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Proactive Monitoring

Good for You!

Article from ADMIN 35/2016

By Dirk Röder

System administrators usually take action after monitoring software indicates the failure of a service or server. In contrast to this reactive approach, a proactive monitoring solution with Riemann allows admins to detect problems in advance.

Many monitoring solutions respond to a problem once a threshold set by the admin is reached. These values derive mostly from experience. An alarm triggered by an overrun threshold can darken the mood of the team member on call when, for example, hard disk drive loads increase beyond defined limits during a backup in the middle of the night.

Instead of this reactive monitoring, developer Kyle Kingsbury and his team recommend proactive monitoring with Riemann [1], which allows you to predict imminent failures and initiate countermeasures in a timely manner.

The program, first published in 2012, is an event-stream processor; that is, connected hosts use a log buffer to send events to the Riemann server. Each event contains data for the host, a service description, a status, the time of the measurement, and a validity period. Riemann processes the received events and aggregates values to statistical mean values. A functional language configures the event flow; for example, you could forward the data to other programs for the purpose of evaluation, alert the on-duty employee or team, or both.

How Are You?

Proactive monitoring thus reverses the direction of intervention compared with reactive monitoring: Monitored hosts send metrics to Riemann, and they assess their status themselves, rather than leaving this decision to a central instance [2]. In addition to the server, which is implemented in Clojure and runs in a Java virtual machine, Riemann has a web interface (the Riemann Dash) and various clients for Linux, OS X, and Windows.

The Riemann service stores all the information in its index and uses this to respond to the client requests. The index resides exclusively in RAM and stores precisely one value – the latest – for each metric received. In other words, after

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