Elastic's RAG Based AI Assistant for Observability

Learn how Elastic uses RAG to provide better observability analysis for all signals with Bahubali Shetti (Senior Director, Product Marketing at Elastic).
Elastic's platform has the Elastic Learned Sparse Encoder Representations (ELSER), an advanced NLP model built to aid in handling various NLP tasks like search, text classifications, and entity extraction. Elastic Observability uses ELSER to help find the proper contextual information when analyzing issues as an SRE.
GitHub issues, runbooks from Wikipedia or other places, customer tickets, and more can be ingested, indexed, and run through ELSER to help aid in adding contextual internal information when an SRE is analyzing issues with Elastic Observability's AI Assistant. In this video, Bahubali shows you how this works in various features such as APM & Universal Profiling.
Timestamps:
0:00. Introduction
0:52 Teams need AI-powered observability
01:49 Elastic Observability
03:16 Elastic's RAG based AI Assistant
05:42 Retrieval Augmented Generation (RAG)
08:02 Demo
19:03 Closing remarks
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