https://video.ut0pia.org/videos/watch/73e58e6d-ead1-418a-99d8-24678f3fa97e Traditional monitoring reported the system healthy: latency down, errors at zero. A mandatory processing step had been silently skipped, and nothing caught it except the graph. Ritvik Pandya's team at JP Morgan models each API request as a short lived execution graph, a DAG of the middleware steps it passes through, learned from telemetry at over 1,600 requests per second. Compare what actually ran against that learned graph and a skipped, reordered, or injected step stops hiding behind healthy averages. The same graph localizes performance problems to the exact node instead of the whole endpoint. In production it flagged a 41x deviation at a single node that service level monitoring never saw, cutting root cause from hours to under 30 seconds. The talk separates a one off anomaly from real drift, a slow shift that needs a new baseline, and sorts drift into structural, volume, and behavioral, using per node baselines and KL divergence rather than one threshold for every request. The payoff is a cheap tier one check that only escalates when the graph says something actually changed. Speaker info: https://www.linkedin.com/in/ritvik-pandya/, Timestamps: 0:00 - Execution graphs for anomaly and drift detection 1:07 - What a short lived execution graph is 3:28 - Tiered checks and per client baselines 5:23 - The method: baseline, deviation, localize, act 6:16 - Localizing a slow node, and how the system is trained 7:33 - Anomaly versus drift 8:55 - The three kinds of drift: structural, volume, covariate 12:46 - The pipeline: from telemetry to gradual rollout 13:54 - Hot path versus recon, and worked examples 15:21 - Tuning it: delayed events, sampling, cold starts 17:09 - Results and lessons Thu, 23 Jul 2026 09:43:54 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/73e58e6d-ead1-418a-99d8-24678f3fa97e All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.