Scalability and Error Handling in Azure OpenAI with API Management
This video demonstrates how Azure OpenAI achieves scalability using API Management and discusses error handling and access permissions.
00:00:00 This video demonstrates how Azure OpenAI can be deployed securely using Azure API Management as a gateway. It also showcases a centralized logging and monitoring framework for chargeback purposes.
🔑 Azure OpenAI can be deployed in an Enterprise grade resilient and secured way by using Azure API management as a gateway.
🌐 The proposed deployment model includes a central logging and monitoring framework for chargeback purposes.
🔒 API management uses Azure AD service principles to authenticate and authorize against Azure OpenAI.
00:01:38 This video explains how Azure OpenAI uses API Management to handle errors and retry logic. It demonstrates a simple API call to the OpenAI service.
💡 API management handles error handling and retry logic for OpenAI backends.
🔧 API management simplifies the process of creating a completion operation for the Azure OpenAI service.
📊 API management allows for integration with reporting solutions for data analysis.
00:03:16 Learn about Azure OpenAI scalability and API management, including how to handle errors and access permissions.
🔑 The video discusses the configuration of the API Management service for Azure OpenAI scalability.
⚙️ The API operation in question does not have any retry logic and will throw an error if the call to OpenAI instance one fails.
🔒 Access for the service principle representing business unit 1 has been revoked, resulting in a permission denied error.
00:04:58 This video explains how Azure OpenAI achieves scalability using API Management. It discusses the retry logic and switching backend service URL in case of errors.
API Management allows for scalability and fault tolerance in Azure services.
Retry logic is implemented to handle errors and switch to a different backend service URL.
Clients need to use a subscription key issued by API Management to consume the API.
00:06:39 Learn how to use Azure AD for authentication and authorization in OpenAI API Management. See how error handling and retry logic can switch between backend instances.
🔑 Using Azure AD for authentication and authorization instead of OpenAI API Keys.
🔍 Tracing the API call to identify the caller and understand the back end response.
🔄 Implementing retry logic to switch to a different backend instance in case of errors.
00:08:21 Learn how Azure OpenAI achieves scalability using API Management by forwarding requests transparently and logging necessary information for business unit chargeback policies.
🔑 The video discusses how Azure OpenAI scalability can be achieved using API Management.
📈 By forwarding calls to multiple instances and logging necessary information to an event hub, a chargeback policy can be implemented based on business units, number of calls made, and tokens consumed.
💡 Stream Analytics can be used to create aggregations and query the data in the event hub to analyze the usage and make informed decisions.
00:10:01 Azure OpenAI scalability using API Management. A multi-regional active active deployment with improved client experience, security, and chargeback policy.
📌 API Management can handle errors gracefully and implement retry logic for improved client experience.
🔒 Azure ID access tokens can be utilized to add security to the system.
🌐 By repeating the logic in another region and implementing a multi-regional load balancer, the deployment becomes multi-regional and active-active.
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