Hướng dẫn tích hợp Claude trên Microsoft Azure AI Foundry

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Published: 2026-05-09 · Source: crawler_authoritative

Tình huống

Nhà phát triển cần truy cập và sử dụng các mô hình Claude AI thông qua nền tảng Microsoft Azure AI Foundry, quản lý chi phí qua Azure subscription.

Insight

Microsoft Foundry cung cấp endpoint Azure-native và authentication để truy cập Claude API. Tại launch, Claude khả dụng với deployment type Global Standard (US DataZone sắp ra mắt). Pricing sử dụng standard API pricing của Anthropic. Foundry hỗ trợ C#, Java, PHP, Python, TypeScript SDK; Go và Ruby SDK không hỗ trợ Foundry. Claude Opus 4.7, 4.6 và Sonnet 4.6 có context window 1M token trên Foundry; các model khác có 200k token context window. Các tính năng không hỗ trợ: Admin API, Compliance API, Models API, Message Batch API. Anthropic cung cấp zero data retention cho khách hàng Foundry. Request identifiers (request-id, apim-request-id) được include trong response headers để debug và trace.

Hành động

1. Cài đặt SDK tương ứng: pip install anthropic, npm install @anthropic-ai/foundry-sdk, dotnet add package Anthropic.Foundry, hoặc Gradle/Maven dependency cho Java. 2. Tạo Foundry resource tại ai.azure.com, configure access management với API keys hoặc Entra ID (RBAC). 3. Deploy Claude model: Models + endpoints > Deploy base model > chọn model (vd claude-sonnet-4-6) > đặt deployment name > chọn Global Standard > Deploy. 4. Authentication: Sử dụng API key từ Keys and Endpoint section (api-key hoặc x-api-key header), hoặc Entra ID token (Bearer token từ az account get-access-token). 5. Sử dụng endpoint format: https://{resource}.services.ai.azure.com/anthropic/v1/* . 6. Monitoring qua Azure Monitor, Log Analytics, Cost Management; recommend logging 30-day rolling basis. 7. Troubleshooting: 401 lỗi API key, 403 thiếu RBAC role, 429 rate limit cần exponential backoff.

Điều kiện áp dụng

Go và Ruby SDK không hỗ trợ Microsoft Foundry - cần dùng Python hoặc TypeScript SDK để có full Foundry support. Các tính năng Admin API, Compliance API, Models API, Message Batch API không khả dụng trên Foundry. Rate limit headers không được include trong responses - cần quản lý qua Azure monitoring tools.

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Nội dung gốc (Original)

Claude in Microsoft Foundry

Access Claude models through Microsoft Foundry with Azure-native endpoints and authentication.

---

This guide walks you through the process of setting up and making API calls to Claude in Foundry in Python, TypeScript, or using direct HTTP requests. When you can access Claude in Foundry, you are billed for Claude usage in the Microsoft Marketplace with your Azure subscription, allowing you to access Claude’s latest capabilities while managing costs through your Azure subscription.

Regional availability: At launch, Claude is available as a Global Standard deployment type in Foundry resources (US DataZone coming soon). Pricing for Claude in the Microsoft Marketplace uses Anthropic’s standard API pricing. Visit the pricing page for details.

Foundry is supported by the C#, Java, PHP, Python, and TypeScript SDKs. The Go and Ruby SDKs do not currently support Microsoft Foundry. For available SDK platform integrations, see [Client SDKs](/docs/en/api/client-sdks).

Preview

In this preview platform integration, Claude models run on Anthropic’s infrastructure. This is a commercial integration for billing and access through Azure. As an independent processor for Microsoft, customers using Claude through Microsoft Foundry are subject to Anthropic’s data use terms. Anthropic continues to provide its industry-leading safety and data commitments, including zero data retention availability.

