Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Why nobody cares about your anomaly detection

Baron Schwartz (VividCortex)
2:40pm3:20pm Wednesday, March 7, 2018
Secondary topics:  Graphs and Time-series
Average rating: ****.
(4.80, 5 ratings)

Who is this presentation for?

  • Data engineers, architects, and product managers

What you'll learn

  • Understand why anomaly detection is a means, not an end


Anomaly detection is white hot in the monitoring industry, but many don’t really understand or care about it, while others repeat the same pattern many times. VividCortex has built several features based on anomaly detection into its product, but customers have told the company that only some of them are valuable. The same is true of other companies in the space. It seems like everyone has anomaly detection, but customers generally aren’t finding it useful. Why? And what can we do about it?

VividCortex’s Baron Schwartz is very interested in anomaly detection and even coauthored an O’Reilly book on the subject. Baron explains how he arrived at a different perspective of anomaly detection (one that people he admires have long held but which took him a while to understand): a “post-anomaly detection” point of view. Baron shares why he now sees anomaly detection as a very limited tool, to be used for specific purposes and with careful attention to design and context (including culture) and only to be considered as a part of an overall solution—not a solution itself.

Photo of Baron Schwartz

Baron Schwartz


Baron Schwartz is the founder and CTO of VividCortex, the best way to see what your production database servers are doing. Baron has written a lot of open source software and several books, including High Performance MySQL. He’s focused his career on learning and teaching about performance and observability of systems generally, including the view that teams are systems and culture influences their performance, and databases specifically.