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Create your first containerized Azure Functions

  • Artikkeli

In this article, you create a function app running in a Linux container and deploy it to Azure Functions.

Deploying your function code to Azure Functions in a container requires Premium plan or Dedicated (App Service) plan hosting. Completing this article incurs costs of a few US dollars in your Azure account, which you can minimize by cleaning-up resources when you're done.

Other options for deploying your function app container to Azure include:

Choose your development language

First, you use Azure Functions tools to create your project code as a function app in a Docker container using a language-specific Linux base image. Make sure to select your language of choice at the top of the article.

Core Tools automatically generates a Dockerfile for your project that uses the most up-to-date version of the correct base image for your functions language. You should regularly update your container from the latest base image and redeploy from the updated version of your container. For more information, see Creating containerized function apps.

Prerequisites

Before you begin, you must have the following requirements in place:

If you don't have an Azure subscription, create an Azure free account before you begin.

To publish the containerized function app image you create to a container registry, you need a Docker ID and Docker running on your local computer. If you don't have a Docker ID, you can create a Docker account.

You also need to complete the Create a container registry section of the Container Registry quickstart to create a registry instance. Make a note of your fully qualified login server name.

Create and activate a virtual environment

In a suitable folder, run the following commands to create and activate a virtual environment named .venv. Make sure to use one of the Python versions supported by Azure Functions.

python -m venv .venv

source .venv/bin/activate

If Python didn't install the venv package on your Linux distribution, run the following command:

sudo apt-get install python3-venv

You run all subsequent commands in this activated virtual environment.

Create and test the local functions project

In a terminal or command prompt, run the following command for your chosen language to create a function app project in the current folder:

func init --worker-runtime dotnet-isolated --docker

func init --worker-runtime node --language javascript --docker

func init --worker-runtime powershell --docker

func init --worker-runtime python --docker

func init --worker-runtime node --language typescript --docker

In an empty folder, run the following command to generate the Functions project from a Maven archetype:

mvn archetype:generate -DarchetypeGroupId=com.microsoft.azure -DarchetypeArtifactId=azure-functions-archetype -DjavaVersion=8 -Ddocker

The -DjavaVersion parameter tells the Functions runtime which version of Java to use. Use -DjavaVersion=11 if you want your functions to run on Java 11. When you don't specify -DjavaVersion, Maven defaults to Java 8. For more information, see Java versions.

Important

The JAVA_HOME environment variable must be set to the install location of the correct version of the JDK to complete this article.

Maven asks you for values needed to finish generating the project on deployment. Follow the prompts and provide the following information:

Prompt Value Description
groupId com.fabrikam A value that uniquely identifies your project across all projects, following the package naming rules for Java.
artifactId fabrikam-functions A value that is the name of the jar, without a version number.
version 1.0-SNAPSHOT Select the default value.
package com.fabrikam.functions A value that is the Java package for the generated function code. Use the default.

Type Y or press Enter to confirm.

Maven creates the project files in a new folder named artifactId, which in this example is fabrikam-functions.

The --docker option generates a Dockerfile for the project, which defines a suitable container for use with Azure Functions and the selected runtime.

Navigate into the project folder:

cd fabrikam-functions

Use the following command to add a function to your project, where the --name argument is the unique name of your function and the --template argument specifies the function's trigger. func new creates a C# code file in your project.

func new --name HttpExample --template "HTTP trigger"

Use the following command to add a function to your project, where the --name argument is the unique name of your function and the --template argument specifies the function's trigger. func new creates a subfolder matching the function name that contains a configuration file named function.json.

func new --name HttpExample --template "HTTP trigger"

To test the function locally, start the local Azure Functions runtime host in the root of the project folder.

func start  

func start  

npm install
npm start

mvn clean package  
mvn azure-functions:run

After you see the HttpExample endpoint written to the output, navigate to that endpoint. You should see a welcome message in the response output.

