September 7th, 2017 • By Tyler Cascade
We’ve just updated our Rollbar.js and Python libraries, making it easy for you to monitor errors on AWS Lambda. If you’ve been considering building apps with serverless architectures on Lambda, we’ve got the exception tracking covered so you can rest easy.
Serverless architectures have taken resource abstraction to the next level.
We've now gone from having servers hosted and managed in the cloud, to having servers that require zero touch and are ephemeral in nature - they're spun up automatically only when certain events are triggered.
They also scale out automatically with usage, and whereas before you paid for compute resources you allocated, now you only pay the resources your app actually uses.
In AWS Lambda, currently the most popular service for building serverless apps, how much you use is based on how many times you trigger functions and how long it takes for those functions to execute.
Lambda functions come with limits, such as the concurrency execution limits. This is set at account-level and when you hit those limits, throttling kicks in. As a result, your functions don’t get executed and you get errors. This is just one of many things to consider and monitor when architecting your app to run on Lambda.
Lambda uses Cloudwatch for monitoring and logging, providing metrics such as number of invocations, execution duration times, throttles, logs, and number of errors from failed invocations.
For richer and more granular information on errors that helps you debug them quickly, we recommend you use a dedicated error monitoring tool like Rollbar.
With Rollbar, you get complete stack traces, replay requests, track events by browser, IP address, affected users tracking, and much more.
Give it a try and let us know what you think!
If you encounter any problems or have improvement requests, we welcome you to open an issue in GitHub. Since the notifier is open source, we always welcome your contributions.
If you haven’t already, sign up for a 14-day free trial of Rollbar and start monitoring for errors in your Node.js app on Lambda.