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Objective
You have a working Azure Python docker function and the source code is managed in a Git repository. The goal of the tutorial is to automate the build and publish of a docker image to Azure Function App. This automation will include:
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The tutorial does not cover every feature or configuration option available in FlexDeploy.
Checklist
Checklist | Description |
|---|---|
Azure Tenant Id | Azure Tenant Id for the company |
Azure Subscription Id | Azure Subscription where the Function App exists |
Azure Client ID | Client ID to connect to desired Azure Subscription |
Azure Client Key | Password for the Client ID |
Azure Client ID permission | The Client ID must have relevant access in the target Function App to deploy code |
Azure Function App | The Function App with relevant runtime should already be created |
Azure Resource Group | The Resource Group containing the Function App |
Azure CLI installation | Azure CLI needs to be installed on the Target m/c where the plugin operation shall run |
Azure CLI in class path | Azure CLI should be added to the classpath in target m/c. Else the path can also be set under FlexDeploy environment level property |
Docker Registry Address | Target Azure Container Registry URL |
Docker Registry User | Azure Client ID to push/pull images against Azure Container Registry |
Docker Registry Token/Password | Password for the above Client ID |
Docker Registry User permission | The Client ID must have relevant access to push/pull images from Azure Container Registry |
Configure cloud account
First, an Azureaccount needs to be configured under Topology. FlexDeploy will connect to the right Azure Subscription with provided details and do the deployment.
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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
next update the Client Key value under Secret Text. This is to make sure no one else can retrieve the password
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Configure container account
Next, a DockerRegistry account needs to be configured under Topology. FlexDeploy will connect to the right Container Registry with provided details and push the docker image.
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Docker Registry Token/Password is a password field and hence needs to be kept hidden. To update the same click on the pencil icon as shown below
next update the Client Key value under Secret Text. This is to make sure no one else can retrieve the password
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Git repository structure
The Git repository should contain the codebase. A dockerfile should exist within the codebase with steps defined to create the docker image. 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.
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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.
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Step-iii: Build 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 and Push docker image to ACR
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If the Container Registry Account is properly configured it would push the image to Docker Registry. In our case, the image will be pushed to Azure Container Registry.
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Step-iv: Save all as Artifact from the intermediate dir as Artifact
Post execution of the above steps the intermediate directory(artifactObjects) should contain files as shown below.
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Configure the Source SCM repository under Source Control as shown below.
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To configure Project specific Source Control one first need to navigate to the Project Configuration tab.
Next, expand the SOURCE CONTROL option from the left-hand pane.
Select SOURCES for configuring the Source Repository
Select the appropriate Source Control Type
Configure Source Repository. For detailed steps of Source Control configuration please refer to Configure Source Control in FlexDeploy
Project Properties
To configure Project specific settings one can navigate to Configuration Properties as shown below.
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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 detailsat 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:
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Properties | Mandatory field | Description |
Slot Name |
| Target slot for deployment |
Target slot to swap | Optional | In case slot swap is required |
Azure Cloud Account |
| An azure account with relevant details |
The absolute path of Azure CLI | Optional | Not required if Azure CLI already added to workflow execution m/c classpath |
Docker Server | Optional | Docker server address. Required if Docker Unix Socket is not set. |
Docker Server Port | Optional | The port to connect to on the Docker server. |
Docker Unix Socket | Optional | The socket the Docker daemon listens on The default value is [/var/run/docker.sock] |
Registry Account | Docker Registry account with relevant details | |
GIT Path | Optional | Path to the Git executable. Required only if git is not on class path. |
Below given are the env-specific values which need to be updated.
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Congratulations! You have successfully completed the Java Application Python docker image deployment to the Azure Function App tutorial.
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