본문으로 건너뛰기
← 전체 뉴스
Databricks Blog2026년 10월 20일

How Hamlet uses Databricks Lakebase Postgres to test changes against production data

요약

Hamlet gives every pull request its own Lakebase Postgres branch of production data, so engineers can reproduce and test fixes against the exact data that caused a bug without touching production. AI coding agents run the pipelines and check their work on each branch before a person approves the merge, and Hamlet is now exploring Lakebase Search, branching for object storage, and a home for longer agentic jobs.

* Hamlet gives every pull request its own Lakebase Postgres branch of production data, so engineers test changes against the data that caused a bug without touching production. * AI coding agents run the pipelines and check their work on each branch before a person approves the merge. * Hamlet is exploring Lakebase Search for vector and text search in Postgres, branching for object storage and a home for longer agentic jobs.

관련 기사

News

MemCurrent: Designing Persistent Memory for Production Agents

databricks-blog1h ago
News

Introducing Agent Memory on Databricks

databricks-blog1h ago
News

HP가 Databricks CustomerLake로 AI 준비가 완료된 CDP를 구축하는 방법

databricks-blog19h ago
News

CustomerLake enters Beta: Leading enterprises going live with the Agentic CDP

databricks-blog20h ago