Anna Stepanyan

Developers branch their code constantly, but the database has always been the exception: shared, stateful, and a constant source of friction. Someone runs a migration in the dev environment and breaks everyone else's work. Test data gets polluted. Schema changes get deferred because coordinating them is painful. Lakebase branching fixes this by letting you spin up an isolated, zero-copy clone of your database in seconds, one per feature branch, one per pull request, one per developer if you want. In this lightning talk, you'll see how database branching slots into the workflows you already use: local development, CI pipelines, and staging environments, without the overhead of maintaining separate database instances. The result is a development workflow where the database finally moves at the same speed as the rest of your stack.

Running Postgres in production gets harder as your application grows — logs pile up, metrics live in one tool, schema changes live in another, and when something breaks, you are stuck stitching it all together under pressure. This session shares practical tips and tricks for getting ahead of common Postgres operational challenges — we will cover how to spot configuration issues before they hit production, how to unblock application updates when schema changes go sideways, and how to quickly connect application failures back to the database changes that caused them. Along the way, we will show how bringing Postgres operational data together with modern AI tooling can take a lot of the manual work out of diagnostics — so you spend less time hunting for root causes and more time shipping. Whether you are running a handful of Postgres instances or managing them at scale, you will leave with concrete techniques you can apply to your own environment.