maf-online-endpoint Skill
Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project. Wraps any workflow into an init()/run() scoring script, creates conda environment, endpoint and deployment YAMLs, deploy script, and assigns RBAC. Supports managed identity a Published by microsoft in promptflow.
What is maf-online-endpoint Skill?
Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project. Wraps any workflow into an init()/run() scoring script, creates conda environment, endpoint and deployment YAMLs, deploy script, and assigns RBAC. Supports managed identity a Published by microsoft in promptflow. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Deployment use cases
Technical details
- Install or run with Copy skill directory
When to use maf-online-endpoint Skill
- Use it for deployment.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/promptflow
- Skill file: .github/skills/maf-online-endpoint/SKILL.md
What it does
Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project. Wraps any workflow into an init()/run() scoring script, creates conda environment, endpoint and deployment YAMLs, deploy script, and assigns RBAC. Supports managed identity a
Skill instructions
Deploy MAF Workflow as a Managed Online Endpoint This skill wraps a Microsoft Agent Framework (agent-framework) workflow into a managed online endpoint using the standard scoring-script pattern (init() / run()), following the patterns from the azureml-examples managed endpoint samples. The endpoint can be deployed to either: | Deployment Target | Description | |-------------------|-------------| | Azure Machine Learning workspace | Standalone AML workspace — user provides subscription, resource group, and workspace name | | Azure AI Foundry hub-based project | An AI project living under a Foundry hub — the project name is the workspace name for az ml commands | Both targets produce the same generated files (online-deployment/ directory) and use the same az ml CLI / azure-ai-ml Python SDK. The difference is in how the workspace is identified and RBAC scope. Overview The deployment creates all files in an online-deployment/ subdirectory under the project root: <project-root/ workflow.py
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Frequently asked questions
What is maf-online-endpoint?
maf-online-endpoint is a open-source AI agent skill with Copy skill directory. Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project.
Who is maf-online-endpoint best for?
maf-online-endpoint is best for reusing agent instructions, scripts, and references, deployment workflows.
How do I install maf-online-endpoint?
Install or run maf-online-endpoint using Copy skill directory. Check maf-online-endpoint for the latest setup command.
Is maf-online-endpoint actively maintained?
maf-online-endpoint may need a closer maintenance check before production use.
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