functions-create-function-linux-custom-image.md

title	description	ms.date	ms.topic	ms.custom	zone_pivot_groups
Create Azure Functions on Linux using a custom image	Learn how to create Azure Functions running on a custom Linux image.	12/2/2020	tutorial	devx-track-csharp, mvc, devx-track-python, devx-track-azurepowershell, devx-track-azurecli	programming-languages-set-functions-full

Create a function on Linux using a custom container

In this tutorial, you create and deploy your code to Azure Functions as a custom Docker container using a Linux base image. You typically use a custom image when your functions require a specific language version or have a specific dependency or configuration that isn't provided by the built-in image.

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

You can also use a default Azure App Service container as described on Create your first function hosted on Linux. Supported base images for Azure Functions are found in the Azure Functions base images repo.

In this tutorial, you learn how to:

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-java"

[!div class="checklist"]

• Create a function app and Dockerfile using the Azure Functions Core Tools.
• Build a custom image using Docker.
• Publish a custom image to a container registry.
• Create supporting resources in Azure for the function app
• Deploy a function app from Docker Hub.
• Add application settings to the function app.
• Enable continuous deployment.
• Enable SSH connections to the container.
• Add a Queue storage output binding. ::: zone-end ::: zone pivot="programming-language-customhandler" [!div class="checklist"]
• Create a function app and Dockerfile using the Azure Functions Core Tools.
• Build a custom image using Docker.
• Publish a custom image to a container registry.
• Create supporting resources in Azure for the function app
• Deploy a function app from Docker Hub.
• Add application settings to the function app.
• Enable continuous deployment.
• Enable SSH connections to the container. ::: zone-end

You can follow this tutorial on any computer running Windows, macOS, or Linux.

[!INCLUDE functions-requirements-cli]

• Docker

• A Docker ID

[!INCLUDE functions-cli-verify-prereqs]

• Run docker login to sign in to Docker. This command fails if Docker isn't running, in which case start docker and retry the command.

[!INCLUDE functions-cli-create-venv]

Create and test the local functions project

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python"
In a terminal or command prompt, run the following command for your chosen language to create a function app project in a folder named LocalFunctionsProject.
::: zone-end
::: zone pivot="programming-language-csharp"

func init LocalFunctionsProject --worker-runtime dotnet --docker

::: zone-end
::: zone pivot="programming-language-javascript"

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

::: zone-end
::: zone pivot="programming-language-powershell"

func init LocalFunctionsProject --worker-runtime powershell --docker

::: zone-end
::: zone pivot="programming-language-python"

func init LocalFunctionsProject --worker-runtime python --docker

::: zone-end
::: zone pivot="programming-language-typescript"

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

::: zone-end ::: zone pivot="programming-language-java"
In an empty folder, run the following command to generate the Functions project from a Maven archetype.

Bash

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

PowerShell

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

Cmd

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.
Provide the following values when prompted:

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	Choose 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 with a name of artifactId, which in this example is fabrikam-functions. ::: zone-end

::: zone pivot="programming-language-customhandler"

func init LocalFunctionsProject --worker-runtime custom --docker

::: zone-end

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

Navigate into the project folder: ::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-customhandler"

cd LocalFunctionsProject

::: zone-end
::: zone pivot="programming-language-java"

cd fabrikam-functions

::: zone-end
::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python" Add a function to your project by using the following command, 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 code file appropriate to the project's chosen language and a configuration file named function.json.

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

::: zone-end

::: zone pivot="programming-language-customhandler" Add a function to your project by using the following command, 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"

In a text editor, create a file in the project folder named handler.R. Add the following as its content.

library(httpuv)

PORTEnv <- Sys.getenv("FUNCTIONS_CUSTOMHANDLER_PORT")
PORT = strtoi(PORTEnv , base = 0L)

http_not_found <- list(
  status=404,
  body='404 Not Found'
)
http_method_not_allowed <- list(
  status=405,
  body='405 Method Not Allowed'
)

hello_handler <- list(
  GET = function (request) list(body="Hello world")
)

routes <- list(
  '/api/HttpExample' = hello_handler
)

router <- function (routes, request) {
  if (!request$PATH_INFO %in% names(routes)) {
    return(http_not_found)
  }
  path_handler <- routes[[request$PATH_INFO]]

