I am setting up an environment for ADF. I have multiple projects and Segments which I need to support. I have noticed that I can only set up one publish branch in ADF.
Should we create ADF for each project?
What is the recommended approach for setting up an environment ?.
Multiple ADFs are required if there is complete different project with different data. If you want to work in same project and just need to manage different environment like development, testing and prod; all this can be managed in one ADF.
A developer creates a feature branch to make a change. They debug their pipeline runs with their most recent changes. For more information on how to debug a pipeline run, see Iterative development and debugging with Azure Data Factory.
After a developer is satisfied with their changes, they create a pull request from their feature branch to the main or collaboration branch to get their changes reviewed by peers.
After a pull request is approved and changes are merged in the main branch, the changes get published to the development factory.
When the team is ready to deploy the changes to a test or UAT (User Acceptance Testing) factory, the team goes to their Azure Pipelines release and deploys the desired version of the development factory to UAT. This deployment takes place as part of an Azure Pipelines task and uses Resource Manager template parameters to apply the appropriate configuration.
After the changes have been verified in the test factory, deploy to the production factory by using the next task of the pipelines release.
Note
Note: Only the development factory is associated with a git repository. The test and production factories shouldn't have a git repository associated with them and should only be updated via an Azure DevOps pipeline or via a Resource Management template.
Related
I have a situation here where I import resources from my Azure DevOps Git repository DEV to TEST, I want DEV code to be independent of TEST and not commit my changes back to the repository.
After I import the repository to TEST I made changes to the SQL database connection string in the copy activity source and sink in TEST and had to commit the changes for the debug to run and the triggers I have setup for the pipelines don't run in TEST as per the schedule and fail in DEV because of the changes I did in TEST.
When move the pipelines and underlying objects to different environments, How do I make all the environments independent once I import repository? Is there a way to copy from the repository to the Synapse live mode to accomplish this?
OR How would I automate deployment of Synapse pipelines? Is it using ARM or Bicep Template?
You'll want to follow Microsoft's guide on CI/CD with Synapse. This is a great walkthrough video for the process.
The flow is:
Work in your development environment and commit to your collaboration branch.
A pipeline triggers off of your workspace_publish branch, releasing your code to your next environment (preferably with an approval gate)
Continue releasing the same code to higher environments, again with approval gates.
For Azure DevOps, you can use variable groups to parameterize your pipeline. Also make sure to read through the custom parameters section on that link to parameterize parts of the template that are not parameterized by default.
I have two instances of Azure Data Factory in which one is integrated with GIT repo and another is not.
I have taken ARM templates from non GIT ADF instance using Export ARM template option.
I have to deploy this ARM template in the second ADF instance using azure DevOps pipeline.
How should I do this process using the devOps pipeline.
Is there any way to fetch this downloaded ARM templates using devOps pipeline and deploy in another ADF instance?
Also before deployment I have to replace some text in the json files. (ex: instance01/tmp/file to instance02/tmp/file) Is there any shell script that can be make use here?
Deploying the code to the other Data Factory will not be a problem.
After downloading the ARM template for the non Git integrated one there should be a parameter for what Data Factory you are deploying to. It would be as simple as updating that parameter to point to the other instance of Data Factory and deploying the ARM template either via Azure DevOps or Powershell w/ the Incremental deployment. This is possible since the deployment will do a delta and each pipeline/linked service/ data set will be it's own resource it should deploy the new. Just be careful if there are any conflicts on the naming standard.
The issue you will run into will be the source code definition. The way the CI/CD integration works is the collaboration branch, usually master, is defined and when clicking publish the changes are consolidated and pushed to adf_publish by default. The adf_publish will be the definition of the Data Factory that is published. Since we are publishing outside of a repository neither the master nor adf_publish will have any knowledge of the changes. Unfortunately given that adf_publish cannot merge back into master the best way might be to stand up a new repo or reimport the data factory definition after the manual publish has occurred.
