Azure OpenAI Provider Guide¶

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.

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¶

# Via Azure CLI
az cognitiveservices account create \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --location eastus \
  --kind OpenAI \
  --sku S0

Or use Azure Portal:

Search for "Azure OpenAI"
Click "Create"
Select subscription and resource group
Choose region (eastus, westeurope, etc.)
Name your resource
Click "Review + Create"

2. Deploy a Model¶

# Deploy GPT-4o model
az cognitiveservices account deployment create \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --deployment-name gpt-4o-deployment \
  --model-name gpt-4o \
  --model-version "2024-08-06" \
  --model-format OpenAI \
  --sku-capacity 10 \
  --sku-name "Standard"

Or via Azure Portal:

Open your Azure OpenAI resource
Go to "Deployments" → "Create new deployment"
Select model (gpt-4o, gpt-4, gpt-35-turbo, etc.)
Name deployment
Set capacity (TPM quota)

3. Get Credentials¶

# Get endpoint
az cognitiveservices account show \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --query "properties.endpoint" --output tsv

# Get API key
az cognitiveservices account keys list \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --query "key1" --output tsv

4. Configure NeuroLink¶

# .env
AZURE_OPENAI_API_KEY=your_api_key_here
AZURE_OPENAI_ENDPOINT=https://my-resource.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT=gpt-4o-deployment

import { NeuroLink } from "@juspay/neurolink";

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        apiKey: process.env.AZURE_OPENAI_API_KEY,
        endpoint: process.env.AZURE_OPENAI_ENDPOINT,
        deployment: process.env.AZURE_OPENAI_DEPLOYMENT,
      },
    },
  ],
});

const result = await ai.generate({
  input: { text: "Hello from Azure OpenAI!" },
  provider: "azure-openai",
});

console.log(result.content);

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¶

const ai = new NeuroLink({
  providers: [
    // US deployments
    {
      name: "azure-us-east",
      config: {
        apiKey: process.env.AZURE_US_EAST_KEY,
        endpoint: "https://my-us-east.openai.azure.com/",
        deployment: "gpt-4o-deployment",
      },
      region: "us-east",
      priority: 1,
      condition: (req) => req.userRegion === "us",
    },

    // EU deployments
    {
      name: "azure-eu-west",
      config: {
        apiKey: process.env.AZURE_EU_WEST_KEY,
        endpoint: "https://my-eu-west.openai.azure.com/",
        deployment: "gpt-4o-deployment",
      },
      region: "eu-west",
      priority: 1,
      condition: (req) => req.userRegion === "eu",
    },

    // Asia deployments
    {
      name: "azure-japan",
      config: {
        apiKey: process.env.AZURE_JAPAN_KEY,
        endpoint: "https://my-japan.openai.azure.com/",
        deployment: "gpt-4o-deployment",
      },
      region: "japan",
      priority: 1,
      condition: (req) => req.userRegion === "asia",
    },
  ],
  failoverConfig: { enabled: true },
});

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)¶

Standard Tier Quotas (Tokens Per Minute):
- gpt-4o:              10K - 1M TPM
- gpt-4o-mini:         10K - 10M TPM
- gpt-4-turbo:         10K - 1M TPM
- gpt-35-turbo:        10K - 10M TPM
- embeddings:          10K - 10M TPM

Request quota increase via Azure Portal if needed.

Multiple Model Deployments¶

const ai = new NeuroLink({
  providers: [
    // GPT-4o for complex tasks
    {
      name: "azure-gpt4o",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-4o-deployment",
      },
      model: "gpt-4o",
    },

    // GPT-4o-mini for general tasks
    {
      name: "azure-gpt4o-mini",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-4o-mini-deployment",
      },
      model: "gpt-4o-mini",
    },

    // GPT-3.5-turbo for high-volume
    {
      name: "azure-gpt35",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-35-turbo-deployment",
      },
      model: "gpt-35-turbo",
    },
  ],
});

// Route based on task complexity
const complexTask = await ai.generate({
  input: { text: "Complex analysis..." },
  provider: "azure-gpt4o",
});

const simpleTask = await ai.generate({
  input: { text: "Simple query..." },
  provider: "azure-gpt4o-mini",
});

