---
id: azure-mgmt-batchai
version: "7.0.0"
license: MIT License
license_treatment: permissive
maintenance: active
---

# azure-mgmt-batchai — Microsoft Azure Batch AI Management Client Library for Python

License: permissive · Maintenance: active · Downloads: 6.7M/mo

## What it is and what it does

Azure Batch AI Management is a Python SDK for controlling Batch AI compute resources on Microsoft Azure. It provides client libraries to create and manage clusters, file servers, jobs, experiments, and workspaces through the Azure Resource Manager API. The package wraps Azure's REST endpoints and handles authentication, polling, and error handling.

This package is deprecated and will receive no updates after 10-31-2024 except security patches. It was designed for distributed machine learning workloads on Azure infrastructure but has been superseded by azureml-core. Existing code using this library will continue to function if credentials and subscription IDs are properly configured, but new projects should adopt the replacement package and follow the published migration guide.

Use it for:

- Programmatically provision and tear down Batch AI clusters for temporary compute jobs in existing Azure infrastructure.
- Automate job submission and monitoring for distributed training workloads using the management API.
- Query usage limits and resource quotas for Batch AI workspaces in a subscription.
- Manage experiment grouping and job scheduling within Azure Batch AI workspaces via Python.
- Integrate Batch AI resource lifecycle into CI/CD pipelines or orchestration tools.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Manages Azure Batch AI resources (clusters, jobs, experiments, workspaces) via the Azure Resource Manager API; deprecated as of 10-31-2024 in favor of azureml-core.

No, unless maintaining legacy code. The package is officially deprecated as of 10-31-2024 and will receive no feature updates or non-security bug fixes. New projects should install azureml-core instead. Existing deployments can continue to function but should plan migration to avoid future support gaps.

## Install

pip install azure-mgmt-batchai
uv add azure-mgmt-batchai
poetry add azure-mgmt-batchai

## Installing azure-mgmt-batchai

Before you install: Low install friction with four lightweight runtime dependencies. Package is marked inactive (Development Status 7) and officially deprecated as of 10-31-2024; only security fixes are provided until that date. New projects should migrate to azureml-core instead.

License in practice: MIT License permits commercial and private use with minimal restrictions, requiring only license and copyright notice retention.

Quickstart:

pip install azure-mgmt-batchai

from azure.mgmt.batchai import BatchAIManagementClient
from azure.identity import DefaultAzureCredential

credential = DefaultAzureCredential()
client = BatchAIManagementClient(credential, subscription_id)

Requires Azure subscription credentials and Python 3.7 or later. Uses azure-identity for authentication, not legacy azure.common.credentials.

Verify before relying:

- Whether existing Batch AI workloads can be migrated to azureml-core without breaking changes beyond those documented in the migration guide.
- Timeline and support status for security fixes after 10-31-2024.
- Compatibility of async operations (aio namespace) with current Azure service endpoints.

## Package facts

- License: MIT License (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 6.7M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure batch ai management, azure resource manager batch ai, azure ml cluster management, azure job scheduling sdk, azure workspace management, batch ai python client, azure compute resource control, deprecated, azure-sdk, legacy

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