After you see the HttpExample endpoint written to the output, navigate to http://localhost:7071/api/HttpExample?name=Functions. The browser must display a "hello" message that echoes back Functions, the value supplied to the name query parameter.

Press Ctrl+C (Command+C on macOS) to stop the host.

Build the container image and verify locally

(Optional) Examine the Dockerfile in the root of the project folder. The Dockerfile describes the required environment to run the function app on Linux. The complete list of supported base images for Azure Functions can be found in the Azure Functions base image page.

In the root project folder, run the docker build command, provide a name as azurefunctionsimage, and tag as v1.0.0. Replace <DOCKER_ID> with your Docker Hub account ID. This command builds the Docker image for the container.

docker build --tag <DOCKER_ID>/azurefunctionsimage:v1.0.0 .

When the command completes, you can run the new container locally.

To verify the build, run the image in a local container using the docker run command, replace <DOCKER_ID> again with your Docker Hub account ID, and add the ports argument as -p 8080:80:

docker run -p 8080:80 -it <DOCKER_ID>/azurefunctionsimage:v1.0.0

After the image starts in the local container, browse to http://localhost:8080/api/HttpExample, which must display the same greeting message as before. Because the HTTP triggered function you created uses anonymous authorization, you can call the function running in the container without having to obtain an access key. For more information, see authorization keys.

After the image starts in the local container, browse to http://localhost:8080/api/HttpExample?name=Functions, which must display the same "hello" message as before. Because the HTTP triggered function you created uses anonymous authorization, you can call the function running in the container without having to obtain an access key. For more information, see authorization keys.

After verifying the function app in the container, press Ctrl+C (Command+C on macOS) to stop execution.

Publish the container image to a registry

To make your container image available for deployment to a hosting environment, you must push it to a container registry.

Azure Container Registry is a private registry service for building, storing, and managing container images and related artifacts. You should use a private registry service for publishing your containers to Azure services.

  1. Use this command to sign in to your registry instance using your current Azure credentials:

    az acr login --name <REGISTRY_NAME>

    In the previous command, replace <REGISTRY_NAME> with the name of your Container Registry instance.

  2. Use this command to tag your image with the fully qualified name of your registry login server:

    docker tag <DOCKER_ID>/azurefunctionsimage:v1.0.0 <LOGIN_SERVER>/azurefunctionsimage:v1.0.0

    Replace <LOGIN_SERVER> with the fully qualified name of your registry login server and <DOCKER_ID> with your Docker ID.

  3. Use this command to push the container to your registry instance:

    docker push <LOGIN_SERVER>/azurefunctionsimage:v1.0.0

Create supporting Azure resources for your function

Before you can deploy your container to Azure, you need to create three resources:

  • A resource group, which is a logical container for related resources.
  • A Storage account, which is used to maintain state and other information about your functions.
  • A function app, which provides the environment for executing your function code. A function app maps to your local function project and lets you group functions as a logical unit for easier management, deployment, and sharing of resources.

Use the following commands to create these items. Both Azure CLI and PowerShell are supported. To create your Azure resources using Azure PowerShell, you also need the Az PowerShell module, version 5.9.0 or later.

  1. If you haven't done already, sign in to Azure.

    az login

    The az login command signs you into your Azure account.

  2. Create a resource group named AzureFunctionsContainers-rg in your chosen region.

    az group create --name AzureFunctionsContainers-rg --location <REGION>

    The az group create command creates a resource group. In the above command, replace <REGION> with a region near you, using an available region code returned from the az account list-locations command.

  3. Create a general-purpose storage account in your resource group and region.

    az storage account create --name <STORAGE_NAME> --location <REGION> --resource-group AzureFunctionsContainers-rg --sku Standard_LRS

    The az storage account create command creates the storage account.

    In the previous example, replace <STORAGE_NAME> with a name that is appropriate to you and unique in Azure Storage. Storage names must contain 3 to 24 characters numbers and lowercase letters only. Standard_LRS specifies a general-purpose account supported by Functions.

