Azure Container Apps for AI Agents

Name: Azure Container Apps for AI Agents
Rating: 4.5 (43 reviews)

Deploy, scale, and productionize Azure AI Agents using Azure Container Apps with real-world cloud practices.

Created byKuljot Singh Bakshi | 70,000+ Enrollments Worldwide

Last updated 5/2026

English

English [Auto],

What you'll learn

Deploy and scale Azure AI Agents on Azure Container Apps with real-world production patterns.
Implement autoscaling, revisions, and secrets management to handle enterprise workloads.
Integrate Azure OpenAI, storage, and event-driven triggers into containerized AI agent workflows.
Design a production-ready architecture that balances cost, performance, and scalability.
Troubleshoot, monitor, and optimize Azure Container Apps for AI workloads in production.

Course content

9 sections • 29 lectures • 7h 15m total length

Course Introduction4:07
Learn to turn works on my machine into scalable production with Azure Container Apps, exploring automatic scaling, canary deployments, secret management, and multi-container AI workflows.

Evolution of Software Architecture32:18
Explore the evolution of software architecture from monolithic apps to microservices and serverless, and learn how containers and Azure Container Apps enable scalable orchestration.
Introduction to ACA and Container Orchestration23:14
Discover Azure Container Apps as a serverless, event-driven container orchestration platform built on Kubernetes, enabling flexible microservices, blue-green deployments and traffic splitting, with simplified routing for modern apps.
ACA Essentials: Environments, Replicas, Revisions & More26:52
Learn how Azure container apps use environments as boundaries with container apps, revisions, replicas, blue-green and canary deployments, and workload vs consumption plan for scalable serverless workloads.
Kubernetes v/s Azure Container Apps13:34
Compare Azure container apps and AKS for container orchestration, highlighting abstraction, serverless deployment, and tradeoffs. Discover when ACA suits simple, cost-effective workloads and AKS suits complex enterprise microservices.

Lab: Deploying ACA Environment and Azure Container Registry (ACR) (Hands-On Lab)22:21
Deploy and manage a serverless azure container apps environment with a Docker Hub image, push to azure container registry, enable public ingress, and monitor via a log analytics workspace.
What We Will Be Building: "Architectural Pit-Stop"3:26
Clone the public repo, build and push the chat app image to Azure Container Registry, then deploy to Azure Container Apps with a system assigned managed identity.
Lab: Deploying Azure AI Foundry and GPT LLM (Hands-On Lab)12:07
Deploy an Azure AI Foundry hub and project to host a GPT 4.1 model in a serverless, vendor-agnostic, multi-modal environment using the AI Foundry portal.
Lab: Building and Pushing Container Image From Docker to ACR (Hands-On Lab)10:56
Build and push a docker image of the Azure OpenAI chat app to Azure Container Registry, configuring environment variables, wiring the React frontend to Azure AI Foundry, and testing locally.
Lab: Deploying ACR Image as an Azure Container App (Hands-On Lab)11:56
Deploy an image from Azure Container Registry to an Azure Container Apps environment by configuring a system assigned managed identity and creating the container app in the portal.

Module Outcome: "Architectural Pit-Stop"3:21
Dive into Azure container apps with labs on environment variables, secrets, and key vault integration, deploying a Python backend with Azure AI Foundry GPT LM and blue-green revisions using GPT-4.
Lab: Environment Variables and Secrets in Azure Container Apps (Hands-On Lab)18:01
Demonstrate injecting environment variables and secrets at runtime in Azure container apps using a python flask backend that calls the GPT LLM via /chat.
Introduction to Azure Key Vault10:20
Explore how Azure Key Vault acts as a secret store for keys and certificates, using managed identities to securely access secrets from Azure Container Apps and Azure Container Registry.
Lab: Using Azure Key Vault Secret Store with ACA (Hands-On Lab)23:31
Learn to integrate Azure key vault secret store with Azure container apps by configuring secrets, using a user assigned managed identity, and deploying container app that accesses GPT 4.1 model.
Lab: Revisions and Traffic Splitting with ACA (Hands-On Lab)37:16
Perform a hands-on lab on blue-green and canary deployments with Azure Container Apps to route traffic between GPT 4.1 and GPT 4 models using revisions, labels, and traffic weights.

What We Will be Building: "Architectural Pit-Stop"2:52
Explore multi-container design patterns in Azure container apps by deploying a frontend React SPA and a backend Python Flask service, connected to Azure OpenAI GPT, with selective ingress.
Lab: Deploying Simple Frontend-Backend AI App Setup (Hands-On Lab)18:26
Explore the front end back end container design pattern by building a Flask backend and a React frontend with nginx proxy inside Azure Container Apps, using internal ingress.