  if (!request$REQUEST_METHOD %in% names(path_handler)) {
    return(http_method_not_allowed)
  }
  method_handler <- path_handler[[request$REQUEST_METHOD]]

  return(method_handler(request))
}

app <- list(
  call = function (request) {
    response <- router(routes, request)
    if (!'status' %in% names(response)) {
      response$status <- 200
    }
    if (!'headers' %in% names(response)) {
      response$headers <- list()
    }
    if (!'Content-Type' %in% names(response$headers)) {
      response$headers[['Content-Type']] <- 'text/plain'
    }

    return(response)
  }
)

cat(paste0("Server listening on :", PORT, "...\n"))
runServer("0.0.0.0", PORT, app)

In host.json, modify the customHandler section to configure the custom handler's startup command.

"customHandler": {
  "description": {
      "defaultExecutablePath": "Rscript",
      "arguments": [
      "handler.R"
    ]
  },
  "enableForwardingHttpRequest": true
}

::: zone-end

To test the function locally, start the local Azure Functions runtime host in the root of the project folder: ::: zone pivot="programming-language-csharp"

func start --build  

::: zone-end
::: zone pivot="programming-language-javascript,programming-language-powershell,programming-language-python"

func start  

::: zone-end
::: zone pivot="programming-language-typescript"

npm install
npm start

::: zone-end
::: zone pivot="programming-language-java"

mvn clean package  
mvn azure-functions:run

::: zone-end ::: zone pivot="programming-language-customhandler"

R -e "install.packages('httpuv', repos='http://cran.rstudio.com/')"
func start

::: zone-end ::: zone pivot="programming-language-javascript,programming-language-powershell,programming-language-python,programming-language-java,programming-language-typescript" Once you see the HttpExample endpoint appear in the output, navigate to http://localhost:7071/api/HttpExample?name=Functions. The browser should display a "hello" message that echoes back Functions, the value supplied to the name query parameter. ::: zone-end ::: zone pivot="programming-language-customhandler" Once you see the HttpExample endpoint appear in the output, navigate to http://localhost:7071/api/HttpExample. The browser should display a "Hello world" message. ::: zone-end Use Ctrl-C to stop the host.

Build the container image and test locally

::: zone pivot="programming-language-javascript,programming-language-powershell,programming-language-python,programming-language-java,programming-language-typescript" (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. ::: zone-end

::: zone pivot="programming-language-customhandler" Examine the Dockerfile in the root of the project folder. The Dockerfile describes the required environment to run the function app on Linux. Custom handler applications use the mcr.microsoft.com/azure-functions/dotnet:3.0-appservice image as its base.

Modify the Dockerfile to install R. Replace the contents of Dockerfile with the following.

FROM mcr.microsoft.com/azure-functions/dotnet:3.0-appservice 
ENV AzureWebJobsScriptRoot=/home/site/wwwroot \
    AzureFunctionsJobHost__Logging__Console__IsEnabled=true

RUN apt update && \
    apt install -y r-base && \
    R -e "install.packages('httpuv', repos='http://cran.rstudio.com/')"

COPY . /home/site/wwwroot

::: zone-end

In the root project folder, run the docker build command, and provide a name, azurefunctionsimage, and tag, 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 test the build, run the image in a local container using the docker run command, replacing again <DOCKER_ID with your Docker ID and adding the ports argument, -p 8080:80:

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

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-customhandler"
Once the image is running in a local container, open a browser to http://localhost:8080, which should display the placeholder image shown below. The image appears at this point because your function is running in the local container, as it would in Azure, which means that it's protected by an access key as defined in function.json with the "authLevel": "function" property. The container hasn't yet been published to a function app in Azure, however, so the key isn't yet available. If you want to test against the local container, stop docker, change the authorization property to "authLevel": "anonymous", rebuild the image, and restart docker. Then reset "authLevel": "function" in function.json. For more information, see authorization keys.

::: zone-end ::: zone pivot="programming-language-java"
Once the image is running in a local container, browse to http://localhost:8080/api/HttpExample?name=Functions, which should display the same "hello" message as before. Because the Maven archetype generates an HTTP triggered function that uses anonymous authorization, you can still call the function even though it's running in the container. ::: zone-end

After you've verified the function app in the container, stop docker with Ctrl+C.

