically when triggered by a compute event. This automation also means that your Lambda costs can quickly exceed your budget. That is especially true when you’re not familiar with AWS Lambda pricing. In this guide, we’ll discuss the AWS Lambda pricing model, including how billing works and how to optimize Lambda costs.

Serverless or event-driven applications can comprise many different distributed components, including serverless compute services such as AWS Lambda and AWS Fargate for Amazon ECS, as well as managed data streams, data stores, workflow orchestration tools, queues, and more. Having full end-to-end visibility into requests as they propagate across all of these parts of your application is crucial to monitoring performance, locating affected up- or downstream services, and troubleshooting issues.