Azure AD Authentication¶

Managed Identity (Recommended)¶

import { DefaultAzureCredential } from "@azure/identity";

const credential = new DefaultAzureCredential();

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        credential, // Use Azure AD instead of API key
        endpoint: process.env.AZURE_OPENAI_ENDPOINT,
        deployment: process.env.AZURE_OPENAI_DEPLOYMENT,
      },
    },
  ],
});

Service Principal¶

import { ClientSecretCredential } from "@azure/identity";

const credential = new ClientSecretCredential(
  process.env.AZURE_TENANT_ID!,
  process.env.AZURE_CLIENT_ID!,
  process.env.AZURE_CLIENT_SECRET!,
);

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        credential,
        endpoint: process.env.AZURE_OPENAI_ENDPOINT,
        deployment: process.env.AZURE_OPENAI_DEPLOYMENT,
      },
    },
  ],
});

User-Assigned Managed Identity¶

import { ManagedIdentityCredential } from "@azure/identity";

const credential = new ManagedIdentityCredential({
  clientId: process.env.AZURE_CLIENT_ID,
});

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        credential,
        endpoint: process.env.AZURE_OPENAI_ENDPOINT,
        deployment: process.env.AZURE_OPENAI_DEPLOYMENT,
      },
    },
  ],
});

Private Endpoint & VNet Integration¶

Configure Private Endpoint¶

# Create private endpoint
az network private-endpoint create \
  --name my-openai-pe \
  --resource-group my-resource-group \
  --vnet-name my-vnet \
  --subnet my-subnet \
  --private-connection-resource-id "/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/my-openai" \
  --group-id account \
  --connection-name my-openai-connection

Private DNS Zone¶

# Create private DNS zone
az network private-dns zone create \
  --resource-group my-resource-group \
  --name privatelink.openai.azure.com

# Link to VNet
az network private-dns link vnet create \
  --resource-group my-resource-group \
  --zone-name privatelink.openai.azure.com \
  --name my-openai-dns-link \
  --virtual-network my-vnet \
  --registration-enabled false

VNet Integration in Code¶

// No code changes needed - just use private endpoint URL
const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: "https://my-openai.privatelink.openai.azure.com/", // Private endpoint
        deployment: "gpt-4o-deployment",
      },
    },
  ],
});

Compliance & Security¶

Data Residency¶

// Ensure EU data stays in EU
const ai = new NeuroLink({
  providers: [
    {
      name: "azure-eu",
      config: {
        apiKey: process.env.AZURE_EU_KEY,
        endpoint: "https://my-eu-resource.openai.azure.com/",
        deployment: "gpt-4o-deployment",
        region: "westeurope", // EU region
      },
      condition: (req) => req.userRegion === "EU",
      compliance: ["GDPR", "ISO27001", "SOC2"],
    },
  ],
});

Customer-Managed Keys (CMK)¶

# Enable CMK with Azure Key Vault
az cognitiveservices account update \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --encryption KeyVault \
  --encryption-key-name my-key \
  --encryption-key-source Microsoft.KeyVault \
  --encryption-key-vault https://my-vault.vault.azure.net/

Disable Public Network Access¶

# Restrict to private endpoint only
az cognitiveservices account update \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --public-network-access Disabled

Monitoring & Logging¶

Azure Monitor Integration¶

import { ApplicationInsights } from "@azure/monitor-opentelemetry";

const appInsights = new ApplicationInsights({
  connectionString: process.env.APPLICATIONINSIGHTS_CONNECTION_STRING,
});

appInsights.start();

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_OPENAI_ENDPOINT,
        deployment: process.env.AZURE_OPENAI_DEPLOYMENT,
      },
    },
  ],
  onSuccess: (result) => {
    // Log to Application Insights
    appInsights.trackEvent({
      name: "AI_Generation_Success",
      properties: {
        provider: result.provider,
        model: result.model,
        tokens: result.usage.totalTokens,
        cost: result.cost,
        latency: result.latency,
      },
    });
  },
  onError: (error, provider) => {
    // Log errors
    appInsights.trackException({
      exception: error,
      properties: { provider },
    });
  },
});

