Abstract
76%
senior dev or higher
1:11
speaker ratio
60+
practitioners
QCon London 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
From the same track
Tuesday 17 March
10:35 Fleming (3rd Fl.) Session Generative AI Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale Prasanna Vijayanathan, Renzo Sanchez-Silva As Netflix scales hundreds of client platforms, microservices, and infrastructure components, correlating user experience with system performance has become a hard data problem, not just an observability one. 11:45 Windsor (5th Fl.) Session Machine Learning Infrastructure From S3 to GPU in One Copy: Rethinking Data Loading for ML Training Onur Satici Staff Engineer @SpiralDB & a Core Maintainer of Vortex (LF AI & Data), Previously Building Distributed Systems @Palantir ML training pipelines treat data as static. Teams spend weeks preprocessing datasets into WebDataset or TFRecords, and when they want to experiment with curriculum learning or data mixing, they reprocess everything from scratch. 13:35 Whittle (3rd Fl.) Session Kafka Introducing Tansu.io -- Rethinking Kafka for Lean Operations Peter Morgan Founder @tansu.io What if Kafka brokers were ephemeral, stateless and leaderless with durability delegated to a pluggable storage layer? 14:45 Mountbatten (6th Fl.) Session AI/ML Chronon - Mixed-Workload Data Processing Framework Nikhil Simha Co-Founder & CTO @zipline.ai, Author of "Chronon Feature Platform", Previously @Airbnb, @Meta, and @Walmartlabs Chronon is a data processing framework open-sourced by Airbnb. It is adopted across organizations like Stripe, Netflix, OpenAI, and Uber. Chronon was originally built for ML applications. 15:55 Whittle (3rd Fl.) Session streaming The Rise of the Streamhouse: Idea, Trade-Offs, and Evolution Giannis Polyzos, Anton Borisov Over the last decade, streaming architectures have largely been built around topic-centric primitives—logs, streams, and event pipelines—then stitched together with databases, caches, OLAP engines, and (increasingly) new serving systems. 17:05 Rutherford (4th Fl.) Event Connecting the Dots: Modern Data Engineering & Architectures (Limited Space - Registration Required)