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databricks-solutions/ai-platform-kit

开发工具

本页由 AI 翻译,技术细节请以原文为准。 查看原文

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AI驱动的Databricks平台工程——配置工作区、配置Unity Catalog、管理身份与治理,以及在Azure、AWS和GCP之间建立网络,全部通过自然流程......

概览

通过自然语言与编码代理(Claude Code、Codex、Cursor、Copilot、Gemini等)配置工作区、配置Unity Catalog、搭建网络、管理组和权限管理。 作为Databricks AI开发套件的姊妹:该套件为编码代理提供Databricks专属的平台构建技能,而该套件则专注于平台本身的搭建——工作空间、Unity 目录、身份以及跨Azure、AWS和GCP的网络。 为什么大家都在使用Databricks的AI平台套件?——简要介绍该套件的功能及使用方法。

概述(AI 翻译)

** AI 驱动的 Databricks 平台工程。** 配置工作区、配置 Unity 目录、搭建网络、管理组和权限——所有这些都通过自然语言与你的编码代理(Claude Code、Codex、Cursor、Copilot、Gemini 等)进行。

Databricks AI 开发套件的兄弟:该套件为编码代理提供 Databricks 专属技能,用于在平台上构建,而该套件则专注于搭建平台本身——工作区、Unity 目录、身份以及跨 Azure、AWS 和 GCP 的网络。

观看概览

为什么大家都在使用Databricks AI平台套件? ——简要介绍该套件的功能及使用方法。

它的作用

告诉你的经纪人你需要什么,剩下的由他们帮你处理:

  • Workspace 配置 — VNet/VPC 注入,跨 Azure、AWS、GCP 的安全集群连接
  • Unity 目录 — 主观设置:自管理元存储、每个环境目录、外部位置、奖章模式、湖屋联合
  • 身份与治理 — 账户级 SCIM 组、分级 RBAC、作业服务主体
  • 工作空间配置 — SQL 仓库、集群策略、秘密范围、IP 访问列表

本页由 AI 翻译,技术细节请以原文为准。

README

以下为原文 README 节选,完整内容请查看原文。

Databricks Platform Kit

AI-powered Databricks platform engineering. Provision workspaces, configure Unity Catalog, set up networking, manage groups and permissions — all through natural language with your coding agent (Claude Code, Codex, Cursor, Copilot, Gemini, and more).

Sibling to the Databricks AI Dev Kit: where that kit gives coding agents Databricks-specific skills for building on the platform, this kit focuses on standing up the platform itself — workspaces, Unity Catalog, identity, and networking across Azure, AWS, and GCP.

Watch the overview

Why Is Everyone Using the Databricks AI Platform Kit? — a short walkthrough of what the kit does and how to use it.

What it does

Tell your agent what you need, and it handles the rest:

  • Workspace provisioning — VNet/VPC injection, Secure Cluster Connectivity across Azure, AWS, GCP
  • Unity Catalog — opinionated setup: self-managed metastore, per-env catalogs, external locations, medallion schemas, Lakehouse Federation
  • Identity & governance — account-level SCIM groups, tiered RBAC, service principals for jobs
  • Workspace config — SQL warehouses, cluster policies, secret scopes, IP access lists
  • Private networking — private link (AWS), Private Endpoints (Azure), Private Service Connect (GCP), hub-spoke, NCC for serverless connectivity (when you need it)
  • Built-in verification — a 3-path test (classic cluster + serverless SQL warehouse + serverless notebook job) designed to catch common configuration failures after a deploy (it does not guarantee correctness or fitness for any particular use)

The agent writes the Terraform and SDK calls from scratch based on your specific requirements — no rigid templates to fill in.

Architecture

.claude/skills/                      # 6 focused skills
  platform-provisioning/             #   Workspace creation + deploy
    SKILL.md                         #     Shared workflow + interaction guidance
    AZURE.md / AWS.md / GCP.md       #     Cloud-entry navigation files
    {azure,aws,gcp}-1-auth.md        #     Auth setup per cloud
    {azure,aws,gcp}-2-deploy.md      #     Deploy patterns per cloud
    {azure,aws,gcp}-3-gotchas.md     #     Sharp edges per cloud
  unity-catalog-setup/               #   Metastore, catalogs, governance
    SKILL.md + AZURE.md / AWS.md / GCP.md
  identity-governance/               #   Groups, users, SPs, RBAC
    SKILL.md                         #     Cloud-agnostic
  workspace-config/                  #   SQL warehouses, policies, secrets
    SKILL.md                         #     Cloud-agnostic
  private-networking/                #   Private link, hub-spoke, NCC, PSC
    SKILL.md + AZURE.md / AWS.md / GCP.md
在 GitHub 查看完整 README

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安装

npx skillfish add databricks-solutions/ai-platform-kit
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