Automated Anomaly Detection with Machine Learning

The creators of Elasticsearch, Kibana, Beats, and Logstash bring you a brand new feature. The 5.4 release introduces machine learning features (in beta) for the Elastic Stack. We hope you’re excited about it — because we are!

As datasets increase in size and complexity, it becomes impractical to spot infrastructure problems, cyber attacks, or business issues using only dashboards or rules. X-Pack machine learning features automatically model the normal behavior of your time series data in real time to identify anomalies, streamline root cause analysis, and reduce false positives.

Get a full tour of machine learning featuring a demo and Q&A. 

You might also enjoy these:

Register to Watch

You'll also receive an email with related content

Steve Dodson

Dr Steve Dodson is Tech Lead, Machine Learning at Elastic. He was previously founder and CTO at Prelert (acquired by Elastic in Sept 2016). Steve has over 18 years of experience in enterprise systems and software development, focused on large distributed systems, complex event processing, and machine learning. Prior to software development, Steve worked in the Computational Mechanics group at Imperial College, London where he delivered key contributions to the field, resolving scalability issues using a novel approach to solving Maxwell's equations which allowed it to become a practical technique used today by major companies.

Steve Kearns

Steve is director of product management, focused on Elasticsearch and commercial products at Elastic. Prior to Elastic, he worked at DataGravity and Basis Technology, where he designed and deployed text analytics and search technologies to solve interesting problems for some of the world's most successful companies.