I recently presented “The RED Method: How to Instrument Your Services” at CloudNativeCon Austin. The conference was a blast, and whilst my talk was beset by a couple of technical challenges I still think it went quite well! Here’s the video for those who couldn’t make it, and a full write up will be coming in the next few weeks:
I still remember my first steps with PromQL. Even after I learned more about the available functions and the Prometheus data model, the queries just would not flow as quickly as I liked. At Kausal, we believe making the writing of those queries easier will benefit the general adoption of Prometheus. That is why we decided to make our PromQL query editor open source.
The editor comes with tab-completion for metric names, label keys, label values, ranges, etc.
It is now available as
prom-editor at our public mono-repo: https://github.com/kausalco/public, wrapped inside an example React application.
We previously wrote about Slate and Prism, the underlying editor libraries.
This blog post will dive a little deeper into the mechanics of the editor and its integration into an application.
Once developers have experienced the benefits of metrics instrumentation they go nuts and emit metrics for everything. That is a generally a good thing, but could also lead to unnecessary load on Prometheus or, depending on the label usage, extended query evaluation times. Sometimes it helps to see it to believe it. We recently added a usage graph for the metrics space to give our customers insight into their timeseries’ label space.