I have a data factory instance which is linked to github, used for development.
I am having two different changes in the two different branches of data factory.
change01 and change02
I have merged these two changes into master branch and did a publish.
While doing a CI/CD even though these two changes are now available in the dev data factory instance, is it possible to deploy only change01 into other environments?
How can we control which release/change should go for deployment into other environments?
Can we do a build directly from a branch and push to prod?
To best accomplish this will have to to publish outside of the Data Factory editor. Each branch contains the necessary ARM components to publish the Data Factory ARM templates. The issue is when clicking the publish button Data Factory/ADO behind the scenes consolidates the ARM templates to just one .json file to make it easier to deploy while simultaneously deploying to the Data Factory destination.
The best course of action here might be to determine how to publish the ARM templates w/o clicking the publish button. This can be done by using ARM deployments or Powershell.
Furthermore I'd consider the potential options you have when considering how to managed and deploy Data Factory under CI/CD.
I would suggest to use separate branch and configure your builds to use proper one. Verify you builds in Azure Dev Ops.
It can be also helpful to cherry-pick changes which shouldn't be deployed.
I'm working on an API in core3.1. We have a build pipeline that builds and unit tests any change for any branch. And release pipelines for development and master branches. These deploy to designated app services in Azure.
Now we would like a release pipeline for feature branches. So what we want is a pipeline that can dynamically created app-services per feature branch and deploy to that app service. And preferably dynamically delete the app-service when the branch is deleted.
Just to clarify, the proces how we would like it:
a developer creates feature branch and pushes it >
the build pipeline builds it >
an app service gets created automatically >
stuff gets deployed to that app service >
developers work on the branch and changes get build and deployed to the app service like normal >
at some later point a developer deletes branch >
app service gets deleted automaticcaly
Is there any way to accomplish this? Maybe there is a standard way?
Feature branches are located in a subfolder, e.g. "feat/feature-branch-name".
I'm fairly new to Azure and DevOps.
Any help is appriciated. Thanks in advance.
You should follow the practice of Infrastructure as Code (IaC) and use ARM templates in your pipeline to create/update/delete your Azure resources. You can also use the built-in tasks available in Azure DevOps to deploy your ARM templates.
Is that possible?
It would be very convenient, to have all branches with an open PR deployed somewhere, where I can have a shareable link.
There are the PR-Branch Triggers, but AFAIK it can only deploy one branch to one environment at the time. And another PR update would just overwrite the state.
EDIT to clarify what I mean:
Each feature branch (or bugfix or whatever) of our webapp should be deployed to an app service (or whatever), so when we create the feature, we always have a link to share during development, in which our designers (or whoever) could find issues in early development. At another cloude storage provider, we had something like that and we would always receive a unique link after successful deployment.
I'm a bit late but working on this now. What I intend to do:
Pull request on selected feature branches triggers task 2
Task will create app services via Terraform (Link)
Use the 'app service deploy' task to push the artifact from that pull request to the new app service created in the prior task.
We'll see how it goes
If deploying each feature branch to an app service is what you are trying to achieve.
You can try below steps(Only for classic pipeline view):
1,In your CI build pipeline, Go to triggers page, add each of your feature branch to branch filters, So that each Pull request made to your feature branch can trigger a build.
2, in your CD release pipeline(Classic view), add different stages, each for an artifacts which built from feature branches:
3, for each stage, In the pre-deployment conditions page, add an artifacts filters to its corresponding feature branch. So that the artifacts from this specific feature branch will trigger to deploy its corresponding stage.
4, Change the settings and parameters of the tasks in each stage according to each feature branch. So that each app service deployed for each feature branch has its own settings and configurations,
5,Configure your app service deploy tasks in each stage.
With above steps done,each time when a new pull request is merged to the feature branch, the corresponding stage will be automatically triggered to deploy this pull request to the configured app service.