Prerequisites

Before you begin, ensure you have:

• An active Azure subscription
• Access to Foundry
• The Azure CLI installed (optional, for resource management)

Install an SDK

Anthropic’s client SDKs support Foundry through platform-specific packages.

```bash pip install -U "anthropic" ``` ```bash npm install @anthropic-ai/foundry-sdk ``` ```bash dotnet add package Anthropic.Foundry ``` ```kotlin implementation("com.anthropic:anthropic-java-foundry:2.30.0") ``` ```xml com.anthropic anthropic-java-foundry 2.30.0 ``` ```bash composer require anthropic-ai/sdk ```

Provisioning

Foundry uses a two-level hierarchy: resources contain your security and billing configuration, while deployments are the model instances you call via API. You’ll first create a Foundry resource, then create one or more Claude deployments within it.

Provisioning Foundry resources

Create a Foundry resource, which is required to use and manage services in Azure. You can follow these instructions to create a Foundry resource. Alternatively, you can start by creating a Foundry project, which involves creating a Foundry resource.

To provision your resource:

1. Navigate to the Foundry portal
2. Create a new Foundry resource or select an existing one
3. Configure access management using Azure-issued API keys or Entra ID (formerly Azure Active Directory) for role-based access control
4. Optionally configure the resource to be part of a private network (Azure Virtual Network) for enhanced security
5. Note your resource name. You’ll use this as {resource} in API endpoints (for example, https://{resource}.services.ai.azure.com/anthropic/v1/*)

Creating Foundry deployments

After creating your resource, deploy a Claude model to make it available for API calls:

1. In the Foundry portal, navigate to your resource
2. Go to Models + endpoints and select + Deploy model > Deploy base model
3. Search for and select a Claude model (for example, claude-sonnet-4-6)
4. Configure deployment settings:
   • Deployment name: Defaults to the model ID, but you can customize it (for example, my-claude-deployment). The deployment name cannot be changed after it has been created.
   • Deployment type: Select Global Standard (recommended for Claude)
5. Select Deploy and wait for provisioning to complete
6. Once deployed, you can find your endpoint URL and keys under Keys and Endpoint

The deployment name you choose becomes the value you pass in the `model` parameter of your API requests. You can create multiple deployments of the same model with different names to manage separate configurations or rate limits.

Authentication

Claude on Foundry supports two authentication methods: API keys and Entra ID tokens. Both methods use Azure-hosted endpoints in the format https://{resource}.services.ai.azure.com/anthropic/v1/*.

API key authentication

After provisioning your Foundry Claude resource, you can obtain an API key from the Foundry portal:

1. Navigate to your resource in the Foundry portal
2. Go to Keys and Endpoint section
3. Copy one of the provided API keys
4. Use either the api-key or x-api-key header in your requests, or provide it to the SDK

The Python and TypeScript SDKs require an API key and either a resource name or base URL. The SDKs will automatically read these from the following environment variables if they are defined:

• ANTHROPIC_FOUNDRY_API_KEY - Your API key
• ANTHROPIC_FOUNDRY_RESOURCE - Your resource name (e.g., example-resource)
• ANTHROPIC_FOUNDRY_BASE_URL - Alternative to resource name; the full base URL (e.g., https://example-resource.services.ai.azure.com/anthropic/)

The `resource` and `base_url` parameters are mutually exclusive. Provide either the resource name (which the SDK uses to construct the URL as `https://{resource}.services.ai.azure.com/anthropic/`) or the full base URL directly.

Example using API key:

curl https://{resource}.services.ai.azure.com/anthropic/v1/messages \
  -H "content-type: application/json" \
  -H "api-key: YOUR_AZURE_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

# ant reads ANTHROPIC_API_KEY and sends it as x-api-key, which Foundry accepts
export ANTHROPIC_API_KEY="YOUR_AZURE_API_KEY"
 
ant messages create \
  --base-url https://example-resource.services.ai.azure.com/anthropic \
  --model claude-opus-4-7 \
  --max-tokens 1024 \
