Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/skylinecommunications/skyline-dataminer-deploy-action

An action to build a DataMiner Application Package (.dmapp) from your solution and deploy it to your cloud connected DataMiner System.
https://github.com/skylinecommunications/skyline-dataminer-deploy-action

continuous-delivery dataminer deployment skyline-communications

Last synced: about 2 hours ago
JSON representation

An action to build a DataMiner Application Package (.dmapp) from your solution and deploy it to your cloud connected DataMiner System.

Awesome Lists containing this project

README 

        
# Skyline DataMiner Deploy Action



> [!IMPORTANT]

> This GitHub action no longer runs under its own docker image. The docker image has been deprecated and is replaced by .NET tools which makes it easier to create workflows/pipelines/... outside GitHub and still be able to deploy packages to DataMiner.

> You can still use this GitHub action in GitHub workflows. It will perform the dotnet tool calls on the current runner.



## **Important Changes Since Version 2.0.0**



- The **catalog identifier** (GUID identifying the catalog item on [catalog.dataminer.services](https://catalog.dataminer.services/)) is now required. It must be specified in a `catalog.yml` file as described [here](https://docs.dataminer.services/user-guide/Cloud_Platform/Catalog/Register_Catalog_Item.html#manifest-file).

  

- If a `README.md` file or an `Images` folder exists in the same directory (or a parent directory) as the `.dmapp` file, they will be automatically registered alongside the package.



- Either the repository’s name or a GitHub topic must be used to infer the catalog item type.



### **Inferring Catalog Item Type:**



The GitHub action can automatically determine the artifact type in two ways:



1. **Repository Naming Convention:**

   - If the repository follows the naming conventions outlined in the [GitHub Repository Naming Convention](https://docs.dataminer.services/develop/CICD/Skyline%20Communications/Github/Use_Github_Guidelines.html#repository-naming-convention), the tool can infer the type from the repository name itself without needing a GitHub topic.



2. **GitHub Topic:**

   - If the repository does not follow the naming convention, the tool relies on the presence of a GitHub topic that matches one of the [Artifact Types](#artifact-types) to determine the type.



If neither the repository name follows the convention nor the appropriate GitHub topic is present, the tool will fail to detect the type and return an error.



### Artifact Types



- **AS**: automationscript

- **C**: connector

- **CF**: companionfile

- **CHATOPS**: chatopsextension

- **D**: dashboard

- **DISMACRO**: dismacro

- **DOC**: documentation

- **F**: functiondefinition

- **GQIDS**: gqidatasource

- **GQIO**: gqioperator

- **LSO**: lifecycleserviceorchestration

- **PA**: processautomation

- **PLS**: profileloadscript

- **S**: solution

- **SC**: scriptedconnector

- **T**: testingsolution

- **UDAPI**: userdefinedapi

- **V**: visio



> [!IMPORTANT]

> Currently only Automation Script solutions are supported. This will limit the types to 'automationscript', 'gqidatasource', 'gqioperator', 'lifecycleserviceorchestration', 'profileloadscript' and 'userdefinedapi'.



## Transition to .NET Tools



Our workflow has evolved from relying solely on GitHub actions to embracing the versatility of .NET tools. This transition offers enhanced flexibility, enabling seamless integration across various widely utilized platforms such as GitHub, GitLab, Azure DevOps, and more.



The GitHub Action encompassed a bundled approach, performing three distinct tasks within a single docker image in the background:



1. Generating a package

1. Uploading the package to the Catalog

1. Deploying the package to a DataMiner



However, this bundled functionality didn't always align with the specific needs of our users. In response, we have modularized these tasks into individual .NET tools, allowing for tailored usage based on the unique requirements of each scenario.



Below, we present an example detailing the migration process from the GitHub action:



```yaml

       - name: Install .NET Tools

         run: |

           dotnet tool install -g Skyline.DataMiner.CICD.Tools.Packager

           dotnet tool install -g Skyline.DataMiner.CICD.Tools.CatalogUpload

           dotnet tool install -g Skyline.DataMiner.CICD.Tools.DataMinerDeploy



       - name: Create package name

         id: packageName

         run: |

          tempName="${{ github.repository }} ${{ github.ref_name }}"

          echo name=${tempName//[\"\/\\<>|:*?]/_} >> $GITHUB_OUTPUT

         shell: bash



       - name: Create dmapp package

         run: dataminer-package-create dmapp "${{ github.workspace }}" --type automation --version ${{ github.ref_name }} --output "${{ github.workspace }}" --name "${{ steps.packageName.outputs.name }}"



       - name: Upload to Catalog

         id: uploadToCatalog

         run: echo id=$(dataminer-catalog-upload with-registration --path-to-artifact "${{ github.workspace }}/${{ steps.packageName.outputs.name }}.dmapp" --dm-catalog-token ${{ secrets.api-key }} --artifact-version ${{ inputs.referenceName }}) >> $GITHUB_OUTPUT

 

       - name: Deploy to DataMiner

         run: dataminer-package-deploy from-catalog --artifact-id "${{ steps.uploadToCatalog.outputs.id }}" --dm-catalog-token ${{ secrets.DATAMINER_DEPLOY_KEY }}



```



More information on how to use these .NET tools can be found on their respective README files:



- [Creating a package](https://github.com/SkylineCommunications/Skyline.DataMiner.CICD.Packages/blob/main/Tools.Packager/README.md)

- [Uploading a package to the Catalog](https://github.com/SkylineCommunications/Skyline.DataMiner.CICD.Tools.CatalogUpload/blob/main/CICD.Tools.CatalogUpload/README.md)

- [Deploying a package to a DataMiner](https://github.com/SkylineCommunications/Skyline.DataMiner.CICD.Tools.DataMinerDeploy/blob/main/CICD.Tools.DataMinerDeploy/README.md)



## Github Action



This action builds a DataMiner Artifact from your Automation Script solution and deploys it to your cloud-connected DataMiner System. The action will wait until the deployment is finished, with a configurable timeout. At present, only DataMiner Automation Script solutions created by DIS are supported.



