Don’t call it ML: A New Approach for Troubleshooting with the Elastic Stack

Phoenix
Thu, Sep 15, 3:15 PM (MST)

3 RSVP'ed

About this event

This is the live-streamed presentation portion of the Dallas in-person meetup. Presentations should begin around 5:15pm CDT

Please use the following Zoom details:

https://elastic.zoom.us/webinar/register/WN_2IFT-gEGReet-5zgkUihyg

Agenda:

5:00pm: Doors open (in-person - Dallas)

5:15pm: What is new with Elastic - brought to you by the Elastic Dallas Account Team

5:30pm: Zebrium presentation followed by a Q&A

6:15 -6:50pm: Networking & refreshments (in-person - Dallas)

6:50pm: Event ends (in-person - Dallas)


Talk Abstract: Don’t call it machine learning: A New Approach for Troubleshooting with the Elastic Stack - Larry Lancaster - Founder and CTO @ Zebrium

Imagine this: you wake up to find your Slack blowing up. Alerts are going off, and users are complaining. You go straight to your monitoring dashboard, and you can see right away there's a problem. What's not clear is the reason: what happened? When you can't tell the root cause from your other canned dashboards and alert rules, you have to go searching through logs. You sink into despair... it's going to be a long night.

In this technical discussion, we'll describe an unsupervised machine learning approach that mimics the process of an experienced troubleshooter. It identifies small clusters of log events that are the best indicators of root cause. The resultant payload is summarized using NLP and sent with relevant metrics to Elasticsearch for visualization alongside other observability data on any Kibana dashboard. Larry Lancaster, Founder and CTO @ Zebrium, will describe and demo the machine learning technology together with feedback from real-world users.


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