Raj - I'm looking for the same thing. As the ML library doesn't support DataStream api, I'm tossing ideas around maybe using the windowing function to build up a model that changes over time.
Jeremy D. Branham Technology Architect - Sprint O: +1 (972) 405-2970 | M: +1 (817) 791-1627 jeremy.d.bran...@sprint.com #gettingbettereveryday -----Original Message----- From: Raj Kumar [mailto:smallthings1...@gmail.com] Sent: Thursday, July 20, 2017 4:24 PM To: user@flink.apache.org Subject: Flink Anomaly Detection Hi, I don't see much discussion on Anomaly detection using Flink. we are working on a project where we need to monitor the server logs in real time. If there is any sudden spike in the number of transactions(Unusual), server errors, we need to create an alert. 1. How can we best achieve this? 2. How do we store the historical information about the patterns observed and compute the baseline? Do we need any external source like Elasticsearch to store the window snapshots to build a baseline? 3. Baseline should be self-learning as new patterns are discovered and baseline should get adjusted based on this. 4. Flink ML has any capabilities to achieve this? Please let me know if you have any approach/suggestions ? -- View this message in context: https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fapache-flink-user-mailing-list-archive.2336050.n4.nabble.com%2FFlink-Anomaly-Detection-tp14370.html&data=02%7C01%7CJeremy.D.Branham%40sprint.com%7C0fd3a0f94d3547bdf12b08d4cfb86865%7C4f8bc0acbd784bf5b55f1b31301d9adf%7C0%7C0%7C636361838310440993&sdata=Rah8P27ro%2FT5xZJAN%2BFwQv0Ze%2FGD9WuF6lGM3ox1Mac%3D&reserved=0 Sent from the Apache Flink User Mailing List archive. mailing list archive at Nabble.com. ________________________________ This e-mail may contain Sprint proprietary information intended for the sole use of the recipient(s). Any use by others is prohibited. If you are not the intended recipient, please contact the sender and delete all copies of the message.
