There are four standard types of metric in Prometheus instrumentation: Gauge, Counter, Summary and Histogram. Today we'll have a look at the principles around Counters, and how Prometheus differs from other monitoring systems.
Reliable Insights
A blog on monitoring, scale and operational Sanity
High CPU load is a common cause of issues. Let's look at how to dig into it with Prometheus and the Node exporter.
As your Prometheus usage grows and starts to get loaded, it'd be useful to know which metrics are using the most resources so that you can re-evaluate their utility.
It's a best practice with Prometheus that target labels should be constant over a target's entire lifetime. On the other hand it's useful to aggregate metrics across all the machines that are currently Apache servers. How can we do that?
Prometheus 0.16.1 was just released, and with it brings my addition of the irate function. This offers more responsive graphs and higher resolution dashboards.
It's easy to get carried away by the power of labels with Prometheus. In the extreme this can overload your Prometheus server, such as if you create a time series for each of hundreds of thousands of users. Thankfully there's a way to deal with this without having to turn off monitoring or deploy a new version of your code.
Some monitoring systems are very limited in what calculations you can do with them. Prometheus is not such a system, and today I'm happy to say that half a year after it publicly launched, Prometheus is Turing Complete.
