databricks-lakebase-autoscale

What problem does it solve?

This Skill helps you create and operate Databricks Lakebase Autoscaling (managed PostgreSQL) for OLTP workloads without breaking authentication or connection lifecycles.

Core Features & Use Cases

• Credential-safe connection setup: generates Lakebase-scoped database credentials using WorkspaceClient().postgres.generate_database_credential(...) and uses the returned token as the Postgres password (with sslmode=require).
• Production-ready resource orchestration: covers projects, branches, endpoints/compute sizing, scale-to-zero behavior, and update/create/delete flows including long-running operation handling with .wait().
• Practical reverse ETL integration: documents the Delta-to-Postgres synced-table model and the operational constraints (including CDF requirements for triggered/continuous modes).

Use Case Example: You need a dev/test workflow where production is protected, a temporary branch gets its own autoscaling endpoint, your app connects reliably using rotating credentials, and you sync curated Delta tables into Lakebase for low-latency reads.

Quick Start

Tell the AI: “Set up a Lakebase Autoscaling project with a protected production branch and an autoscaling read-write endpoint sized for 1–8 CU, then show the Python psycopg pool + OAuth connection pattern using a freshly minted Lakebase-scoped credential.”