Prometheus offers a lot of value to the operators of a Kubernetes cluster. Let's look at some of the more important dimensions of the software:

• Simple to operate: It was built to run as individual servers using local storage for reliability
• It's precise: You can use a query language similar to JQL, DDL, DCL, or SQL queries to define alerts and provide a multi-dimensional view of status
• Lots of libraries: You can use more than ten languages and numerous client libraries in order to introspect your services and software
• Efficient: With data stored in an efficient, custom format both in memory and on disk, you can scale out easily with sharding and federation, creating a strong platform from which to issue powerful queries that can construct powerful data models and ad hoc tables, graphs, and alerts

Also, Promethus is 100% open source and is (as of July 2018) currently an incubating project in the CNCF. You can install it with Helm as we did with other software, or do a manual installation as we'll detail here. Part of the reason that we're going to look at Prometheus today is due to the overall complexity of the Kubernetes system. With lots of moving parts, many servers, and potentially differing geographic regions, we need a system that can cope with all of that complexity.

A nice part about Prometheus is the pull nature, which allows you to focus on exposing metrics on your nodes as plain text via HTTP, which Prometheus can then pull back to a central monitoring and logging location. It's also written in Go and inspired by the closed source Borgmon system, which makes it a perfect match for our Kubernetes cluster. Let's get started with an install!