Governed Orchestration Architecture

← All Interactive Pages

Governed Orchestration Architecture

A comprehensive guide to building governed AI applications on Databricks. Understand how authentication flows, MCP integration, Model Serving, and AI Gateway work together for secure, scalable orchestration.

The "mother of all" scenarios: stitching together Databricks services with proper auth flows

↓ Explore the architecture

Architecture Components

All the pieces that come together in a governed AI application. Each component has specific authentication requirements.

Entry Points
🌐
External App
Token Exchange
📱
Databricks App
Native Auth
Model Serving (Deployment)
🤖
Custom Models
Agents, MLflow
🧠
Foundation Models
Hosted LLMs
🌉
AI Gateway
External LLMs
Authentication Methods (Agent → Resources)
Automatic
Passthrough
👤
OBO
User Identity
🔑
Manual
Credentials
MCP Servers & Resources
🔮
Genie
Analytics
🔍
Vector Search
Retrieval
⚙️
UC Functions
Tools
📊
DBSQL
Queries
🔗
External MCP
UC HTTP Conn
📦
Custom MCP
Databricks Apps
🗃️
Lakebase (Postgres)
Agent Memory • OLTP State • OAuth/Native Auth
Governance Layer
🛡️
Unity Catalog
Permissions, ABAC, Row Filters, Column Masks, Lineage

Three Authentication Scenarios

Scenario A: External App → Databricks

Your application runs OUTSIDE Databricks and needs to call Databricks APIs.

  • OAuth Token Exchange — IdP token → Databricks token (requires Federation Policy)
  • Native OAuth with Entra — Azure AD direct integration
  • Server-side handling — Tokens managed on backend, never exposed to browser

Scenario B: Agent → Resources

Your agent runs ON Databricks (Model Serving) and needs to access resources.

  • Automatic Authentication Passthrough
  • On-Behalf-Of-User (OBO)
  • Manual Authentication
  • Declared at logging time

Scenario C: Databricks App → Resources

Your web app runs ON Databricks (Apps platform) and needs to access resources.

  • Native OAuth (automatic)
  • Unity Catalog integration
  • Databricks SQL access
  • Streamlit, Dash, Gradio, React
📚 Databricks Apps Docs →

🗃️ Lakebase: Managed Postgres for AI Applications

Lakebase is a fully-managed Postgres OLTP database. Register in Unity Catalog for unified governance, permissions, lineage, and cross-source analytics alongside your lakehouse data.

🧠 Agent Memory
Short-term (session) & long-term (cross-session) memory with checkpointing
⚡ Online Feature Store
Low-latency feature serving for real-time ML models
💾 OLTP State
Fast transactional data access for apps and agents
OAuth (U2M / M2M)
  • 1-hour tokens as DB password
  • User, Group, or Service Principal
  • Requires SSL connection
Native Postgres Password
  • For apps that can't rotate tokens
  • Standard CREATE ROLE
  • Enable via instance settings
🛡️ UC Registration 🧠 Agent Memory ⚡ Online Features 🔐 Auth Docs

Deep Dive Topics

Explore each aspect of the architecture with interactive scrollytelling visualizations.