For in-person attendees: Please register here as well as on AWS Builder Loft page to secure your spot: https://events.builder.aws.com/ReRbol

2026 is the year agentic AI finally works, & it's changing open source analytics.

OSA Con 2026 brings together engineers, architects, & builders working at the intersection of open source data infrastructure & AI. No vendor pitches or 10x AI miracles. Just deep technical talks from great engineers building stuff that works.

We'll get into AI workloads & data management, agents building & operating analytic platforms, & analytics powering autonomous actions, alongside what's happening in real-time analytics, shared data lakes, & emerging open-source architectures.

Nov 2 AWS Builder Loft, San Francisco + Online [Free to attend / Limited in-person capacity]

Speakers

See their abstracts at osacon.io

Lisa Cao - Databricks: Getting AI agents to write better Apache Spark pipelines

Wei-Chin Call - Grafana Labs: Benchmarking AI agents that debug your dashboards

Jason Jay Smith - Google: Serverless eventing for simpler, scalable AI data pipelines

Aditi Pandit - IBM: Inside the Presto C++ engine: production experience, performance & the 2026 roadmap

Alex Merced - Dremio: Building the Open Agentic Lakehouse for data + AI

Heather Meeker, Roman Shaposhnik (Panel discussion): Whose Code Is It Anyway? AI-generated code, ownership & open-source licensing

David Morrison - Applied Computing Research Labs: 10 infrastructure dashboards you can't build with Grafana

Patrick McFadin - McFadin Data & AI Advisory: Why we're still paying rent on our own data-and where lock-in is moving

Felicitas Pojtinger - Loophole Labs: Building legacy-free RISC-V Kubernetes clusters with ClickHouse

Matthew Topol - Columnar / Apache Software Foundation: What it really takes to run ADBC in production

Brandon Wilcox - Gamebeast: Building AI-powered LiveOps & analytics for gaming

MORE COMING SOON

What to Expect

Deep technical sessions from engineers building & running analytics platforms in production

AI agents, model evaluation, real-time analytics, data lakes, & modern open-source infrastructure

Architecture, performance, scalability, reliability, & cost-without the vendor pitches

Meet engineers, architects, maintainers, & open-source contributors building the next generation of data systems

Who Should Attend

Data engineers & analytics engineers

Platform engineers working on data infrastructure

Architects & technical decision-makers designing analytics systems

Anyone interested in the intersection of analytics, AI, & modern data platforms