  --message '{role: user, content: "Hello!"}' \
  --transform content

import os
from anthropic import AnthropicFoundry
 
client = AnthropicFoundry(
    api_key=os.environ.get("ANTHROPIC_FOUNDRY_API_KEY"),
    resource="example-resource",  # your resource name
)
 
message = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content)

import AnthropicFoundry from "@anthropic-ai/foundry-sdk";
 
const client = new AnthropicFoundry({
  apiKey: process.env.ANTHROPIC_FOUNDRY_API_KEY,
  resource: "example-resource" // your resource name
});
 
const message = await client.messages.create({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Hello!" }]
});
console.log(message.content);

using Anthropic.Foundry;
using Anthropic.Models.Messages;
 
var client = new AnthropicFoundryClient(
    new AnthropicFoundryApiKeyCredentials(
        Environment.GetEnvironmentVariable("ANTHROPIC_FOUNDRY_API_KEY")!,
        "example-resource"
    )
);
 
var response = await client.Messages.Create(new MessageCreateParams
{
    Model = "claude-opus-4-7",
    MaxTokens = 1024,
    Messages = [new() { Role = Role.User, Content = "Hello!" }],
});
 
Console.WriteLine(
    string.Join("", response.Content
        .Select(block => block.Value)
        .OfType<TextBlock>()
        .Select(textBlock => textBlock.Text)));

import com.anthropic.client.AnthropicClient;
import com.anthropic.client.okhttp.AnthropicOkHttpClient;
import com.anthropic.foundry.backends.FoundryBackend;
import com.anthropic.models.messages.MessageCreateParams;
 
void main() {
    // Requires env vars: ANTHROPIC_FOUNDRY_API_KEY, ANTHROPIC_FOUNDRY_RESOURCE
    AnthropicClient client = AnthropicOkHttpClient.builder()
        .backend(FoundryBackend.fromEnv())
        .build();
 
    MessageCreateParams params = MessageCreateParams.builder()
        .model("claude-opus-4-7")
        .maxTokens(1024)
        .addUserMessage("Hello!")
        .build();
 
    client.messages().create(params).content().stream()
        .flatMap(block -> block.text().stream())
        .forEach(textBlock -> System.out.println(textBlock.text()));
}

<?php
 
use Anthropic\Foundry;
 
$client = Foundry\Client::withCredentials(
    apiKey: getenv('ANTHROPIC_FOUNDRY_API_KEY'),
    baseUrl: 'https://example-resource.services.ai.azure.com/anthropic/v1',
);
 
$message = $client->messages->create(
    maxTokens: 1024,
    messages: [
        ['role' => 'user', 'content' => 'Hello!']
    ],
    model: 'claude-opus-4-7',
);
echo $message->content[0]->text;

The Anthropic Ruby SDK does not currently support Microsoft Azure AI Foundry. You can use the standard `Anthropic::Client` with a custom `base_url` pointing to your Foundry endpoint, but Azure-specific authentication (Entra ID) is not built in. For full Foundry support, use the Python or TypeScript SDKs. Keep your API keys secure. Never commit them to version control or share them publicly. Anyone with access to your API key can make requests to Claude through your Foundry resource.

Microsoft Entra authentication

For enhanced security and centralized access management, you can use Entra ID (formerly Azure Active Directory) tokens:

1. Enable Entra authentication for your Foundry resource
2. Obtain an access token from Entra ID
3. Use the token in the Authorization: Bearer {TOKEN} header

Example using Entra ID:

# Get Azure Entra ID token
ACCESS_TOKEN=$(az account get-access-token --resource https://cognitiveservices.azure.com --query accessToken -o tsv)
 
# Make request with token. Replace {resource} with your resource name
curl https://{resource}.services.ai.azure.com/anthropic/v1/messages \
  -H "content-type: application/json" \
  -H "Authorization: Bearer $ACCESS_TOKEN" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

import os
from anthropic import AnthropicFoundry
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
 
# Get Azure Entra ID token using token provider pattern
token_provider = get_bearer_token_provider(
    DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
)
 
# Create client with Entra ID authentication
client = AnthropicFoundry(
    resource="example-resource",  # your resource name
    azure_ad_token_provider=token_provider,  # Use token provider for Entra ID auth
)
 
# Make request
message = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content)

