Time-Series-Based Monitoring with Prometheus


Wherever container-based microservices spread, classic monitoring tools such as Nagios [1] and Icinga [2] quickly reach their limits. They are simply not designed to monitor short-lived objects such as containers. In native cloud environments, Prometheus [3], with its time series database approach, has therefore blossomed into an indispensable tool. The software is related to the Kubernetes [4] container orchestrator: Whereas Kubernetes comes from Google’s Borg cluster system, Prometheus is rooted in Borgmon, the monitoring tool for Borg.

Matt Proud and Julius Volz, two former site reliability engineers (SREs) with Google, started the project at SoundCloud in 2012. Starting in 2014, other companies began taking advantage of it. In 2015, the creators published it as an open source project with an official announcement [5], although it previously also existed as open source on GitHub [6]. Today, programmers interested in doing so can develop Prometheus under the umbrella of the Cloud Native Computing Foundation (CNCF) [7], along with other prominent projects such as Containerd, rkt, Kubernetes, and gRPC.

What’s Going On

Thanks to its minimalist architecture and easy installation, Prometheus, written in Go, is easy to try out. To install the software, first download Prometheus [8] and then unpack and launch:

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