Have you imagined a simple machine learning solution able to prevent revenue leakage and monitor your distributed application? To answer this question, we offer a practical and a simple machine learning solution to create an intelligent monitoring application based on simple data analysis using Apache Spark MLlib. Our application uses linear regression models to make predictions and check if the platform is experiencing any operational problems that can impact in revenue losses. The application monitor distributed systems and provides notifications stating the problem detected, that way users can operate quickly to avoid serious problems which directly impact the company's revenue and reduce the time for action. We will present an architecture for not only a monitoring system, but also an active actor for our outages recoveries. At the end of the presentation you will have access to our training program source code and you will be able to adapt and implement in your company. This solution already helped to prevent about US$3mi in losses last year

Spark Summit 2017 - in Dublin, Ireland
Link to the presentation: https://www.youtube.com/watch?v=8-eYUBgqOfM

Slide deck:
https://www.slideshare.net/SparkSummit/preventing-revenue-leakage-and-monitoring-distributed-systems-with-machine-learning-eiti-kimura-and-flavio-clsio