When it comes to operating Lambda, we often want to configure alarms to alert us when things aren’t running smoothly. Naturally our first choice for Lambda alarms is CloudWatch, the default monitoring service that comes with AWS.

CloudWatch gives us some custom metrics out-of-the-box, such as: errors and invocation rates. But there are some problems we run into when setting up alarms based directly on these metrics.

By the end of this article you’ll understand why alarms based on default AWS Lambda Metrics can cause difficulty, how AWS Metric Math helps us to apply “context” in our alarms and make them more effective, and how to setup an alarm using metric math to calculate an error rate percentage. 

Your AWS Lambda code is throwing errors in production. To defuse the situation, you need to pinpoint what’s going wrong and find the fix. It’s a good thing you already instrumented your Lambda with high quality, well structured logs, right?

There are many aspects to monitoring a distributed system. And a big part is understanding how, and what to log. But, fear not, you’re in the right place!

Today we’re going to talk about the first step: how you can get Lambda logs into CloudWatch for analysis. Once we’ve discussed that, in the next article, we’ll discuss how to analyse those logs to properly extract the data.

By the end of this article you’ll understand the three steps you’ll need to take to enable CloudWatch logging for a Lambda function.