simonjj explores how developers can deploy and manage AI agents like Goose on Azure Container Apps, taking advantage of serverless GPU resources and secure, scalable infrastructure for rapid innovation.

Building Agents on Azure Container Apps with Goose AI Agent, Ollama, and gpt-oss

Author: simonjj

Overview

Azure Container Apps (ACA) provides a new approach for developers to build and operate intelligent agents. Leveraging serverless scalability, GPU-on-demand, and robust enterprise isolation, ACA delivers a strong foundation for securely and cost-effectively running AI agents and inference workloads.

Challenges in Hosting AI Agents

  • Security: AI agents often require access to sensitive data and internal APIs, making robust security and data governance essential.
  • Flexibility: Developers want the ability to try different agentic frameworks without increasing operational burden or compromising isolation.
  • Simplicity and Performance: Managing scale, networking, and infrastructure should not impede iteration. Separating agent reasoning from inference backends can add complexity and latency.

ACA and Serverless GPUs for AI Agents

Azure Container Apps streamlines the experience of deploying both agentic logic and inference models inside one environment. Key features include:

  • Security & Data Governance: Run agents in isolated, private environments with control over identity and networking. Data stays inside your container boundary.
  • Serverless Cost Model: Scale down to zero when idle, pay only for what you use.
  • Simple Developer Experience: One-command deployments, integrated Azure identity, and networking. No manual setup or infrastructure management.
  • Inference with Serverless GPUs: Easily run open-source, community, or custom models (such as gpt-oss via Ollama) alongside your agent framework, avoiding third-party API costs and improving data privacy.

Deploying Goose AI Agent on ACA

The Goose AI Agent is an open-source, general-purpose agent framework from Block. It supports email integration, GitHub operations, CLI access, and system tool extensions. By deploying Goose on ACA, you get:

  • Serverless scaling and secure isolation
  • GPU-on-demand for inferencing
  • Rapid customization and iteration

Getting started: Use the Goose-on-ACA starter template to quickly set up your environment—includes model server, web UI, and CLI endpoints.

Benefits of ACA for Agentic Workloads

  • Always-On Availability: Run Goose agents continuously for asynchronous and long-lived tasks.
  • Cost Efficiency: Pay-per-use GPU eliminates expensive, hosted inference APIs.
  • Seamless Developer Experience: Minimal configuration; deploy full agentic systems in minutes.

Expanding Ecosystem

ACA is becoming a hub for both open-source and commercial agent frameworks, including n8n and Goose. With features like serverless scaling, GPU-on-demand, and complete network isolation, ACA empowers developers to innovate rapidly and securely, whether prototyping single agents or building complex automated solutions.

Key Takeaways

  • ACA enables secure, flexible, and efficient deployment of AI agents, reducing operational burden.
  • Goose, as an open-source agent framework, is optimized for quick deployment and extensive integration.
  • Serverless GPUs and isolated container environments on Azure simplify running custom and open-source models, maximizing privacy and cost-effectiveness.

Resources

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