Deploy .NET Application to Azure Function

Objective

You have a working Azure .NET Function and the source code is managed in a GIT repository.  The goal of the tutorial is to automate the deployment of a .NET Function to Azure Function App.  This automation will include:

• cloning the composite from a GIT repository

• package the .NET archive and Application Setting/Connection String properties file

• update relevant Application Setting and Connection String properties in Azure Function App

• Deploy Approach 1:

  • compile the .NET package in local

  • deploy the executable files to Azure Function App

• Deploy Approach 2:

  • create an archive of source code in local

  • deploy the source code to Azure Function App

  • compile the .NET application in Azure Function App backend

  • retrieve the deployment log(optional) against the deployment executed

We will walk through each of the FlexDeploy features that will be created/configured to accomplish this goal and have the .NET Function deployed in a very short amount of time.

Checklist

Configure cloud account

First, an Azure account needs to be configured under Topology. FlexDeploy will connect to the right Azure Subscription with provided details and do the deployment.

1. Navigate to the Topology Tab

2. Select Integrations from the left-hand pane

3. Navigate to the Cloud tab under Topology

4. Create a new Cloud account of the provider type “Azure” with the “+” button.

Open

It should have a Client ID, Client Key, Tenant Id, and Subscription Id configured in it. The Client ID must have relevant access in the target Function App to deploy code and make other associated changes(Application Setting update etc).

Open

 Client Key is a password field and hence needs to be kept hidden. To update the same click on the pencil icon as shown below

1. Update the Client Key value under Secret Text. This is to make sure no one else can retrieve the password

Git repository structure

The git repo should contain the codebase. Alongside it can also contain any Application Setting and Connection String related attributes in respective files(any naming convention allowed). These files are not mandatory, however in case someone has any Application Setting and Connection String property to update this is recommended option. Please review Application Setting and Connection String property update for detailed explanation.

Sample Git Repo structure given below.

Build and Deploy Workflows

Navigate to Workflows and create a build and a deploy workflow using the button as highlighted below.

Build/Deploy Approach 1:

Under this approach, the build is going to happen locally on the execution host (where the build workflow is executed). Since we are going to build the executable (.dll files) using the .NET command, it’s essential that .NET with the correct version is already preinstalled on the host m/c.

Below is a sample build workflow to build .NET publish folder and create an artifact from it.

Step-i: Clone Git Repository

This step will clone the Git repository codebase into the project execution working directory. The Git URL will be retrieved from Source Control configured under Project Configuration.

Below is the Git code structure and corresponding exported codebase during execution as a result of the above step.

Git Codebase

Exported Codebase

Step-ii: Restore .NET Application

The below step will use the MSBuild Plugin to restore the .NET Codebase in the TEMP folder.

Note: Each application will have separate directory structure/file name hence the all paths need to be modified accordingly.

Note: Its essential to make sure Consumes Artifacts and Produces Artifacts checkbox is marked only when required. Please follow the snapshots for all execution steps to avoid any discrepancy.

Step-iii: Build .NET Application

The below step will use the MSBuild Plugin to Build the .NET Application to create the executable files(.dll etc)

Step-iii: Copy the properties file to the intermediate dir

Application Setting and Connection String json files(if applicable/present) will be moved to the intermediate directory. An intermediate directory can have any name, in this case, we are using the artifactsObjects folder inside the temp directory. File names are mentioned under File Filter with ‘##’ separated(as advised in the description). Application Setting and Connection String values can also be passed as input to deploy workflow. Application Setting and Connection String files are optional, please review the Application Setting and Connection String property update for a detailed explanation.

Step-v: Create an archive of the executable in the intermediate dir

Per the Azure Function App deployment requirement, we have created an archive with the .NET executable inside it.

Note: Each application will have separate directory structure hence the all paths need to be modified accordingly.

If we look inside the deploy.zip, it contains the executable along with other associated files. Basically, it contains all relevant files that need to be copied to the Azure Function App backend. Azure Function App treats this as an executable package and runs it.

Note: the executable files inside the .zip file shouldn’t be inside any subfolder. Else once the zip file is deployed to Azure Function App may not work.

Step-v: Save all as Artifact from the intermediate dir

Post execution of the above steps the intermediate directory(artifactObjects) should contain files as shown below.