  4. Use the command to create a Premium plan for Azure Functions named myPremiumPlan in the Elastic Premium 1 pricing tier (--sku EP1), in your <REGION>, and in a Linux container (--is-linux).

    az functionapp plan create --resource-group AzureFunctionsContainers-rg --name myPremiumPlan --location <REGION> --number-of-workers 1 --sku EP1 --is-linux

    We use the Premium plan here, which can scale as needed. For more information about hosting, see Azure Functions hosting plans comparison. For more information on how to calculate costs, see the Functions pricing page.

    The command also creates an associated Azure Application Insights instance in the same resource group, with which you can monitor your function app and view logs. For more information, see Monitor Azure Functions. The instance incurs no costs until you activate it.

Create and configure a function app on Azure with the image

A function app on Azure manages the execution of your functions in your Azure Functions hosting plan. In this section, you use the Azure resources from the previous section to create a function app from an image in a container registry and configure it with a connection string to Azure Storage.

  1. Create a function app using the following command, depending on your container registry:

    az functionapp create --name <APP_NAME> --storage-account <STORAGE_NAME> --resource-group AzureFunctionsContainers-rg --plan myPremiumPlan --image <LOGIN_SERVER>/azurefunctionsimage:v1.0.0 --registry-username <USERNAME> --registry-password <SECURE_PASSWORD>

    In this example, replace <STORAGE_NAME> with the name you used in the previous section for the storage account. Also, replace <APP_NAME> with a globally unique name appropriate to you and <DOCKER_ID> or <LOGIN_SERVER> with your Docker Hub account ID or Container Registry server, respectively. When you're deploying from a custom container registry, the image name indicates the URL of the registry.

    When you first create the function app, it pulls the initial image from your Docker Hub. You can also Enable continuous deployment to Azure from your container registry.

    Tip

    You can use the DisableColor setting in the host.json file to prevent ANSI control characters from being written to the container logs.

  2. Use the following command to get the connection string for the storage account you created:

    az storage account show-connection-string --resource-group AzureFunctionsContainers-rg --name <STORAGE_NAME> --query connectionString --output tsv

    The connection string for the storage account is returned by using the az storage account show-connection-string command.

    Replace <STORAGE_NAME> with the name of the storage account you created earlier.

  3. Use the following command to add the setting to the function app:

    az functionapp config appsettings set --name <APP_NAME> --resource-group AzureFunctionsContainers-rg --settings AzureWebJobsStorage=<CONNECTION_STRING>

    The az functionapp config appsettings set command creates the setting.

    In this command, replace <APP_NAME> with the name of your function app and <CONNECTION_STRING> with the connection string from the previous step. The connection should be a long encoded string that begins with DefaultEndpointProtocol=.

  4. The function can now use this connection string to access the storage account.

Verify your functions on Azure

With the image deployed to your function app in Azure, you can now invoke the function through HTTP requests.

  1. Run the following az functionapp function show command to get the URL of your new function:

    az functionapp function show --resource-group AzureFunctionsContainers-rg --name <APP_NAME> --function-name HttpExample --query invokeUrlTemplate

    Replace <APP_NAME> with the name of your function app.

  1. Use the URL you just obtained to call the HttpExample function endpoint, appending the query string ?name=Functions.
  1. Use the URL you just obtained to call the HttpExample function endpoint.

When you navigate to this URL, the browser must display similar output as when you ran the function locally.

Clean up resources

If you want to continue working with Azure Function using the resources you created in this article, you can leave all those resources in place. Because you created a Premium Plan for Azure Functions, you'll incur one or two USD per day in ongoing costs.

To avoid ongoing costs, delete the AzureFunctionsContainers-rg resource group to clean up all the resources in that group:

az group delete --name AzureFunctionsContainers-rg

Next steps

Working with custom containers and Azure Functions