Diagnostic Logs¶

# Enable diagnostic logs
az monitor diagnostic-settings create \
  --name my-diagnostic-settings \
  --resource "/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/my-openai" \
  --logs '[{"category":"Audit","enabled":true},{"category":"RequestResponse","enabled":true}]' \
  --workspace "/subscriptions/{sub}/resourceGroups/{rg}/providers/microsoft.operationalinsights/workspaces/my-workspace"

Cost Management¶

Pricing Model¶

Azure OpenAI Pricing (as of 2025):

GPT-4o:
- Input:  $2.50 per 1M tokens
- Output: $10.00 per 1M tokens

GPT-4o-mini:
- Input:  $0.15 per 1M tokens
- Output: $0.60 per 1M tokens

GPT-4-turbo:
- Input:  $10.00 per 1M tokens
- Output: $30.00 per 1M tokens

GPT-3.5-turbo:
- Input:  $0.50 per 1M tokens
- Output: $1.50 per 1M tokens

Embeddings (ada-002):
- $0.10 per 1M tokens

Cost Tracking¶

class AzureCostTracker {
  private dailyCost = 0;
  private monthlyCost = 0;

  recordUsage(result: any) {
    const inputTokens = result.usage.promptTokens;
    const outputTokens = result.usage.completionTokens;

    // Calculate cost based on model
    let cost = 0;
    if (result.model === "gpt-4o") {
      cost =
        (inputTokens / 1_000_000) * 2.5 + (outputTokens / 1_000_000) * 10.0;
    } else if (result.model === "gpt-4o-mini") {
      cost =
        (inputTokens / 1_000_000) * 0.15 + (outputTokens / 1_000_000) * 0.6;
    }

    this.dailyCost += cost;
    this.monthlyCost += cost;

    return cost;
  }

  getStats() {
    return {
      daily: this.dailyCost,
      monthly: this.monthlyCost,
    };
  }
}

const costTracker = new AzureCostTracker();

const result = await ai.generate({
  input: { text: "Your prompt" },
  provider: "azure-openai",
  enableAnalytics: true,
});

const cost = costTracker.recordUsage(result);
console.log(`Request cost: $${cost.toFixed(4)}`);

Budget Alerts¶

# Create budget in Azure
az consumption budget create \
  --budget-name openai-monthly-budget \
  --amount 1000 \
  --time-grain Monthly \
  --start-date 2025-01-01 \
  --end-date 2025-12-31 \
  --resource-group my-resource-group

Production Patterns¶

Pattern 1: High Availability Setup¶

const ai = new NeuroLink({
  providers: [
    // Primary region
    {
      name: "azure-primary",
      priority: 1,
      config: {
        apiKey: process.env.AZURE_PRIMARY_KEY,
        endpoint: process.env.AZURE_PRIMARY_ENDPOINT,
        deployment: "gpt-4o-deployment",
      },
    },

    // Failover region
    {
      name: "azure-secondary",
      priority: 2,
      config: {
        apiKey: process.env.AZURE_SECONDARY_KEY,
        endpoint: process.env.AZURE_SECONDARY_ENDPOINT,
        deployment: "gpt-4o-deployment",
      },
    },
  ],
  failoverConfig: {
    enabled: true,
    maxAttempts: 3,
    retryDelay: 1000,
  },
  healthCheck: {
    enabled: true,
    interval: 60000,
  },
});

Pattern 2: Load Balancing Across Deployments¶

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-deployment-1",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-4o-deployment-1",
      },
      weight: 1,
    },
    {
      name: "azure-deployment-2",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-4o-deployment-2",
      },
      weight: 1,
    },
    {
      name: "azure-deployment-3",
      config: {
        apiKey: process.env.AZURE_API_KEY,
        endpoint: process.env.AZURE_ENDPOINT,
        deployment: "gpt-4o-deployment-3",
      },
      weight: 1,
    },
  ],
  loadBalancing: "round-robin",
});

Pattern 3: Quota Management¶

class QuotaManager {
  private tokensThisMinute = 0;
  private minuteStart = Date.now();
  private quotaLimit = 100000; // 100K TPM

  async checkQuota(estimatedTokens: number): Promise<boolean> {
    const now = Date.now();

    // Reset if new minute
    if (now - this.minuteStart > 60000) {
      this.tokensThisMinute = 0;
      this.minuteStart = now;
    }

