skyline

I am interested in how it compares with Etsy's Skyline project: https://github.com/etsy/skyline

Evaluated it, and ultimately rejected it for a couple of reasons: - You must pick up Clojure to understand and configure Riemann (we're not a Clojure shop, so this is a non-trivial requirement) - Config file isn't a config file, it's an executed bit of Clojure code - Riemann is not a replacement for an alerting mechanism, it's another signal for alerting mechanisms (though since it's Clojure and the configuration file is a Clojure script, you can absolutely hack it into becoming an alerting system) - Riemann is not a replacement for a trend graphing mechanism. - There are other solutions which can be piped together to get the 80% of the functionality we wanted from Riemann (Graphite + Skyline) in much less invested time Skyline link: https://github.com/etsy/skyline

Anomaly detection is very different across different domains. For CC fraud / risk, you have discrete transactions so the problem is one of classification, and generally approached with supervised learning. I don't know what you mean by combining multiple variables. Do you mean analysis methods that work with multiple variables (instead of 1-dimensional z-scores) or do you mean methods that combine multiple variables into 1, to reduce input dimensions (i.e. principal component analysis) Because data and data reporting platforms are so different across companies, there's no 'simple framework' to do reporting. You probably want something like https://github.com/etsy/skyline. You also describe an ensemble method for outlier detection, which is what Skyline uses. I want to note that there is no reason to consider ensembles "not" outlier detect