Push the image to Docker Hub

Docker Hub is a container registry that hosts images and provides image and container services. To share your image, which includes deploying to Azure, you must push it to a registry.

1. If you haven't already signed in to Docker, do so with the docker login command, replacing <docker_id> with your Docker ID. This command prompts you for your username and password. A "Login Succeeded" message confirms that you're signed in.

   docker login

2. After you've signed in, push the image to Docker Hub by using the docker push command, again replacing <docker_id> with your Docker ID.

   docker push <docker_id>/azurefunctionsimage:v1.0.0

3. Depending on your network speed, pushing the image the first time might take a few minutes (pushing subsequent changes is much faster). While you're waiting, you can proceed to the next section and create Azure resources in another terminal.

Create supporting Azure resources for your function

To deploy your function code to Azure, you need to create three resources:

• A resource group, which is a logical container for related resources.
• An Azure Storage account, which maintains state and other information about your projects.
• An Azure functions 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.

You use Azure CLI commands to create these items. Each command provides JSON output upon completion.

1. Sign in to Azure with the az login command:

   az login
   

2. Create a resource group with the az group create command. The following example creates a resource group named AzureFunctionsContainers-rg in the westeurope region. (You generally create your resource group and resources in a region near you, using an available region from the az account list-locations command.)

   az group create --name AzureFunctionsContainers-rg --location westeurope
   

   [!NOTE] You can't host Linux and Windows apps in the same resource group. If you have an existing resource group named AzureFunctionsContainers-rg with a Windows function app or web app, you must use a different resource group.

3. Create a general-purpose storage account in your resource group and region by using the az storage account create command. In the following example, replace <storage_name> with a globally unique name appropriate to you. Names must contain three to 24 characters numbers and lowercase letters only. Standard_LRS specifies a typical general-purpose account.

   az storage account create --name <storage_name> --location westeurope --resource-group AzureFunctionsContainers-rg --sku Standard_LRS
   

   The storage account incurs only a few USD cents for this tutorial.

4. Use the command to create a Premium plan for Azure Functions named myPremiumPlan in the Elastic Premium 1 pricing tier (--sku EP1), in the West Europe region (-location westeurope, or use a suitable region near you), and in a Linux container (--is-linux).

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

   We use the Premium plan here, which can scale as needed. To learn more about hosting, see Azure Functions hosting plans comparison. To calculate costs, see the Functions pricing page.

   The command also provisions 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 hosting plan. In this section, you use the Azure resources from the previous section to create a function app from an image on Docker Hub and configure it with a connection string to Azure Storage.

1. Create the Functions app using the az functionapp create command. In the following 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> with your Docker ID.

   az functionapp create --name <app_name> --storage-account <storage_name> --resource-group AzureFunctionsContainers-rg --plan myPremiumPlan --runtime <functions runtime stack> --deployment-container-image-name <docker_id>/azurefunctionsimage:v1.0.0
   

   The deployment-container-image-name parameter specifies the image to use for the function app. You can use the az functionapp config container show command to view information about the image used for deployment. You can also use the az functionapp config container set command to deploy from a different image.

2. Retrieve the connection string for the storage account you created by using the az storage account show-connection-string command, assigning it to a shell variable storageConnectionString:

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

3. Add this setting to the function app by using the az functionapp config appsettings set command. In the following command, replace <app_name> with the name of your function app, and replace <connection_string> with the connection string from the previous step (a long encoded string that begins with "DefaultEndpointProtocol="):

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

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

   [!TIP] In Bash, you can use a shell variable to capture the connection string instead of using the clipboard. First, use the following command to create a variable with the connection string:

   storageConnectionString=$(az storage account show-connection-string --resource-group AzureFunctionsContainers-rg --name <storage_name> --query connectionString --output tsv)

   Then refer to the variable in the second command:

   az functionapp config appsettings set --name <app_name> --resource-group AzureFunctionsContainers-rg --settings AzureWebJobsStorage=$storageConnectionString
   

Note

If you publish your custom image to a private container account, you should use environment variables in the Dockerfile for the connection string instead. For more information, see the ENV instruction. You should also set the variables DOCKER_REGISTRY_SERVER_USERNAME and DOCKER_REGISTRY_SERVER_PASSWORD. To use the values, then, you must rebuild the image, push the image to the registry, and then restart the function app on Azure.

