Fabric Data Science standalone vs. hybrid with Azure ML for production MLOps

Hi AlAmeenN 
Thanks for reaching out to Mircrosoft Fabric Community Forum.

• If your use case is primarily focused on data preparation, model training, experiment tracking and batch scoring within the Fabric ecosystem, Fabric Data Science may be sufficient and has the advantage of keeping everything in a single platform.
• However, if you're looking for more mature MLOps capabilities around model deployment, monitoring, governance, dedicated compute resources or advanced CI/CD workflows, it may be worth evaluating Azure Machine Learning alongside Fabric.
• A key consideration is also how your workloads are expected to scale. Since Fabric workloads share capacity resources, organizations with larger or more demanding ML workloads sometimes whether dedicated Azure ML compute provides additional operational flexibility.

For additional guidance, you may refer to the following documentation:
Overview of Microsoft Machine Learning Products and Technologies - Azure Architecture Center | Microsoft Learn
IDEAS journey to a modern data platform with Fabric - Microsoft Fabric | Microsoft Learn

Hope this helps!!

Thank You.