Last year, we released native tracing for AWS Lambda through Datadog APM to provide deep visibility into serverless functions and surface performance issues such as cold starts and errors, without any added latency. But Lambda functions are only one piece of the puzzle in a rapidly growing serverless ecosystem, which includes message queues, data streams, notification services, and more.

When using services created by other people, it’s often neither obvious what they mean, let alone how to fix them. One of these error messages you might see when using Amazon API Gateway is “encoding not enabled”. The first question here is, what kind of encoding does this error message refer to? The first thought might go into the video or audio encoding direction and lead to a dead-end since you probably didn’t send any audio or video files.

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. It is great if you want to create a cost-effective, on-demand service. You can use it as part of a bigger project where you have multiple services or as a standalone service to do a certain task like controlling Alexa Skill.

How do we get started on monitoring AWS Lambda? Let me first introduce you to the term serverless computing. It doesn't matter if you have been in the tech industry only a few months, or you started writing code when Pascal was still considered cutting edge, you probably would have heard the term serverless computing thrown around in recent times. But what exactly is serverless computing?

One of the serverless best practices is one-purpose functions. You should keep your Lambda functions small and solve exactly one use-case. This way, you can optimize them better and keep potential security problems contained. But creating many small functions can get overwhelming quickly. Even small projects can end up with more than 20 Lambda functions.