Verify your functions on Azure

With the image deployed to the function app on Azure, you can now invoke the function through HTTP requests. Because the function.json definition includes the property "authLevel": "function", you must first obtain the access key (also called the "function key") and include it as a URL parameter in any requests to the endpoint.

1. Retrieve the function URL with the access (function) key by using the Azure portal, or by using the Azure CLI with the az rest command.)

   Portal

   1. Sign in to the Azure portal, then search for and select Function App.

   2. Select the function you want to verify.

   3. In the left navigation panel, select Functions, and then select the function you want to verify.

      

   4. Select Get Function Url.

      

   5. In the pop-up window, select default (function key) and then copy the URL to the clipboard. The key is the string of characters following ?code=.

      

   [!NOTE]
   Because your function app is deployed as a container, you can't make changes to your function code in the portal. You must instead update the project in the local image, push the image to the registry again, and then redeploy to Azure. You can set up continuous deployment in a later section.

   Azure CLI

   1. Construct a URL string in the following format, replacing <subscription_id>, <resource_group>, and <app_name> with your Azure subscription ID, the resource group of your function app, and the name of your function app, respectively:

      "/subscriptions/<subscription_id>/resourceGroups/<resource_group>/providers/Microsoft.Web/sites/<app_name>/host/default/listKeys?api-version=2018-11-01"
      

      For example, the URL might look the following address:

      "/subscriptions/1234aaf4-1234-abcd-a79a-245ed34eabcd/resourceGroups/AzureFunctionsContainers-rg/providers/Microsoft.Web/sites/msdocsfunctionscontainer/host/default/listKeys?api-version=2018-11-01"
      

      [!TIP] For convenience, you can instead assign the URL to an environment variable and use it in the az rest command.

   2. Run the following az rest command (available in the Azure CLI version 2.0.77 and later), replacing <uri> with the URI string from the last step, including the quotes:

      az rest --method post --uri <uri> --query functionKeys.default --output tsv
      

   3. The output of the command is the function key. The full function URL is then https://<app_name>.azurewebsites.net/api/<function_name>?code=<key>, replacing <app_name>, <function_name>, and <key> with your specific values.

      [!NOTE] The key retrieved here is the host key that works for all functions in the functions app; the method shown for the portal retrieves the key for the one function only.

   ---

2. Paste the function URL into your browser's address bar, adding the parameter &name=Azure to the end of this URL. Text like "Hello, Azure" should appear in the browser.

   

3. To test authorization, remove the code= parameter from the URL and verify that you get no response from the function.

Enable continuous deployment to Azure

You can enable Azure Functions to automatically update your deployment of an image whenever you update the image in the registry.

1. Enable continuous deployment by using az functionapp deployment container config command, replacing <app_name> with the name of your function app:

   az functionapp deployment container config --enable-cd --query CI_CD_URL --output tsv --name <app_name> --resource-group AzureFunctionsContainers-rg
   

   This command enables continuous deployment and returns the deployment webhook URL. (You can retrieve this URL at any later time by using the az functionapp deployment container show-cd-url command.)

2. Copy the deployment webhook URL to the clipboard.

3. Open Docker Hub, sign in, and select Repositories on the nav bar. Locate and select image, select the Webhooks tab, specify a Webhook name, paste your URL in Webhook URL, and then select Create:

   

4. With the webhook set, Azure Functions redeploys your image whenever you update it in Docker Hub.

Enable SSH connections

SSH enables secure communication between a container and a client. With SSH enabled, you can connect to your container using App Service Advanced Tools (Kudu). To make it easy to connect to your container using SSH, Azure Functions provides a base image that has SSH already enabled. You need only edit your Dockerfile, then rebuild and redeploy the image. You can then connect to the container through the Advanced Tools (Kudu)

1. In your Dockerfile, append the string -appservice to the base image in your FROM instruction:

   ::: zone pivot="programming-language-csharp"

   FROM mcr.microsoft.com/azure-functions/dotnet:3.0-appservice

   ::: zone-end

   ::: zone pivot="programming-language-javascript"

   FROM mcr.microsoft.com/azure-functions/node:2.0-appservice

   ::: zone-end

   ::: zone pivot="programming-language-powershell"

