Modern applications need more than just robust business logic—they need to go live quickly and efficiently, leveraging AI to deliver smarter experiences faster.
Azure Container Apps paired with Azure Cognitive Services like Vision and OpenAI enables you to rapidly build, deploy, and scale AI-driven applications without complex infrastructure management.
In this hands-on workshop, you will see how Azure Container Apps simplifies building and deploying AI-enabled Apps to production. You are going to learn how to quickly integrate Semantic Kernel to run large language models (LLMs) during development and seamlessly transition to Azure Container Apps with OpenAI in production without changing your codebase.
Additionally, you’ll experience prompt engineering using Prompty, testing and optimizing prompts to enhance the accuracy of your AI assistant.
We will start by developing an AI-powered app locally using container technology and Ollama. Next, you are going to refine the AI prompt, and effortlessly move to Azure Container Apps. We will cover configuration management and versioning and you will also learn to use the Azure Container Apps extension of Dapr to easily implement state management in distributed applications. In addition, you will get a hands-on experience with Azure Container Apps features like autoscaling, blue/green deployments, and seamless integration with Azure OpenAI models.
Join this interactive workshop and go from zero on your laptop to a fully operational AI-powered application, architecture and implementation in Azure Container Apps, reducing your time to production drastically.
You will learn:
- Develop container-based distributed AI-enabled applications with Large Language Models and Azure AI services
- Deploying cloud applications to Azure Container Apps and utilize features of autoscaling and blue/green deployments for fast release to production
- Use architectural, design patterns and semantic kernel to transition efficiently between environments, from local development to staging and production