Using Azure AI Services Containers

By Ashwin Venugopal -

 





Introduction

You can deploy a containerized service that encapsulates a specific Azure AI services service API by using the container images for Azure AI services that are available in the Microsoft Container Registry.

To deploy and use an Azure AI services container, the following three activities must occur:

  • The container image for the specific Azure AI services API you want to use is downloaded and deployed to a container host, such as a local Docker server, an Azure Container Instance (ACI), or Azure Kubernetes Service (AKS).

  • Client applications submit data to the endpoint provided by the containerized service, and retrieve results just as they would from an Azure AI services cloud resource in Azure.

  • Periodically, usage metrics for the containerized service are sent to an Azure AI services resource in Azure in order to calculate billing for the service.

For billing purposes, you must provision an Azure AI services resource in Azure even if you are using a container.

In order to avoid sending potentially sensitive data to the Azure AI services endpoint, client applications submit their requests to the containerized service. However, the container must be able to connect to the Azure AI services resource on a regular basis in order to send usage metrics for billing.

Azure AI Services Container Images

A portion of the capability of Azure AI services is offered by each container. For instance, not every element of the Azure AI Language service is included within a single container. Sentiment analysis, translation, and language detection are all distinct container pictures. All containers, however, require comparable setup procedures.

Azure AI Services Container Configuration

Three options need to be specified when deploying an Azure AI services container image to a host.

  • ApiKey- Key from your deployed Azure AI service, used for billing.

  • Billing- Endpoint URI from your deployed Azure AI service, used for billing.

  • Eula- Value of accept to state you accept the license for the container.

Consuming Azure AI Services From a Container

Applications use the containerized Azure AI services endpoint instead of the usual Azure endpoint once your Azure AI services container is deployed.  

The client application does not need to supply a subscription key in order to be authenticated, but it must be set up with the proper URL for your container. As needed for your particular application scenario, you can impose network security limitations and design your own authentication system.

Conclusion

We have successfully learnt about using Azure AI services containers.

 

 

 













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