Deploy and run container on Azure Container Instance
With the following steps, scale Azure Cognitive Services applications in the cloud easily with Azure Container Instance. This helps you focus on building your applications instead of managing the infrastructure.
This solution works with any Cognitive Services container. The Cognitive Service resource must be created in the Azure portal before using this recipe. Each Cognitive Service that supports containers has a "How to install" document specifically for installing and configuring the service for a container. Because some services require a file or set of files as input for the container, it is important that you understand and have used the container successfully before using this solution.
- A Cognitive Service resource, created in Azure portal.
- Cognitive Service endpoint URL - review your specific service's "How to install" for the container, to find where the endpoint URL is from within the Azure portal, and what a correct example of the URL looks like. The exact format can change from service to service.
- Cognitive Service key - the keys are on the Keys page for the Azure resource. You only need one of the two keys. The key is a string of 32 alpha-numeric characters.
- A single Cognitive Services Container on your local host (your computer). Make sure you can:
- Pull down the image with a
- Run the local container successfully with all required configuration settings with a
- Call the container's endpoint, getting a response of 2xx and a JSON response back.
- Pull down the image with a
All variables in angle brackets,
<>, need to be replaced with your own values. This replacement includes the angle brackets.
Create an Azure Container Instance resource
Go to the Create page for Container Instances.
On the Basics tab, enter the following details:
Setting Value Subscription Select your subscription. Resource group Select the available resource group or create a new one such as
Container name Enter a name such as
cognitive-container-instance. The name must be in lower caps.
Location Select a region for deployment. Image type If your container image is stored in a container registry that doesn’t require credentials, choose
Public. If accessing your container image requires credentials, choose
Private. Refer to container repositories and images for details on whether or not the container image is
Image name Enter the Cognitive Services container location. The location is what's used as an argument to the
docker pullcommand. Refer to the container repositories and images for the available image names and their corresponding repository.
The image name must be fully qualified specifying three parts. First, the container registry, then the repository, finally the image name:
Here is an example,
mcr.microsoft.com/azure-cognitive-services/keyphrasewould represent the Key Phrase Extraction image in the Microsoft Container Registry under the Azure Cognitive Services repository. Another example is,
containerpreview.azurecr.io/microsoft/cognitive-services-speech-to-textwhich would represent the Speech to Text image in the Microsoft repository of the Container Preview container registry.
Size Change size to the suggested recommendations for your specific Cognitive Service container:
2 CPU cores
On the Networking tab, enter the following details:
Setting Value Ports Set the TCP port to
5000. Exposes the container on port 5000.
On the Advanced tab, enter the required Environment Variables for the container billing settings of the Azure Container Instance resource:
Copied from the Keys page of the resource. It is a 32 alphanumeric-character string with no spaces or dashes,
Copied from the Overview page of the resource.
Click Review and Create
After validation passes, click Create to finish the creation process
When the resource is successfully deployed, it's ready
Use the Container Instance
Select the Overview and copy the IP address. It will be a numeric IP address such as
Open a new browser tab and use the IP address, for example,
http://<IP-address>:5000 (http://22.214.171.124:5000). You will see the container's home page, letting you know the container is running.
Select Service API Description to view the swagger page for the container.
Select any of the POST APIs and select Try it out. The parameters are displayed including the input. Fill in the parameters.
Select Execute to send the request to your Container Instance.
You have successfully created and used Cognitive Services containers in Azure Container Instance.
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