These objects are required as part of the deployment flow. Hence we create an archive(artifacts.zip) with them inside the Artifacts directory. We also enable Produces Artifacts checkbox to save the zip file as an artifact.

As part of the above step, all files inside the artifactObjects folder are archived to create an artifacts.zip which will be saved as an artifact for future reference from the Deployment workflow.

Note: The directory name/artifact name can be anything. The deployment workflow expects only one .zip file inside the artifact containing the executable files. It will search for a .zip extension and treat it as a package archive for deployment.

Note: the deployFunctions operation(Azure plugin) will search for the Application Setting and Connection String file name provided as part of Project properties. Irrespective of folder structure it will find the file. In case more than one file exists with the same name, flow shall fail.

Deploy Workflow

Below given is a sample deployment workflow to deploy the archive to Azure Function App.

This step first updates the Application Setting/Connection String values from the files present in the artifact(optional). Instead of using Application Setting and Connection String files, one can directly provide the values as part of plugin input.

In such case, we can create input variables on deployment workflow like given below and pass them as deployFunctions operation input argument. This is optional and any other way to pass the arguments(e.g. hardcoded value) is also acceptable.

First, click on the Inputs button to open the edit popup. Create two input variables, one each for Application Setting and Connection String as shown below.

The input arguments are then mapped to the input properties of the deployFunctions operation as shown below. The plugin will take the input values and process them accordingly.

The deployFunctions operation returns four output variables. To capture them and use them for further processing/evaluation, one can create four variables and map them against the output parameters of deployFunctions operation. Return As Output option should be checked.

1. First, click the X² button to open the Variables popup.

2. Next use Create option to add four output variables.

Map the variables against the output of the deployFunctions operation to capture the responses.

Build/Deploy Approach 2:

Under this approach, the build is going to happen on the Azure backend. The source code will be added to an archive and need to be deployed.

Below is a sample build workflow to build a code archive and create an artifact from it.

The key question which may arise at this point - how would Azure Web App understand if the deployed archive is an executable and can be run directly? Or is it just the source code which needs to be built first before execution?

To perform a build in Azure Web App backend, you just need to check the Remote Build flag under Project properties. Plugin would do all necessary configurations behind the scenes. Rest all steps and configuration will be exactly as mentioned in the previous case.

Project configuration

Navigate to the Project tab and create a Project with a logical name(DotNetAzureFunction in this case)

Configure the Build and Deploy workflow that has been created in previous steps as shown below

Source Control

Configure the Source SCM repository under Source Control as shown below.

 To configure Project specific Source Control one first need to navigate to the Project Configuration tab.

1. Next, expand the SOURCE CONTROL option from the left-hand pane.

2. Select SOURCES for configuring the Source Repository

3. Select the appropriate Source Control Type

4. Configure Source Repository.

For detailed steps of Source Control configuration please refer to https://flexagon.atlassian.net/wiki/spaces/FD80/pages/10561718147

Project Properties

1. To configure Project specific settings one can navigate to the Project Configuration tab as shown above.

2. Next, select the PROPERTIES option from the left-hand pane.

3. To deploy a Function to Azure Function App, the first two mandatory properties are the Function App Name and Resource Group Name. These need to be configured under Project properties.

4. Remote Build: This flag is applicable in case we want to upload the code to the Azure Function App backend and build it there itself (e.g.: .NET/Node.js). As part of Build/Deploy approachh-2 we are creating archive of source code and want the same to be build at Azure Function App backend, Hence this checkbox needs to be checked.

5. Under Project properties, one also needs to provide the Application Setting/Connection String file names(if applicable).

6. Show deployment log: Once deployment is completed, in case someone wants to verify the execution steps, they need to check the below checkbox under Project properties.

   In this case, the plugin will internally retrieve the deployment Id and will fetch the Deployment log(if available), and return the same as an Output variable.

   This is applicable only for Code archive deployment(not for docker image deployment.)

Application Setting and Connection String property update

These Application Setting/Connection String properties are non-mandatory and can be directly provided as plugin Input as well. Or even may not be passed at all. However this is the recommended way and the files should exist in the working directory(TEMP) during execution(folder hierarchy is not required, the plugin will search the file based on the file name).

Although only one Application Setting and one Connection String file are allowed per project.

Application Setting and Connection String are two separate entities so whichever files exist, the same will be considered during deployment.

