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Azure Container Apps is a serverless container platform that simplifies the deployment and scaling of microservices and AI-powered applications. With native support for GPU workloads, seamless integration with Azure AI services, and flexible deployment options, it is an ideal platform for building intelligent, cloud-native solutions.
GPU-powered inference
Use GPU accelerated workload profiles to meet a variety of your AI workload needs, including:
- Dedicated GPUs: best for continuous, low-latency inference scenarios.
- Scale to zero: automatically scale down idle GPU resources to minimize costs.
Deploying Azure AI Foundry models
Azure Container Apps integrates with Azure AI Foundry, which enables you to deploy curated AI models directly into your containerized environments. This integration simplifies model deployment and management, making it easier to build intelligent applications on Container Apps.
Sample projects
The following are a few examples that demonstrate AI integration with Azure Container Apps. These samples showcase various AI capabilities, including OpenAI integration, multi-agent coordination, and retrieval-augmented generation (RAG) using Azure AI Search. For more samples, visit the template library.
| Sample | Description |
|---|---|
| Host an MCP server | Demonstrates multi-agent coordination using the MCP protocol with Azure OpenAI and GitHub models in Container Apps. |
| MCP client and server | .NET-based MCP agent app using Azure OpenAI with a TypeScript MCP server, both hosted on ACA. |
| Remote MCP server | TypeScript-based MCP server template for Container Apps, ideal for building custom AI toolchains. |