gemAzure OpenAI

Enterprise-grade OpenAI models with Microsoft Azure compliance and global deployment

Enterprise-grade OpenAI models with Microsoft Azure infrastructure and compliance


Overview

Azure OpenAI Service provides REST API access to OpenAI's models including GPT-4, GPT-3.5, and embeddings through Microsoft's global Azure infrastructure. Perfect for enterprise deployments requiring compliance, data residency, and SLA guarantees.

!!! warning "Enterprise-Only Access" Azure OpenAI requires application approval and Azure subscription. Approval can take 1-2 weeks. Use Google AI Studio or Hugging Face for instant access during development.

Key Benefits

  • 🏢 Enterprise SLA: 99.9% uptime guarantee with Azure support

  • 🌍 Global Regions: 30+ Azure regions worldwide

  • 🔒 Compliance: SOC 2, HIPAA, ISO 27001, FedRAMP

  • 🔐 Azure Integration: Azure AD, Key Vault, Private Link

  • 💰 Enterprise Billing: Consolidated Azure billing

  • 🛡️ Data Residency: Control where data is processed

  • 📊 Azure Monitor: Built-in observability and logging

Use Cases

  • Enterprise Applications: SLA-backed production workloads

  • Regulated Industries: Healthcare, finance, government

  • Hybrid Cloud: Integration with existing Azure infrastructure

  • Multi-Region: Global deployments with data residency

  • Compliance Requirements: GDPR, HIPAA, SOC 2


Quick Start

1. Create Azure OpenAI Resource

Or use Azure Portalarrow-up-right:

  1. Search for "Azure OpenAI"

  2. Click "Create"

  3. Select subscription and resource group

  4. Choose region (eastus, westeurope, etc.)

  5. Name your resource

  6. Click "Review + Create"

2. Deploy a Model

Or via Azure Portal:

  1. Open your Azure OpenAI resource

  2. Go to "Deployments" → "Create new deployment"

  3. Select model (gpt-4o, gpt-4, gpt-35-turbo, etc.)

  4. Name deployment

  5. Set capacity (TPM quota)

3. Get Credentials


Regional Deployment

Available Regions

Region
Location
Models Available
Data Residency

East US

Virginia, USA

All models

USA

East US 2

Virginia, USA

All models

USA

South Central US

Texas, USA

All models

USA

West Europe

Netherlands

All models

EU

North Europe

Ireland

All models

EU

UK South

London, UK

All models

UK

France Central

Paris, France

All models

EU

Switzerland North

Zurich

All models

Switzerland

Sweden Central

Stockholm

All models

EU

Australia East

Sydney

All models

Australia

Japan East

Tokyo

All models

Japan

Canada East

Quebec

All models

Canada

Multi-Region Setup


Model Deployments

Available Models

Model
Description
Context
Best For
TPM Quota

gpt-4o

Latest flagship

128K

Complex reasoning

10K - 1M

gpt-4o-mini

Fast, cost-effective

128K

General tasks

10K - 10M

gpt-4-turbo

Previous flagship

128K

Advanced tasks

10K - 1M

gpt-4

Stable version

8K

Production

10K - 1M

gpt-35-turbo

Fast, affordable

16K

High-volume

10K - 10M

text-embedding-ada-002

Embeddings

8K

Vector search

10K - 10M

text-embedding-3-small

Small embeddings

8K

Efficient search

10K - 10M

text-embedding-3-large

Large embeddings

8K

Accuracy

10K - 10M

Deployment Quotas (TPM)

Multiple Model Deployments


Azure AD Authentication

Service Principal

User-Assigned Managed Identity


Private Endpoint & VNet Integration

Configure Private Endpoint

Private DNS Zone

VNet Integration in Code


Compliance & Security

Data Residency

Customer-Managed Keys (CMK)

Disable Public Network Access


Monitoring & Logging

Azure Monitor Integration

Diagnostic Logs


Cost Management

Pricing Model

Cost Tracking

Budget Alerts


Production Patterns

Pattern 1: High Availability Setup

Pattern 2: Load Balancing Across Deployments

Pattern 3: Quota Management


Troubleshooting

Common Issues

1. "Deployment Not Found"

Problem: Incorrect deployment name.

Solution:

2. "Rate Limit Exceeded (429)"

Problem: Exceeded TPM quota for deployment.

Solution:

3. "Resource Not Found"

Problem: Incorrect endpoint or resource deleted.

Solution:

4. "Invalid API Key"

Problem: API key rotated or incorrect.

Solution:


Best Practices

1. ✅ Use Managed Identity in Azure

2. ✅ Deploy Multiple Regions for HA

3. ✅ Use Private Endpoints for Security

4. ✅ Monitor Costs with Budgets

5. ✅ Enable Diagnostic Logging



Additional Resources


Need Help? Join our GitHub Discussionsarrow-up-right or open an issuearrow-up-right.

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