How to intermediate · 3 min read

How to manage Azure OpenAI quota

Quick answer

Use the Azure Portal or Azure CLI to monitor your Azure OpenAI quota and usage. Programmatically, leverage Azure SDK for Python to query quota details and implement usage tracking to avoid exceeding limits when calling AzureOpenAI APIs.

PREREQUISITES

Python 3.8+
Azure subscription with Azure OpenAI resource
Azure CLI installed and logged in
pip install azure-identity azure-mgmt-openai openai>=1.0

Setup Azure SDK and environment

Install the required Azure SDK packages and set environment variables for authentication. Use DefaultAzureCredential for seamless authentication in most environments.

bash

pip install azure-identity azure-mgmt-openai openai>=1.0

Step by step quota management

This example demonstrates how to authenticate with Azure, retrieve your Azure OpenAI resource quota, and track usage to prevent exceeding limits when calling the AzureOpenAI client.

python

import os
from azure.identity import DefaultAzureCredential
from azure.mgmt.openai import OpenAIManagementClient
from openai import OpenAI

# Set your Azure subscription ID and resource details
subscription_id = os.environ["AZURE_SUBSCRIPTION_ID"]
resource_group = os.environ["AZURE_RESOURCE_GROUP"]
resource_name = os.environ["AZURE_OPENAI_RESOURCE_NAME"]

# Authenticate with Azure
credential = DefaultAzureCredential()
client = OpenAIManagementClient(credential, subscription_id)

# Get quota details for the Azure OpenAI resource
quota = client.open_ai_resource.get(resource_group, resource_name)
print(f"Quota details: {quota}")

# Initialize OpenAI client for Azure OpenAI
client_openai = OpenAI(
    api_key=os.environ["AZURE_OPENAI_API_KEY"],
    base_url=os.environ["AZURE_OPENAI_ENDPOINT"],
    api_type="azure",
    api_version="2024-02-01"
)

# Example: simple usage tracking
usage_count = 0
usage_limit = 100000  # Example quota limit, adjust based on your subscription

if usage_count < usage_limit:
    response = client_openai.chat.completions.create(
        model=os.environ["AZURE_OPENAI_DEPLOYMENT"],
        messages=[{"role": "user", "content": "Hello, quota management!"}]
    )
    print(response.choices[0].message.content)
    usage_count += 1
else:
    print("Quota limit reached. Please wait or request a quota increase.")

output

Quota details: <azure.mgmt.openai.models.OpenAIResource object at 0x...>
Hello, quota management!

Common variations

Use Azure CLI commands like az openai account show-usage to check usage manually.
Implement async calls with OpenAI client for high-throughput applications.
Monitor quota via Azure Portal for real-time usage and alerts.

Troubleshooting quota issues

If you receive quota exceeded errors, verify your usage in the Azure Portal and consider requesting a quota increase.
Ensure your AZURE_OPENAI_API_KEY and AZURE_OPENAI_ENDPOINT are correct and have sufficient permissions.
Use exponential backoff and retry logic in your code to handle transient quota limits gracefully.

✅

Key Takeaways

Use Azure SDK for Python to programmatically monitor Azure OpenAI quota.
Track usage in your application to avoid exceeding quota limits.
Leverage Azure Portal and CLI for manual quota and usage monitoring.

Verified 2026-04 · gpt-4o, AzureOpenAI

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