Azure API Management for AI Agents

Name: Azure API Management for AI Agents
Rating: 4.5 (138 reviews)

Azure API Management with Prompt Flows, and AI Agents in Azure Foundry & OpenAI - Secure, Scale and Productionize

Created byKuljot Singh Bakshi

Last updated 6/2026

English

What you'll learn

Design and deploy GenAI workflows using Azure OpenAI and Azure AI Foundry with production-grade reliability.
Secure and expose GenAI services via REST APIs using Azure API Management, with proper authentication and rate limiting.
Implement real-world API management techniques such as semantic caching, load balancing, and circuit breaker patterns.
Build scalable, versioned, and monetizable GenAI APIs with zero-downtime deployments and monitoring dashboards.

Course content

13 sections • 59 lectures • 11h 39m total length

Course Introduction5:59
Master deploying AI agents at scale with Azure API Management as a central gateway, integrating Azure AI Foundry and OpenAI while applying rate limits, circuit breakers, and semantic caching.

Introduction to Azure API Management and API Lifecycle11:22
API Lifecycle with Azure APIM : Understanding the "Design" Part9:04
Note: GitHub Repo For the Labs in the Course2:35
Lab 1: Deploying Azure API Management Instance10:54
API Lifecycle with Azure APIM : Understanding the "Develop" Part14:50
Lab 2: Building an HTTP API from Scratch in Azure APIM (Hands-On Lab)12:45
Lab 3: Building an API From OpenAPI Spec (Hands-On Lab)7:26
API Lifecycle with Azure APIM : Understanding the "Secure" Part9:44
API Lifecycle with Azure APIM : Understanding the "Publish" Part3:43
Explore the publish phase of the api lifecycle in azure api management, using the developer portal for self onboarding, discovery, testing, and subscription keys.
Lab 4: Accessing Azure APIM Dev Portal for Testing APIs (Hands-On Lab)14:34
Publish the developer portal, enable cors, and sign up as a user to test APIs in console. Activate starter and unlimited subscriptions and run Star Wars and Pet Store APIs.
Lab 5: Creating Rate Limiting and Caching Policies for our APIs (Hands-On Lab)13:22
API Lifecycle with Azure APIM : Understanding the "Scale" Part5:12
Explore how Azure API Management scales with multi-region deployments to achieve high availability and fault tolerance by replicating API backends and using Traffic Manager for health-based routing.
API Lifecycle with Azure APIM : Understanding the "Monitor and Analyze" Part3:47
Lab 6: Analyzing usage Metrics with App Insights and Log Analytics Workspace9:48

Introduction to Azure Managed Redis and Semantic Search11:37
Introduction to Vector Embeddings16:23
Lab 1: Making Use of Vector Embeddings from Azure OpenAI Resource (Hands-On Lab)7:48
Lab 2: Setting Up and Seeing Semantic Cache in Action (Hands-On Lab)24:37
Set up an Azure managed Redis with ready search and a text embedding A002 engine to power semantic caching for Azure OpenAI GPT four, delivering cache hits via vector similarity.

Introduction to Azure Content Safety with Azure APIM8:25
Learn to protect AI applications with Azure AI Content Safety Studio and Azure API Management, applying prompt shields, groundedness checks, and content safety policies to secure LLM workflows.
Lab 1: Deploying an Azure Content Safety Studio and Walkthrough (Hands-On Lab)10:16
Lab 2: Calling Azure Content Safety Studio with API Calls (Hands-On Lab)9:31
Lab 3: Configuring Content Safety APIM Policy (Hands-On Lab)17:40
Lab 4: Content Safety Filters in Action with Python Notebook (Hands-On Lab)7:34

Requirements

Knowledge about how the Web Works required
Knowledge about Restful APIs required
Knowledge about Generative AI required

Description

Welcome to Productionize Azure AI Foundry Agents with API Management — the ultimate hands-on course for deploying enterprise-ready GenAI services using Azure OpenAI, Azure AI Foundry, and Azure API Management (APIM).

Whether you're working with prompt flows, custom fine-tuned models, or building full-fledged AI agents, this course teaches you how to go from prototype to production-grade APIs — complete with authentication, rate limiting, caching, logging, and blue-green deployments.

You'll learn to:

Design scalable AI workflows using Azure AI Studio and Foundry
Use Azure API Management to securely expose LLM endpoints
Implement load balancing, versioning, and quota enforcement
Add semantic caching for faster and cheaper inferencing
Monitor usage with Azure Monitor and APIM analytics
Safely release updates using blue-green deployment strategies

By the end, you'll not only understand how to build intelligent solutions — you'll be able to serve them at scale across teams or customers using Azure-native best practices.

This course is ideal for cloud developers, AI engineers, DevOps professionals, and solution architects who want to productize AI with real-world infrastructure patterns.

If you're looking to level up from a working GenAI prototype to a highly available, secure, and monetizable AI service, this course is for you.

If you love the cloud, if you love GenAI, and if you love making things that actually work at scale — you're in the right place.

So gear up... we’re just getting started. See you inside!

Who this course is for:

Cloud developers and solution architects looking to productionize GenAI workflows with enterprise-grade security and scalability.
AI/ML engineers who want to turn their prompt flows and fine-tuned models into secure, monitored APIs using Azure.
Tech consultants and pre-sales engineers working with clients to build GenAI-powered solutions that meet governance and compliance needs.
DevOps and platform engineers interested in managing LLM-based services across regions with throttling, caching, and zero-downtime deployments.

Azure API Management for AI Agents

What you'll learn

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Course content

Introduction1 lecture • 6min

Join the Discord Community1 lecture • 1min

GenAI With APIM - Introduction to AI Specific APIM Use-Cases1 lecture • 24min

Azure API Management Basics14 lectures • 2hr 9min

GenAI With APIM - Azure OpenAI with APIM3 lectures • 47min

GenAI with APIM - Building an OpenAI API from Scratch (For Better Understanding)3 lectures • 32min

GenAI with APIM - AI Foundry with APIM4 lectures • 40min

GenAI with APIM - Semantic Cache with Azure Redis Cache4 lectures • 1hr

GenAI with APIM - Content Safety Filters5 lectures • 53min

GenAI with APIM - Multi-Region Load Balanced Deployments4 lectures • 46min

Requirements

Description

Who this course is for: