MLOps solution components
01.
Data storage

Azure Blob Storage for data storage.

02.
Model training, validation, and registration

Azure Machine Learning workspace.

03.
Model deployment

Azure Machine Learning endpoints and Azure Kubernetes Service.

04.
Model monitor

Azure Monitor for Application Insights.

05.
MLOps pipelines

Azure DevOps and Azure Pipelines.

A standard framework is instrumental in successfully deploying ML models in production.

It plays a pivotal role in managing risks as organizations scale the number of ML applications across various use cases within dynamic environments. Furthermore, it is a steadfast guide to ensure that these applications consistently align with the overarching business objectives, maintaining a harmonious synergy between technology and strategy.

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