One size definitely doesn’t fit all when it comes to open source monitoring solutions, and executing generally understood best practices in the context of unique distributed systems presents all sorts of problems. Megan Anctil shares pain points and lessons learned at Slack wrangling known technologies such as Icinga, Graphite, Grafana, and Elastic Stack to best fit the company’s use cases.
Slack uses a few well-known monitoring tools, including Icinga, Graphite, Grafana and Elastic Stack, but its Technical Operations team isn’t large enough to build an in-house solution for all of these. Nor does the team think it’s sustainable to throw money at the problem, given the volume of information processed and the not-insignificant price and rigidity of many vendor solutions. With thousands of servers across multiple regions and millions of metrics and documents being processed and indexed per second, the team had to figure out how to scale these technologies to fit Slack’s needs.
On the backend, they experimented with multiple clusters in both Graphite and ELK, distributed Icinga nodes, and more. At the same time, they’ve tried to build usability into Grafana that reflects the team’s mental models of the system and have found ways to make alerts from Icinga more insightful and actionable. Megan explores the team’s experience and outlines a framework for building out your own special monitoring snowflakes.
Megan is a senior engineer on the Technical Operations team at Slack. She enjoys deep dives in debugging and long walks on the beach with her #MonitoringLove(s).
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