What We Will be Building: "Architectural Pit-Stop"4:22
Build an end-to-end retrieval augmented generation pipeline with a vector database, sidecar loader, storage via Azure File Share, and a Flask backend plus front-end container enabling chat on private documents.
Introduction to RAG (Retrieval Augmented Generation)16:08
Understand retrieval augmented generation (rag) to power a chatbot with your own data, using the three components: retrieval, augmentation, and generation, aided by vector embeddings and a vector database.
Lab: Introduction to QDrantDB Vector Database (Hands-On Lab)2:34
Explore QDrantDB, vector database, in a lab that guides you to run Docker image, access dashboard, and build collections of text and vector embeddings with SDK for Azure Container Apps.
Understanding Storage Mount in Azure Container Apps11:33
Learn how storage mounts with Azure Container Apps enable persistent data across replicas by mounting an Azure File Share to the container apps environment. Contrast this with ephemeral container storage.
Lab: Deploying Vector-Loader Sidecar Pattern with Storage Mount (Hands-On Lab)36:18
Deploy a two-container Azure container app with a vector loader sidecar and a quadrant vector database, using an Azure file share storage mount to persist embeddings.
Lab: Deploying End-to-End RAG Setup (Hands-On Lab)26:52
Deploy an end-to-end rag pipeline on azure container apps by integrating a vector db and loader sidecar with azure file share, building and deploying backend and frontend containers.

Introduction to Event Driven Scaling with ACA and KEDA11:03
Explore event-driven auto scaling in Azure Container Apps, using Azure Service Bus scale rules and Keda concepts to scale backend microservices from zero to multiple replicas during traffic surges.
Lab: Building an HTTP Scaling Rule (Hands-On Lab)21:54
Explore event driven auto scaling in Azure container apps with an http driven rule, deploying a backend and scaling from one to ten replicas based on http concurrency.
Lab: Building an Azure Blob Storage Scaler (Hands-On Lab)29:23
Perform a hands-on lab to build an event-driven Azure Blob storage scaler that scales Azure Container Apps replicas based on blob counts, using a caption generator with Azure OpenAI.

Requirements

Basic familiarity with cloud computing concepts (containers, APIs, scaling).
An Azure account (free trial is enough for practice).
Some experience with Python or JavaScript is helpful but not mandatory.
Curiosity and willingness to learn — all complex topics are explained step by step.

Description

Building AI agents is exciting — but getting them from “it works on my machine” to running reliably in production is the real challenge. This course, Productionizing Azure AI Agents with Azure Container Apps (ACA), is designed to help you bridge that gap.

You’ll start by understanding how Azure Container Apps provides a serverless, container-native platform that makes running AI agents at scale simple. From there, we’ll dive into deploying Azure AI Agents, integrating them with Azure OpenAI and Azure AI Foundry, and managing workloads in a production environment.

Key topics include:

Deploying AI agents into Azure Container Apps with best practices.
Using autoscaling, secrets, and revisions to ensure secure and scalable deployments.
Integrating event-driven triggers, storage, and APIs into your AI workflows.
Monitoring, troubleshooting, and optimizing for performance and cost efficiency.

By the end of this course, you’ll know how to design, deploy, and scale AI agents that are enterprise-ready — with the same tools used by modern cloud teams.

This course is perfect for AI developers, cloud engineers, and DevOps professionals who want hands-on experience with productionizing AI. Whether you’re building prototypes with Azure OpenAI or managing workloads for a team, this course will give you the skills and confidence to run AI agents in the cloud — the right way.

Who this course is for:

AI/ML developers who want to take their prototypes into production on Azure.
Cloud engineers curious about serverless containerization and AI workloads.
Software developers looking to integrate Azure OpenAI and agents into real-world applications.
DevOps and SRE professionals interested in scaling, monitoring, and securing AI agents.
Tech enthusiasts who want to explore how Azure Container Apps makes AI workloads production-ready.

Azure Container Apps for AI Agents

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 4min

Join the Discord Server Community1 lecture • 1min

Environment Set-Up2 lectures • 1min

Azure Container Apps (ACA) Essentials: ACA-1014 lectures • 1hr 36min

Module 1: Getting Started with Azure Container Apps (ACA)5 lectures • 1hr 1min

Module 2: Exploring Azure Container Apps5 lectures • 1hr 32min

Module 3: Multi-Container Patterns (Simple Frontend Backend AI App Design)2 lectures • 21min

Module 4: Multi-Container Patterns (RAG Design Pattern)6 lectures • 1hr 38min

Module 5: Event Driven Scaling with Azure Container Apps3 lectures • 1hr 2min

Requirements

Description

Who this course is for: