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Super UserBest Way to do CICD for data Science workloads
Hi Srisakthi , for ML Models, you have 2 options. You can use the built-in Fabric deployment pipelines or you can leverage a Git integration to use a service such as Azure DevOps. Both are fully supported. Here is some documentation below:
Super UserHi Srisakthi ,
Which data science workloads are you leveraging? For CI/CD in Fabric, there are a few methodologies you can use. The one I have used is connecting Azure DevOps to a development workspace and leveraging the built-in Fabric Deployment Pipelines as a release pipeline to subsequent environments (test/prod). Here are some additional documentation on methodologies here: https://learn.microsoft.com/en-us/fabric/cicd/manage-deployment
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Thanks,
Samson
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Super UserHi SamsonTruong ,
The link which you have shared is a generic Fabric CICD. I'm looking for is Data Science Workloads.
To give you high level information of data science workload is all about creating deploying ML models, data agents etc.
Regards,
Srisakthi