FAQ for Azure AI services disconnected containers

Azure AI containers allow developers to use the same intelligent APIs that are available in Azure, but with the benefits of containerization. Disconnected containers are offered through commitment tier pricing, each offering a discounted rate compared to the pay-as-you-go pricing model. With commitment tier pricing, you can commit to using the following Azure AI services features for a fixed fee, enabling you to have a predictable total cost based on the needs of your workload.

• Azure AI Speech
  • Speech to text
  • Custom Speech to text
  • Neural Text to speech
• Text Translation (Standard)
• Azure AI Language
  • Sentiment Analysis
  • Key Phrase Extraction
  • Language Detection
  • Named Entity Recognition (NER)
• Azure AI Vision - Read
• Document Intelligence

For more information about commitment tier pricing, reach out to your Microsoft account team or contact at Microsoft. You can also email azureaicontainergating@service.microsoft.com.

We'd like to make more Azure AI services offerings available as containers. Contact your local Microsoft account manager to get updates on new container releases and other Azure AI services announcements.

Fill out and submit the request form to request access to the container. Access is limited to customers that meet the following requirements:

• Your organization must have an enterprise agreement or an equivalent agreement and should be identified as strategic customer or partner with Microsoft.
• Valid business scenario/use case - Disconnected containers are expected to run fully offline hence, your use cases must meet one of below or similar requirements:
  • Environment or device(s) with zero connectivity to internet.
  • Remote location that occasionally has internet access.
  • Organization under strict regulation of not sending any kind of data back to cloud.
• Application completed as instructed - Please pay close attention to guidance provided throughout the application to ensure you provide all the necessary information required for approval.

If your use case can't satisfy above requirements but you're interested in running containers on premises, you might be able to use connected containers.

Possible causes for a denied application are as follows:

• Not being an existing Microsoft partner or enterprise agreement customer
• Invalid Azure subscription ID. your ID must belong to the applicant organization, and you can't apply on behalf of other organizations.
• The application was submitted with a personal email address (For example: @hotmail.com, @gmail.com, @yahoo.com, etc.)
• Invalid justification or business scenario provided
• Other missing or inaccurate data

After you submit the form, the Azure AI services team will review it and email you a decision within 10 business days.

Once your application is approved, the Azure AI services gating team will communicate details for purchasing the commitment tier pricing, and instructions to download and run the containers.

If you have any questions on the application, gating process or other information needed, email azureaicontainergating@service.microsoft.com

These containers are hosted on the Microsoft Container Registry and available for download on Microsoft Artifact Registry and Microsoft Container Registry (MCR). You won't be able to run the container if your Azure subscription has not been approved after completion of the request form. Once you're approved, you can follow the steps in Use Docker containers in disconnected environments

Azure AI services disconnected containers don't have an SLA, because customers control configuration of the resources used. Customers are free to deploy containers on-premises and define the host environments.

Not everyone is familiar with the term sovereign cloud, so let's begin with definition: The sovereign cloud consists of the Azure Government, Azure Germany, and Microsoft Azure operated by 21Vianet clouds. Currently, customers are able to create disconnected containers resource from public cloud.

Customers can choose when to update the containers that they've deployed. Containers will be marked with standard Docker tags such as latest to indicate the most recent version. We encourage customers to pull the latest versions of containers as they're released. For details on how to get notified when an image is updated, see Azure Container Registry webhooks.

The current and last major version of the container will be supported. However, we encourage customers to stay current to get the latest technology to be compliant.

Major version changes indicate that there's a breaking change to the API signature. We anticipate that this will generally coincide with major version changes to the corresponding Azure AI services cloud offering. Minor version changes indicate bug fixes, model updates, or new features that don't make a breaking change to the API signature.

If you're having trouble running an Azure AI services container, you can try using the Microsoft diagnostics container. Use this container to diagnose common errors in your deployment environment that might prevent Azure AI containers from functioning as expected.

To get the container, use the following docker pull command:

docker pull mcr.microsoft.com/azure-cognitive-services/diagnostic

Then run the container. Replace {ENDPOINT_URI} with your endpoint, and replace {API_KEY} with your key to your resource:

docker run --rm mcr.microsoft.com/azure-cognitive-services/diagnostic \
eula=accept \
Billing={ENDPOINT_URI} \
ApiKey={API_KEY}

The container will test for network connectivity to the billing endpoint.

We don't test containers with OpenShift, but generally, Azure AI containers should run on any platform that supports Docker images. If you're using OpenShift, we recommend running the containers as root-user.

We encourage customers to voice their concerns publicly and to up-vote others who have done the same where potential issues overlap. You can use the feedback tool for both product feedback and feature recommendations.

Here are the status messages and errors:

Customer support channels are the same as for the Azure AI services cloud-based APIs. All Azure AI containers include logging features that will help us and the community support customers. Here are options for more support:

• Find contact information in your Azure support plan.
• Try these areas of Stack Overflow, a question-and-answer site for professional and enthusiast programmers:
• Azure AI services
• Microsoft Cognitive

Customers are charged based on the commitment tier they purchase. Choose an annual commitment plan based on the needs of your workload. You can customize the "Commitment tier disconnected containers DC0" pricing tier by selecting one of several commitment tier options.

Each commitment tier offers a discounted rate as compared to the pay-as-you-go pricing model. Commitment plans are charged annually starting from the day the resource was created. Additional units can be added at any time in the year and are charged pro-rated based on the number of days remaining in the billing year. For more information, see the following pricing pages:

• Speech Services for:
  • Speech to text
  • Custom Speech to text
  • Neural Text to speech
• Text Translation (Standard)
• Azure AI Language pricing for
• Sentiment Analysis
• Key Phrase Extraction
• Language Detection
• Azure AI Vision - Read
• Document Intelligence - Custom/Invoice

Docker containers running in a disconnected environment will write usage records to a volume where they're collected over time. These containers also provide a REST endpoint to generate a report about usage. See Use containers in disconnected environments for more information.

Microsoft's standard warranty for enterprise software will apply when a container image is formally announced as General Available (GA). There's no warranty for container images in preview.

Azure AI containers are x64-based containers that can run any compatible Linux node, VM, and edge device that supports x64 Linux Docker containers. They all require CPU processors. You can find the minimum and recommended configurations for each container offering on these pages:

• Speech Service for:
  • Speech to text
  • Custom Speech to text
  • Neural Text to speech
• Text Translation (Standard)
• Azure AI Language documentation for
• Sentiment Analysis
• Key Phrase Extraction
• Language Detection
• Named Entity Recognition
• Azure AI Vision - Read
• Document Intelligence - Custom/Invoice

Azure AI containers are Linux containers, but there's some support for Linux containers on Windows. For more information about Linux containers on Windows, see the Docker documentation.

Azure AI containers don't have any compliance certifications.