Production Lakebase Patterns: OAuth Token Lifecycle, Async Pooling, and Caching for Databricks Apps

Lakebase gives you PostgreSQL on Databricks, but production applications need patterns the documentation doesn't cover. From deploying a conversation persistence layer for an energy sector knowledge assistant, we share battle-tested solutions: Proactive OAuth token refresh that recreates connection pools before credentials expire, async connection pooling with psycopg3 sized for Databricks Apps concurrency, LRU caching with TTL for high-frequency thread lookups, and upsert patterns with conflict resolution for concurrent agent writes. Every pattern is production code running on Databricks Apps today.

This lightning talk is for developers who've tried Lakebase in a notebook and want to know what it takes to run it in a real application with real users.