Do We Still Need to “Observe”? the Future of AI & Observability
summary
Argues that large language models plus Retrieval Augmented Generation already generate PromQL and query live data to answer metric questions, fine tune on org data (Mistral/OpenAI), and produce dashboards and log summaries automatically. Shows automated correlation that finds causal chains, automated correlation and dynamic thresholds that reduce alert fatigue, snapshot gathering for incident context, and autogenerated postmortems with tracked action items. Claims prototypes work end to end and cut investigation time and toil.
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chapters (7)
- 0:00Introduction and AI basics
- 1:39Challenges in observability
- 6:00AI in dashboarding
- 9:49Intelligent alerting
- 11:43AI-assisted investigation
- 14:25Predictions and postmortems
- 17:01Accountability and conclusion
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