The first time I tried to monitor a database, I was overwhelmed. There were hundreds of variables to monitor, and there were lots of Nagios check scripts that had dozens of checks. I wasn’t sure what alerts I should set up, so I set up too many and got a bunch of noise as a result. A couple of years later, I returned to that company and found all those alerts still in place, still spamming everyone — but they’d just filtered every alert to the trash.
In this talk, I’ll share how I learned to do this better, so you won’t make the same mistakes I made! Any sophisticated system like a database has many more instrumentation points than you should actively monitor. The trick is approaching it with a sound monitoring framework in mind. This talk explains the framework I’ve developed over many years, which breaks monitoring into a holistic approach that’s easy to understand and makes it obvious what kinds of data are useful for what purposes.
You’ll learn the 7 golden signals (yes, seven and not four), how workload and resource performance are complementary and necessary for a complete understanding of database health and performance, and how to monitor technology-specific “sharp edges.” I’ll also cover some of those for a few popular databases: MySQL, PostgreSQL, and MongoDB.
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