i have a github integrated Dev data factory and a Master data factory in azure. Now i want to use the Master Data factory's ARM template on the Dev data factory. Both of them have a set of common data sets, linked services, integration run times and triggers; also there are a few extra pipelines and data sets in the Master.
So if export the Master DF's ARM and use it on the Dev DF, will there be any overwrites/new creation of datasets/pipelines/ Intergration runtimes? Is it possible to do this in this way?
I would suggest you use git integration.
Then create Pull Request on Master DF. Now Approve and Merge Pull Request.
This way you will get All Linked Services and Datasets of Master DF into Dev DF.
For more information follow this official documentation
Related
Main problem:
I need to orchestrate the run of Python scripts using an Azure Data Factory pipeline.
What I have tried:
Databricks: The problem with this solution is that it is costly, a little slow (the need to spin up clusters), and it requires that I write my code in a notebook.
Batch activity from ADF: It too is costly and little slow. I don't have to write my code in a notebook, but I have to manually put it in a storage account, which is not great when debugging or updating.
My question:
Is there a way to run code in an Azure repo (or Github repo) directly from the Data Factory? Like the batch activity but instead of reading the code from a storage account read it from the repo itself?
Thanks for your help
Based on the statement in the document "Pipelines and activities in Azure Data Factory", the Azure Git Repos and GitHub Repos are not the supported source data store and sink data store for ADF pipelines. So, it is not possible to directly run the code from the git repository in the ADF pipelines.
However, ADF has the Source control option to allow you to configure a Git repository with either Azure Repos or GitHub. Then you can configure CI/CD pipelines on Azure DevOps to integrate with ADF. The CI/CD pipelines can directly run code from the git repository.
For more details, you can see the document "CI/CD in ADF".
I need to clone a copy of existing pipelines (pipeline count: 10-20) from one subscription to another subscription's (another ADF). Is there any way to do this activity using Azure Devops?
Option1:
Using Git Configuration, you can publish the data factory to the GIT branch. Connect your new data factory to the same repository and build from the branch. Resources, such as pipelines, datasets, and triggers, will carry through. You can delete the pipelines which are not used.
Option2:
You can manually copy the code (JSON code) of each pipeline, dataset, linked service and use the same code in the new data factory. (Use same names for when creating pipelines/datasets/linked services).
I am working on a migration project where I have a few SQL Server Integration Service projects that will be moved to Azure Data Factory. While I go through this we have a few jobs scheduled via SQL Server Agent which has multiple steps. If were to replicate the same using Azure Data Factory triggers is there a way to group multiple pipelines together and sequence the execution accordingly like we have multiple job steps in SQL Server Agents.
For instance:
Load all of the lookup tables
Load all of the staging tables
Load all of the dimension tables
Load Fact table
Please guide in the right direction.
You can use the Execute Pipeline Activity to build a master pipeline that runs your other pipelines. eg
I have a copy data pipeline in the Azure Data Factory. I need to deploy the same Data Factory instance in multiple environments like DEV, QA, PROD using Release Pipeline.
The pipeline transfer data from Customer Storage Account (Blob Container) to Centralized Data Lake. So, we can say - its a Many to One flow. (Many customers > One Data Lake)
Now, suppose I am in DEV environment & I have 1 demo customer there. I have defined an ADF pipeline for Copy Data. But in prod environment, the number of customers will grow. So, I don't want to create multiple copies of the same pipeline in production Data Factory.
I am looking out for a solution so that I can keep one copy pipeline in Data Factory and deploy/promote the same Data Factory from one environment to the other environment. And this should work even if the number of customers is varying from one to another.
I am also doing CI/CD in Azure Data Factory using Git integration with Azure Repos.
You will have to create additional linked services and datasets which do not exist in a non-production environment to ensure any new "customer" storage account is mapped to the pipeline instance.
With CI/CD routines, you can deliver this in an incremental manner i.e. parameterize you release pipeline with variable groups and update the data factory instance with newer pipelines with new datasets/linked services.
How to move all existing job to another Azure Datafactory.
I am trying to move existing job from one data Factory to another but not able to find the solution any suggestions, please.
As far as I know there is no easy import/export facility.
I recommend connecting your Data Factories to source control (GIT). You can then copy and paste the JSON definitions between the two repo's using a text editor.
For propagating pipelines between environments, you can look in to the documentation for CI/CD in Azure Data Factory.