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SUMMARY:Ask Your Microservices Anything: Knowledge Graphs for DevOps RAG -
  Jeremy Adams
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UID:pretalx-devopsdays-portland-2026-FFVUSJ@talks.devopsdays.org
DESCRIPTION:"If the Database goes down\, what breaks?" The answer lives in
  a wiki page that was accurate eighteen months ago\, a ticket queue nobody
  trusts\, and one person's head. \n\nYou could point a RAG chatbot at your
  docs. We'll do exactly that and watch our vector search return a fluent\,
  well-formatted\, incorrect number. We'll try the obvious fix\, watch it a
 ppear to work\, and unpack why that's the most dangerous result of the day
 .\n\nThen we'll fix it properly. Working against a free graph database hol
 ding both your service topology and your unstructured ticket text\, you'll
  build four retrieval strategies and learn exactly what each one gives up:
  semantic (vector) search\, parameterized graph db queries\, the two combi
 ned\, and natural-language-to-query. \n\nYou'll build it twice on the same
  data: once in Python\, once in a no-code agent builder. You leave with bo
 th\, and a working agent you can adapt to your own infrastructure.\n\nTake
 aways\n- Model infrastructure\, ownership\, and work-in-flight as one quer
 yable graph\n- Choose a retrieval strategy deliberately instead of default
 ing to one search approach\n- Build an assistant/agent from the ground up!
 \n- Recognize some specific shapes of question an LLM will answer confiden
 tly and wrongly
LOCATION:Room 329
URL:https://talks.devopsdays.org/devopsdays-portland-2026/talk/FFVUSJ/
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