import AnthropicFoundry from "@anthropic-ai/foundry-sdk";
import { DefaultAzureCredential, getBearerTokenProvider } from "@azure/identity";
 
// Get Entra ID token using token provider pattern
const credential = new DefaultAzureCredential();
const tokenProvider = getBearerTokenProvider(
  credential,
  "https://cognitiveservices.azure.com/.default"
);
 
// Create client with Entra ID authentication
const client = new AnthropicFoundry({
  resource: "example-resource", // your resource name
  azureADTokenProvider: tokenProvider // Use token provider for Entra ID auth
});
 
// Make request
const message = await client.messages.create({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Hello!" }]
});
console.log(message.content);

using Anthropic.Foundry;
using Anthropic.Models.Messages;
using Azure.Identity;
 
var client = new AnthropicFoundryClient(
    new AnthropicFoundryIdentityTokenCredentials(
        new DefaultAzureCredential(),
        "example-resource"
    )
);
 
var response = await client.Messages.Create(new MessageCreateParams
{
    Model = "claude-opus-4-7",
    MaxTokens = 1024,
    Messages = [new() { Role = Role.User, Content = "Hello!" }],
});
 
Console.WriteLine(
    string.Join("", response.Content
        .Select(block => block.Value)
        .OfType<TextBlock>()
        .Select(textBlock => textBlock.Text)));

import com.anthropic.client.AnthropicClient;
import com.anthropic.client.okhttp.AnthropicOkHttpClient;
import com.anthropic.foundry.backends.FoundryBackend;
import com.anthropic.models.messages.MessageCreateParams;
import com.azure.identity.AuthenticationUtil;
import com.azure.identity.DefaultAzureCredentialBuilder;
import java.util.function.Supplier;
 
void main() {
    Supplier<String> bearerTokenSupplier = AuthenticationUtil.getBearerTokenSupplier(
        new DefaultAzureCredentialBuilder().build(),
        "https://cognitiveservices.azure.com/.default"
    );
 
    AnthropicClient client = AnthropicOkHttpClient.builder()
        .backend(FoundryBackend.builder()
            .bearerTokenSupplier(bearerTokenSupplier)
            .resource("example-resource")
            .build())
        .build();
 
    MessageCreateParams params = MessageCreateParams.builder()
        .model("claude-opus-4-7")
        .maxTokens(1024)
        .addUserMessage("Hello!")
        .build();
 
    client.messages().create(params).content().stream()
        .flatMap(block -> block.text().stream())
        .forEach(textBlock -> System.out.println(textBlock.text()));
}

<?php
 
use Anthropic\Foundry;
 
// Azure Entra ID authentication
$client = Foundry\Client::withCredentials(
    authToken: $token,
    baseUrl: 'https://example-resource.services.ai.azure.com/anthropic/v1',
);
 
$message = $client->messages->create(
    maxTokens: 1024,
    messages: [
        ['role' => 'user', 'content' => 'Hello!']
    ],
    model: 'claude-opus-4-7',
);
echo $message->content[0]->text;

The Anthropic Ruby SDK does not currently support Microsoft Azure AI Foundry. You can use the standard `Anthropic::Client` with a custom `base_url` pointing to your Foundry endpoint, but Azure-specific authentication (Entra ID) is not built in. For full Foundry support, use the Python or TypeScript SDKs. Azure Entra ID authentication allows you to manage access using Azure RBAC, integrate with your organization's identity management, and avoid managing API keys manually.

Correlation request IDs

Foundry includes request identifiers in HTTP response headers for debugging and tracing. When contacting support, provide both the request-id and apim-request-id values to help teams quickly locate and investigate your request across both Anthropic and Azure systems.

Supported features

Claude on Foundry supports most of Claude’s powerful features. You can find all the features currently supported in the overview documentation.

Context window

Claude Opus 4.7, Claude Opus 4.6, and Claude Sonnet 4.6 have a 1M-token context window on Microsoft Foundry. Other Claude models, including Sonnet 4.5, have a 200k-token context window.

Features not supported

• Admin API (/v1/organizations/* endpoints)
• Compliance API (/v1/compliance/* endpoints)
• Models API (/v1/models)
• Message Batch API (/v1/messages/batches)

API responses

