AWS Databricks Platform Architect - Mandarin Chinese

This tutorial explores how to build a full-stack Databricks App with Lakebase using a DevHub template and an AI coding agent. You will see how DevHub prompts, Databricks Apps, Lakebase, AppKit, and Declarative Automation Bundles work together to turn application requirements into a deployed, persistent CRUD application backed by managed Postgres.

Along the way, the tutorial deconstructs the generated application to explain how identity, application resources, database isolation, source structure, configuration, deployment, and testing fit together. Rather than providing a comprehensive treatment of each individual technology, the focus is on understanding the end-to-end development workflow and the architectural relationships behind the finished application.

本课程讲授如何构建能够记忆的 AI 智能体——既能在一次对话中记忆，也能跨会话记忆——并使用 Databricks Lakebase 作为持久化后端。学员将了解 LangGraph 的 Checkpointer 系统如何提供短期记忆（会话内的对话连续性），以及 LangGraph 的 Store 如何提供长期记忆（跨会话的用户偏好），二者均由 Lakebase Autoscaling 支撑。学员将在 notebook 中构建并测试这些记忆系统，通过 MLflow 跟踪观察智能体行为，并将一个完全有状态的智能体部署为 Databricks App。

注意：对于 SCORM 课件文件，请在完成内容后关闭 SCORM 窗口。请勿点击 ‘Next Lesson’ 按钮，否则可能会导致 SCORM 模块无法标记为已完成。

In this course, you will learn how to design, implement, and govern catalog structures and large-scale data organization on the Databricks Data Intelligence Platform. It offers a comprehensive view of Unity Catalog as the centralized governance layer for an enterprise lakehouse. Divided into five modules, it begins by placing Unity Catalog within the cloud deployment model — covering the Account Console, metastore creation, and the administrator role hierarchy. You will then translate organizational topology (business units, regions, and dev/QA/prod environments) into a scalable catalog and schema design using naming conventions, ownership patterns, and MANAGE delegation. The course then covers secure storage integration with storage credentials, external locations, the managed-storage hierarchy, managed versus external tables, and UC Volumes for non-tabular data. Next, you will apply access patterns and isolation strategies — the three-level GRANT chain, workspace-catalog binding, and schema-level Attribute-Based Access Control (ABAC) policies — to enforce fine-grained data protection at scale. Finally, the course closes with best practices for catalog design, automation, least-privilege permissions, and group-based access management.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.