Unity Gateway Basics

Unity Gateway extends Unity Catalog governance to AI traffic. Unity Catalog already governs your models, MCP services, functions, and connections as securable objects; Unity Gateway adds a central control plane over the traffic to them, enforcing routing, rate limits, budgets, usage tracking, and **service policies** (guardrails) on every request and response.

This lab introduces the fundamentals through a short lecture and then puts them into practice with a hands-on demo. In the demo, you govern a real agentic application, one that generates Databricks-native diagrams as code, by routing it through Unity Gateway and progressively hardening its governance: creating a model service, granting permissions, adding inference tables, rate limits, a hallucination guardrail policy, traffic splitting across Claude models, and fallback routing. Finally, you explore the `system.ai` and `system.ai_gateway` schemas to see how telemetry and observability complement payload-level inference logging.

By the end of the lab, you will understand how asset, traffic, and behavior governance combine into a single control plane for AI, and how to apply those controls to a production-style generative AI application on Databricks.

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.