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Improve site performance with better serverless insights

by Phil Hawksworth

The more we include serverless and edge functions in the architecture of our sites and applications, the more vital it becomes that we have good insights into their use, performance, and any errors. Netlify Functions Metrics provide this information and lets you map changes in performance to individual deploys. Here’s how.

TL;DR

Function Metrics are available through the Netlify UI. When zoomed to show three days of data or less, individual deploys are annotated against the metrics to let you associate any changes in performance to specific changes in deployed code.

Just show me

For those who prefer to watch, rather than to read, here’s very short video to show where to find Function Metrics and how to see the associated deploys.

How can I inspect my functions?

Netlify has always provided access to the logs generated by your functions, either through our Functions Logs or piped to the service you prefer via our Log Drains.

Now, in a addition to being able to explore the data your functions logs, you can also explore the metrics which show invocations. response types, error rates, and execution durations. The metrics are filterable by branch, function, and time.

How do I set up Functions Metrics?

You don’t need to do anything to enable Functions Metrics. Netlify will begin recording the data for as soon as you have serverless functions or edge functions deployed in your site and receiving requests. This is available on all pricing tiers including the starter tier where the latest 7 days of data are available for inspection. Longer retention periods are available on the paid tiers.

How can I see which deployment impacted function errors?

By reviewing the chart of response types or success/error rates, changes in characteristics can be spotted. Zooming in on the chart to a view that includes 3 or fewer days of data will make deploy markers visible allowing you to visually inspect correlations between code deployments and changes in functions performance.

More information