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Quantifying Abnormal Behavior

At Velocity last week, I spoke about how we quantify abnormality in a system’s time-series metrics cheaply, in realtime, at high frequency. Note that this is not the same thing as…

Replacing Clever Code with Unremarkable Code in Go

Not too long ago, my primary programming language was Perl. I’ve written a lot of Perl, including some things that I think are quite clever. And therein lies the problem.…

How Does Adaptive Fault Detection Work? Does It Eliminate Thresholds?

In previous posts, I claimed that thresholds are a root of much evil in monitoring systems (not the root of all evil, but a root of much evil), and that…

Using Socat to Simulate Networking Traffic to Test and Debug

If you don’t know socat, you probably should. From its man: Socat is a command line based utility that establishes two bidirectional byte streams and transfers data between them. Because the…

Two Reasons Why Threshold-Based Monitoring Is Hopelessly Broken

Why is a threshold-based alert such a disaster? There are two big reasons. Thresholds are always wrong. They’re worse than a broken clock, which is at least right twice a…

A Sure-Fire Recipe For Monitoring Disaster

In this post I’ll tell a story that will feel familiar to anyone who’s ever monitored MySQL. Here’s a recipe for a threshold-based alert that will go horribly wrong, beyond…

Why You Should Almost Never Alert On Thresholds

This post is part of an ongoing series on the best practices for effective and insightful database monitoring. Much of what’s covered in these posts is unintuitive, yet vital to understand. Previous…


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Navigate the unknown in this month's THWACK mission to test your DBA skills! 🚁