Let’s review the sample Application Setting file first(same structure as the local.settings.json file). In our scenario, there are two dynamic values that need to be propagated to Function App Application Setting.

Both are already added to the AppSetting.json file present in Git Repository.

Both properties need to be configured in workflow Properties with relevant Property Scope.

1. To pass the value for DYNAMIC_TESTKEY1(Project specific) one first needs to navigate to the Configuration tab

2. Next, select the PROPERTIES option from the left-hand pane and provide the proper value against the property.

For Environment property, the same needs to be added against Environment-Target Group properties.

1. First, navigate to the Topology.

2. Next, navigate to the Environment-Target Group properties section for the intended Target.

3. Next, select the PROPERTIES tab and provide the value for DYNAMIC_ENV_TESTKEY2 (environment specific) as shown below.

Application Setting/Connection String can also be passed as an input argument to the deployFunction operation. The sample is shown as given below.

Please refer to this link for the input structure of Application Setting and Connection String both when passed as a file or as input parameter - Application Setting/Connection String file and input content acceptable structure

In case both the Application Setting file and Application Setting input argument are passed, a consolidated list of properties will be considered while updating Function App. In case the same attribute is used both in the file and input, the value provided as part of the input will take precedence. The same applies to Connection String as well.

Also, it’s not mandatory to have dynamic values. One can always pass static hard-coded value if needed (although not recommended).

Application Setting and Connection String values will be updated against the Function Slot Name configured at the environment level. Refer to the Deploy to Slot section for further details.

There could also be scenarios where someone only need to update the Application Setting or Connection String without actually deploying the code. In that case one can use upsertFunctionApplicationSetting or upsertFunctionConnectionString operations respectively. The workflow execution will be exactly same only the code archive creation /Docker image update step will not be required. Build workflow generated artifact should only container AppSetting.json or ConnString.json. These values can also be passed as input as already mentioned in detail in above section.

Target Properties

Select Topology from the menu and then select Topology Overview from the left menu. You will see a table that has Instances as the rows and Environments as the columns with colored circles representing the Environment Instance. Color coding represents:

• RED - no required properties are set and/or the Endpoint is not configured

• YELLOW - some of the required properties are set and/or the Endpoint is not configured

• GREEN - all required properties are set and the Endpoint is configured

Selecting the GREEN circle for DEV will display the configurable properties/Endpoint and allows for the configuration of

Below given are the environment-specific values which need to be updated.

Also in case, we are adding any environment-specific properties for Application Setting/Connection String(as mentioned in the previous step), those values should also be updated.

The Azure Cloud account needs to be set here from the drop-down. It will show all Cloud Accounts configured under Topology, which we have already mentioned earlier.

Deploy to Slot

Azure Function App default slot is production. However, one can configure multiple slots and deploy Functions on those slots inside Function App. Function Slot Name is a mandatory field, where the code needs to deploy.

In case someone wants to do a slot swap, they can provide the Target Slot to swap with as shown below.

executeFunctionAppSlotSwap operation can be used to perform the slot swap.

Build Execution

For detailed steps on how to initiate Build Azure Function, review artifacts, and ultimately deploy to Azure Function App please refer to https://flexagon.atlassian.net/wiki/spaces/FD80/pages/10561718093

Post deployment debugging

Post deployment success of plugin execution it can take a little while for the function application up and running.

Currently once the application is deployed to Azure Function App through the plugin operation, Azure basically uploads the files to the backend. However if the application is up and running or have failed, can’t be verified immediately. It takes a little while for the service to start and accept requests.

Issues can happen if host.json has some issue. Sample error message shown below.

The function archive generated is not in desired format hence can’t be loaded. Sample error message shown below.

In such scenario functions deployed will reflect as none with Azure Function may be in unreachable state as shown below.

Best way to check logs: https://$func_name.scm.azurewebsites.net/api/logstream or logstream from console. As already in above scenarios, in case of failure we can easily debug the issue from log and get the issue fixed.

Congratulations! You have successfully completed the .NET Application deployment to the Azure Function App tutorial.

Now that you have configured FlexDeploy for one Azure Function, it is extremely easy to replicate the same for other Azure Functions. Simply use the Copy Project feature and a new project will be created with all of the configuration completed already. You just need to make the necessary configuration changes.