The action consists of 2 stages: `Upload` and `Deploy`.



## Stages



### Upload



This stage creates an artifact and uploads it to dedicated storage in the cloud. The output of this stage will be the ID of the artifact, which can be used in the deploy stage.



### Deploy



This stage deploys the artifact from the artifact storage to your cloud-connected DataMiner System.



## Limitations



This action currently only supports the creation of artifacts with Automation scripts.



## Inputs



### `api-key`



**Required**. The API key generated in the [DCP Admin app](https://admin.dataminer.services) to authenticate to a certain DataMiner System. E.g. `${{ secrets.NAME_OF_YOUR_APIKEY_SECRET }}`. For more information about creating a key, refer to the [DataMiner documentation](https://docs.dataminer.services/user-guide/Cloud_Platform/CloudAdminApp/Managing_DCP_keys.html).



### `solution-path`



**Required**. The path to the .sln file of the solution. At present, only DataMiner Automation Script solutions are supported. E.g. `'./Example/AutomationScript.sln'`. Required for stages `'Upload'` and `'All'`.



### `github-token`



**Optional**. The secrets.GITHUB_TOKEN.  Required for stages `'Upload'` and `'All'`.



### `artifact-name`



**Optional**. The chosen name for the artifact. E.g. `'MyPackageName'`. Required for stages `'Upload'` and `'All'`.



### `version`



**Optional**.

The version number for the artifact. Only required for a release run. Format A.B.C for a stable release or A.B.C-text for a pre-release. E.g. `'1.0.1'`. Required for stages `'Upload'` and `'All'` if no build-number was provided instead.



### `timeout`



**Optional-Deprecated**. The maximum time spent waiting for the deployment to finish, in seconds. Default '900'. E.g. `'300'`.



### `stage`



**Optional**. The stage of the action to run. Options are: `'Upload'`, `'Deploy'` and `'All'`. Default: 'All'.



### `artifact-id`



**Optional**. The private artifact to deploy. This is only needed when 'stage' is `'Deploy'`.



### `build-number`



**Optional**.

The build number of a workflow run. Only required for a development run. Required for stages `'Upload'` and `'All'` if no version was provided instead.



## Outputs



### `artifact-id`



The ID of the private artifact that has been deployed. This is only filled in for stages `'Upload'` and `'All'`.



## Example usage



### All stages at once



```yaml

on: [push]



jobs:

  deploy_artifact_job:

    runs-on: ubuntu-latest

    name: Deploy the artifact on the DataMiner System job

    steps:

      # To use this action, the repository must be checked out 

      - name: Checkout

        uses: actions/checkout@v4

      - name: Set up NuGet

        uses: nuget/[email protected]     

      - name: NuGet restore solution

        run: nuget restore "AutomationScript.sln" -OutputDirectory ${{ github.workspace }}/packages

      - name: Deploy the artifact on the DataMiner System step

        uses: SkylineCommunications/Skyline-DataMiner-Deploy-Action@v1

        id: deploy_artifact_step

        with:

          api-key: ${{ secrets.NAME_OF_YOUR_APIKEY_SECRET }}

          solution-path: './Example/AutomationScript.sln'

          github-token: ${{ secrets.GITHUB_TOKEN }}

          artifact-name: 'MyArtifactName'

          version: '1.0.1'

          timeout: '300'

```



### Separate stages



```yaml

on: [push]



jobs:

  build:

    name: build

    runs-on: ubuntu-latest

    outputs:

      ARTIFACT_ID: ${{ steps.Build_and_upload_artifact_step.outputs.ARTIFACT_ID }}

    steps:

      - name: Checkout

        uses: actions/checkout@v4

      - name: Set up NuGet

        uses: nuget/[email protected]     

      - name: NuGet restore solution

        run: nuget restore "AutomationScript.sln" -OutputDirectory ${{ github.workspace }}/packages

      - name: Deploy the artifact on the DataMiner System step

        uses: SkylineCommunications/Skyline-DataMiner-Deploy-Action@v1

        id: Build_and_upload_artifact_step

        with:

          api-key: ${{ secrets.NAME_OF_YOUR_APIKEY_SECRET }}

          solution-path: './Example/AutomationScript.sln'

          github-token: ${{ secrets.GITHUB_TOKEN }}

          artifact-name: 'MyArtifactName'

          version: '1.0.1'

          stage: Upload



  deploy:

    name: deploy

    runs-on: ubuntu-latest

    needs: build

    steps:

      - name: Deploy

        uses: SkylineCommunications/Skyline-DataMiner-Deploy-Action@v1

        with:

          api-key: ${{ secrets.NAME_OF_YOUR_APIKEY_SECRET }}

          stage: Deploy

          timeout: '300'

          artifact-id: ${{ needs.build.outputs.ARTIFACT_ID }}

```



## License



Code and documentation in this project are released under the [MIT License](https://github.com/SkylineCommunications/Skyline-DataMiner-Deploy-Action/blob/feature/preRelease/LICENSE.txt).