    // Check if within quota
    return this.tokensThisMinute + estimatedTokens <= this.quotaLimit;
  }

  recordUsage(tokens: number) {
    this.tokensThisMinute += tokens;
  }

  getRemaining(): number {
    return Math.max(0, this.quotaLimit - this.tokensThisMinute);
  }
}

const quotaManager = new QuotaManager();

async function generateWithQuota(prompt: string) {
  const estimated = prompt.length / 4; // Rough estimate

  if (!(await quotaManager.checkQuota(estimated))) {
    throw new Error("Quota exceeded, please wait");
  }

  const result = await ai.generate({
    input: { text: prompt },
    provider: "azure-openai",
    enableAnalytics: true,
  });

  quotaManager.recordUsage(result.usage.totalTokens);
  return result;
}

Troubleshooting¶

Common Issues¶

1. "Deployment Not Found"¶

Problem: Incorrect deployment name.

Solution:

# List all deployments
az cognitiveservices account deployment list \
  --name my-openai-resource \
  --resource-group my-resource-group

# Use exact deployment name in config
AZURE_OPENAI_DEPLOYMENT=gpt-4o-deployment  # ✅ Exact name

2. "Rate Limit Exceeded (429)"¶

Problem: Exceeded TPM quota for deployment.

Solution:

# Increase quota via Azure Portal:
# 1. Go to resource → Deployments
# 2. Edit deployment
# 3. Increase TPM capacity
# Or request quota increase via support ticket

3. "Resource Not Found"¶

Problem: Incorrect endpoint or resource deleted.

Solution:

# Verify resource exists
az cognitiveservices account show \
  --name my-openai-resource \
  --resource-group my-resource-group

# Check endpoint format
AZURE_OPENAI_ENDPOINT=https://my-resource.openai.azure.com/  # ✅ With trailing slash

4. "Invalid API Key"¶

Problem: API key rotated or incorrect.

Solution:

# Regenerate key
az cognitiveservices account keys regenerate \
  --name my-openai-resource \
  --resource-group my-resource-group \
  --key-name key1

# Update environment variable

Best Practices¶

1. ✅ Use Managed Identity in Azure¶

// ✅ Good: Managed identity (no keys to manage)
const credential = new DefaultAzureCredential();

const ai = new NeuroLink({
  providers: [
    {
      name: "azure-openai",
      config: { credential, endpoint, deployment },
    },
  ],
});

2. ✅ Deploy Multiple Regions for HA¶

// ✅ Good: Multi-region failover
providers: [
  { name: "azure-us", priority: 1 },
  { name: "azure-eu", priority: 2 },
];

3. ✅ Use Private Endpoints for Security¶

# ✅ Good: Private endpoint + disable public access
az cognitiveservices account update \
  --public-network-access Disabled

4. ✅ Monitor Costs with Budgets¶

# ✅ Good: Set budget alerts
az consumption budget create \
  --amount 1000 \
  --time-grain Monthly

5. ✅ Enable Diagnostic Logging¶

# ✅ Good: Enable audit logs
az monitor diagnostic-settings create \
  --logs '[{"category":"Audit","enabled":true}]'

Provider Setup Guide - General provider configuration
Multi-Region Deployment - Geographic distribution
Compliance Guide - Security and compliance
Cost Optimization - Reduce costs

Additional Resources¶

Azure OpenAI Documentation - Official docs
Azure OpenAI Pricing - Pricing details
Azure Portal - Manage resources
Azure CLI Reference - CLI commands

Need Help? Join our GitHub Discussions or open an issue.

Azure OpenAI Provider Guide¶

Overview¶

Key Benefits¶

Use Cases¶

Quick Start¶

1. Create Azure OpenAI Resource¶

2. Deploy a Model¶

3. Get Credentials¶

4. Configure NeuroLink¶

Regional Deployment¶

Available Regions¶

Multi-Region Setup¶

Model Deployments¶

Available Models¶

Deployment Quotas (TPM)¶

Multiple Model Deployments¶

Azure AD Authentication¶

Managed Identity (Recommended)¶

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"¶

2. "Rate Limit Exceeded (429)"¶

3. "Resource Not Found"¶

4. "Invalid API Key"¶

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¶

Related Documentation¶

Additional Resources¶