Determine a default endpoint for a service

When designing and implementing a Microsoft Azure AI solution, one important aspect to consider is determining a default endpoint for your service. The default endpoint serves as the entry point for your AI solution, enabling clients to make requests and receive responses.

Step 1: Create an Azure Resource Group

Start by creating an Azure resource group to organize and manage your Azure resources. You can use the Azure portal, Azure CLI, or Azure PowerShell to create a resource group.

Step 2: Deploy your AI Service

Once you have a resource group, deploy your AI service in Azure. Azure provides various AI services like Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service. Choose the service that best fits your requirements and follow the deployment instructions provided in the Azure documentation for that specific service.

Step 3: Configure the Service

After deploying your AI service, you need to configure it to define the default endpoint. This step varies depending on the AI service you are using. Let’s take Azure Cognitive Services as an example.

• Azure Cognitive Services: If you are using Azure Cognitive Services, such as Text Analytics or Computer Vision, you can find the endpoint information in the Azure portal. Navigate to the specific Cognitive Service resource you created in your resource group. In the Overview or Keys and Endpoint section, you can find the default endpoint URL. It typically looks like “https://<service-name>.cognitiveservices.azure.com”.

Step 4: Access the Default Endpoint

Now that you have determined the default endpoint for your AI service, you can access it to make requests and receive responses. The method for accessing the endpoint depends on the type of client or application you are using.

• REST API: If you are interacting with the AI service using a REST API, you can use any HTTP client library or simply send HTTP requests to the default endpoint URL. For example, in Python, you can use the requests library to send HTTP requests to the endpoint.

import requests

endpoint = "https://.cognitiveservices.azure.com"
# Make a GET request to the endpoint
response = requests.get(endpoint)
print(response.json())


• SDKs and Libraries: Many AI services provide client SDKs or libraries in various programming languages, which make it easier to interact with the default endpoint. These SDKs abstract the communication details and provide a higher-level interface for accessing the service. Refer to the respective Azure AI service documentation for guidance on how to use the SDKs or libraries.

from azure.cognitiveservices.language.textanalytics import TextAnalyticsClient
from azure.cognitiveservices.language.textanalytics.models import DetectLanguageInput

endpoint = "https://.cognitiveservices.azure.com"
# Create a client using the SDK
client = TextAnalyticsClient(endpoint, api_key)
# Use the client to access the service
response = client.detect_language(inputs=[DetectLanguageInput("Hello!")])
print(response)


By determining a default endpoint for your Azure AI service, you can facilitate communication between clients and your solution. Remember to secure your endpoint by using authentication mechanisms like API keys or Azure Active Directory (Azure AD) authentication to ensure only authorized clients can access your service.