Getting down and dirty with metric-based alerting for AWS Lambda

Getting down and dirty with metric-based alerting for AWS Lambda

You'll want to have those metric based alerts implemented as soon as you start working with Lambda. Here's what you need to know.

The phrase “better safe than sorry” gets thrown around whenever people talk about monitoring or getting observability into your AWS resources but the truth is that you can’t sit around and wait until a problem arises, you need to proactively look for opportunities to improve your application in order to stay one step ahead of the competition. Setting up alerts that go off whenever a particular event happens is a great way to keep tabs on what’s going on behind the scenes of your serverless applications and this is exactly what I’d like to tackle in this article.

AWS Lambda Metrics

AWS Lambda is monitoring functions for you automatically, while it reports metrics through the Amazon CloudWatch. The metrics we speak of consist of total invocations, throttles, duration, error, DLQ errors, etc. You should consider CloudWatch as a metrics repository, being that metrics are the basic concept in CloudWatch and they represent a set of data points which are time-ordered. Metrics are defined by name, one or even more dimensions, as well as a namespace. Every data point has an optional unit of measure and a time stamp.

And while Cloudwatch is a good tool to get the metrics of your functions, Dashbird takes it up a notch by providing that missing link that you’d need in order to properly debug those pesky Lambda issues. It allows you to detect any kinds of failures within all programming languages supported by the platform. This includes crashes, configuration errors, timeouts, early exits, etc. Another quite valuable thing that Dashbird offers is Error Aggregation that allows you to see immediate metrics about errors, memory utilization, duration, invocations as well as code execution.

AWS Lambda metrics explained

Before we jump in I feel like we should discuss the metrics themselves to make sure we all understand and know what every term means or what they reffer too.

From there, we’ll take a peek at some of the namespace metrics inside the AWS Lambda, and we’ll explain how do they operate. For example

Invocations will calculate the number of times a function has been invoked in response to invocation API call or to an event which substitutes the RequestCount metric. All of this includes the successful and failed invocations, but it doesn’t include the throttled attempts. You should note that AWS Lambda will send mentioned metrics to CloudWatch only if their value is at the point of nonzero.


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