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Beyond Logs: Real-Time Anomaly Detection with Machine Learning #114

Open fawazghali opened 1 year ago

fawazghali commented 1 year ago

Author's Name

Fawaz Ghali

Author's Bio

No response

Expected time

Standard talk (~40 min)

Language

Abstract

Logs and traces generated by applications are valuable sources of information that can help detect issues and improve performance. However, they are often treated separately from other data, even though they are no different from the data an application works with. In this talk, we will explore a different approach: treating logs and traces as part of a scalable cloud storage repository that can be analyzed with the same techniques used for big data. By keeping all the data together, we can apply machine learning models to detect situations of interest and alert us in real-time when unwanted behavior is occurring or brewing. This approach enables intelligent monitoring that goes beyond simple threshold-based alerts and can help identify complex issues that would otherwise go unnoticed. We will discuss how to harness existing technologies to implement this approach, providing attendees with practical tips and insights that they can apply to their own projects.

pabluk commented 1 year ago

Hi @fawazghali,

First of all, we really thank you for your participation in the Call for Proposal for SRE SummerCamp 2023.

We are sorry to inform you that your talk, "Beyond Logs: Real-Time Anomaly Detection with Machine Learning", has not been selected for SRE SummerCamp 2023.

Unfortunately we were not able to accept your talk this year due to the number of submissions, you can still talk about this topic as a lighting talk during the event or propose this talk in an upcoming SRE France meetup.

We hope you can join us regardless.

Best,

SRE SummerCamp Team