   FROM mcr.microsoft.com/azure-functions/powershell:2.0-appservice

   ::: zone-end

   ::: zone pivot="programming-language-python"

   FROM mcr.microsoft.com/azure-functions/python:2.0-python3.7-appservice

   ::: zone-end

   ::: zone pivot="programming-language-typescript"

   FROM mcr.microsoft.com/azure-functions/node:2.0-appservice

   ::: zone-end

2. Rebuild the image by using the docker build command again, replacing <docker_id> with your Docker ID:

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

3. Push the updated image to Docker Hub, which should take considerably less time than the first push only the updated segments of the image need to be uploaded.

   docker push <docker_id>/azurefunctionsimage:v1.0.0

4. Azure Functions automatically redeploys the image to your functions app; the process takes place in less than a minute.

5. In a browser, open https://<app_name>.scm.azurewebsites.net/, replacing <app_name> with your unique name. This URL is the Advanced Tools (Kudu) endpoint for your function app container.

6. Sign in to your Azure account, and then select the SSH to establish a connection with the container. Connecting may take a few moments if Azure is still updating the container image.

7. After a connection is established with your container, run the top command to view the currently running processes.

   

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-java"

Write to an Azure Storage queue

Azure Functions lets you connect your functions to other Azure services and resources without having to write your own integration code. These bindings, which represent both input and output, are declared within the function definition. Data from bindings is provided to the function as parameters. A trigger is a special type of input binding. Although a function has only one trigger, it can have multiple input and output bindings. To learn more, see Azure Functions triggers and bindings concepts.

This section shows you how to integrate your function with an Azure Storage queue. The output binding that you add to this function writes data from an HTTP request to a message in the queue.

[!INCLUDE functions-cli-get-storage-connection] ::: zone-end

[!INCLUDE functions-register-storage-binding-extension-csharp]

[!INCLUDE functions-add-output-binding-cli]

::: zone pivot="programming-language-csharp"
[!INCLUDE functions-add-storage-binding-csharp-library]
::: zone-end
::: zone pivot="programming-language-java" [!INCLUDE functions-add-output-binding-java-cli] ::: zone-end

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-java"

Add code to use the output binding

With the queue binding defined, you can now update your function to receive the msg output parameter and write messages to the queue. ::: zone-end

::: zone pivot="programming-language-python"
[!INCLUDE functions-add-output-binding-python] ::: zone-end

::: zone pivot="programming-language-javascript"
[!INCLUDE functions-add-output-binding-js] ::: zone-end

::: zone pivot="programming-language-typescript"
[!INCLUDE functions-add-output-binding-ts] ::: zone-end

::: zone pivot="programming-language-powershell"
[!INCLUDE functions-add-output-binding-powershell]
::: zone-end

::: zone pivot="programming-language-csharp"
[!INCLUDE functions-add-storage-binding-csharp-library-code] ::: zone-end

::: zone pivot="programming-language-java" [!INCLUDE functions-add-output-binding-java-code]

[!INCLUDE functions-add-output-binding-java-test-cli] ::: zone-end

::: zone pivot="programming-language-csharp,programming-language-javascript,programming-language-typescript,programming-language-powershell,programming-language-python,programming-language-java"

Update the image in the registry

1. In the root folder, run docker build again, and this time update the version in the tag to v1.0.1. As before, replace <docker_id> with your Docker Hub account ID:

   docker build --tag <docker_id>/azurefunctionsimage:v1.0.1 .

2. Push the updated image back to the repository with docker push:

   docker push <docker_id>/azurefunctionsimage:v1.0.1

3. Because you configured continuous delivery, updating the image in the registry again automatically updates your function app in Azure.

View the message in the Azure Storage queue

In a browser, use the same URL as before to invoke your function. The browser should display the same response as before, because you didn't modify that part of the function code. The added code, however, wrote a message using the name URL parameter to the outqueue storage queue.

[!INCLUDE functions-add-output-binding-view-queue-cli]

::: zone-end

Clean up resources

If you want to continue working with Azure Function using the resources you created in this tutorial, 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 AzureFunctionsContainer-rg resource group to clean up all the resources in that group:

az group delete --name AzureFunctionsContainer-rg

Next steps

• Monitoring functions
• Scale and hosting options
• Kubernetes-based serverless hosting