Skip to content

Latest commit

 

History

History
52 lines (34 loc) · 3.53 KB

index.md

File metadata and controls

52 lines (34 loc) · 3.53 KB
title layout nav_order
Overview
home
1

Lab: Deploy and run Java applications on Azure Container Apps

In this lab, you’ll learn how to deploy Java applications to Azure Container Apps and integrate them with additional Azure services. You’ll also deploy a copy of the Spring Petclinic Microservices sample workload to find out how Azure Container Apps supports Azure Spring Apps that use managed components.

What you’ll cover

As you work through the lab modules, you’ll explore the following:

  • A general introduction to the sample workload, the Spring applications that it’s composed of, and the related Azure services and resources you’ll use to deploy it
  • A walk-through on how to deploy the Spring Petclinic Microservices workload to Azure Container Apps
  • Detailed steps on enabling monitoring, end-to-end tracing, and Grafana dashboards for the deployed sample application
  • Instructions on how to securely connect applications and services by using managed identities
  • A walk-through on how to build intelligent Azure Spring Apps with Azure OpenAI Service
  • Instructions for automatically deploying applications to Azure
  • Guidance on building reliable Java apps on Azure Container Apps

You can review the contents of this lab as GitHub pages at the Java on ACA site.

Getting Started

Prerequisites

To run this lab, you’ll need:

  • A GitHub account.
  • An Azure subscription that grants you resource creation rights.

Region availability

  1. This lab uses Azure OpenAI Service. It also employs the gpt-4o and text-embedding-ada-002 models, which are not available in all Azure regions. Before deploying any resources or selecting a region, make sure to check for up-to-date region availability and for access to both models.

  2. This lab also uses Azure Database for MySQL - Flexible Server. Before deploying or selecting a region, be sure to verify the service is available in that region.

    {: .note }

    At the time of publishing (January 2025), we recommend using any of the following regions to help ensure that required features are available: West US, West US 2, East US 2, North Central US, Sweden Central.

Installation

Before running this lab, be sure that all the required tooling is available. We’ve provided three options:

  • [Use GitHub Codespaces (preferred)]({% link install.md %}#using-a-github-codespace), which will create a cloud-based development environment with the required tools installed and configured.
  • [Use Visual Studio Code with remote containers option]({% link install.md %}#using-visual-studio-code-with-remote-containers), which will create a Docker container on your local machine with the required tools preconfigured.
  • [Install all the tools on your local machine]({% link install.md %}#install-all-the-tools-on-your-local-machine).

We’ve tested this lab using GitHub Codespaces, which is the preferred option for running it.

You can find the full installation guidance and the options for running this lab in the [Installation]({% link install.md %}) instructions.