API responses from Claude on Foundry follow the standard Claude API response format. This includes the usage object in response bodies, which provides detailed token consumption information for your requests. The usage object is consistent across all platforms (first-party API, Foundry, Amazon Bedrock, and Google Vertex AI).

For details on response headers specific to Foundry, see the correlation request IDs section.

API model IDs and deployments

The following Claude models are available through Foundry. The latest generation models (Opus 4.7, Opus 4.6, Sonnet 4.6, and Haiku 4.5) offer the most advanced capabilities:

Model	Default Deployment Name
Claude Opus 4.7	claude-opus-4-7
Claude Opus 4.6	claude-opus-4-6
Claude Opus 4.5	claude-opus-4-5
Claude Sonnet 4.6	claude-sonnet-4-6
Claude Sonnet 4.5	claude-sonnet-4-5
Claude Opus 4.1	claude-opus-4-1
Claude Haiku 4.5	claude-haiku-4-5

By default, deployment names match the model IDs shown above. However, you can create custom deployments with different names in the Foundry portal to manage different configurations, versions, or rate limits. Use the deployment name (not necessarily the model ID) in your API requests.

Monitoring and logging

Azure provides comprehensive monitoring and logging capabilities for your Claude usage through standard Azure patterns:

• Azure Monitor: Track API usage, latency, and error rates
• Azure Log Analytics: Query and analyze request/response logs
• Cost Management: Monitor and forecast costs associated with Claude usage

Anthropic recommends logging your activity on at least a 30-day rolling basis to understand usage patterns and investigate any potential issues.

Azure's logging services are configured within your Azure subscription. Enabling logging does not provide Microsoft or Anthropic access to your content beyond what's necessary for billing and service operation.

Troubleshooting

Authentication errors

Error: 401 Unauthorized or Invalid API key

• Solution: Verify your API key is correct. You can obtain a new API key from the Azure portal under Keys and Endpoint for your Claude resource.
• Solution: If using Azure Entra ID, ensure your access token is valid and hasn’t expired. Tokens typically expire after 1 hour.

Error: 403 Forbidden

• Solution: Your Azure account may lack the necessary permissions. Ensure you have the appropriate Azure RBAC role assigned (for example, “Cognitive Services OpenAI User”).

Rate limiting

Error: 429 Too Many Requests

• Solution: You’ve exceeded your rate limit. Implement exponential backoff and retry logic in your application.
• Solution: Consider requesting rate limit increases through the Azure portal or Azure support.

Rate limit headers

Foundry does not include Anthropic’s standard rate limit headers (anthropic-ratelimit-tokens-limit, anthropic-ratelimit-tokens-remaining, anthropic-ratelimit-tokens-reset, anthropic-ratelimit-input-tokens-limit, anthropic-ratelimit-input-tokens-remaining, anthropic-ratelimit-input-tokens-reset, anthropic-ratelimit-output-tokens-limit, anthropic-ratelimit-output-tokens-remaining, and anthropic-ratelimit-output-tokens-reset) in responses. Manage rate limiting through Azure’s monitoring tools instead.

Model and deployment errors

Error: Model not found or Deployment not found

• Solution: Verify you’re using the correct deployment name. If you haven’t created a custom deployment, use the default model ID (for example, claude-sonnet-4-6).
• Solution: Ensure the model/deployment is available in your Azure region.

Error: Invalid model parameter

• Solution: The model parameter should contain your deployment name, which can be customized in the Foundry portal. Verify the deployment exists and is properly configured.

[Claude Mythos Preview](https://anthropic.com/glasswing) is a research preview available to invited customers on Microsoft Foundry. For more information, see [Project Glasswing](https://anthropic.com/glasswing).

Additional resources

• Foundry documentation: ai.azure.com/catalog
• Azure pricing: azure.microsoft.com/en-us/pricing
• Anthropic pricing details: Pricing documentation
• Authentication guide: See the authentication section above
• Azure portal: portal.azure.com

Liên kết

• Nền tảng: Microsoft Azure · Anthropic
• Nguồn: https://platform.claude.com/docs/en/build-with-claude/claude-in-microsoft-foundry.md

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