ML Ops For Databricks
ML Ops support for Databricks
🔗MLOps for Databricks Repository🔗
Accelerator Description
The ML Ops for Data Bricks solution accelerator provides a deployable solution that can be used by data engineering and data science teams to:
- ​​​​​​​​​​​​​​Logging Framework using the Opensensus Azure Monitor Exporters.
- Support for Databricks development from VS Code IDE using the Databricks Connect feature.
- Continuous development with Python Local Packaging.
- Implementation of the Databricks utilities in VS Code such as dbutils, notebook execution, secret handling.
- Example Model file which uses the framework end to end.
Components
This solution accelerator featured on an epsiode of the AI Show, Seth welcomes Microsoft Data Scientist, Spyros Marketos, ML Engineer, Davide Fornelli and Data Engineer, Samarendra Panda. Together they make up an AI Taskforce and they will showcase a high-level intro into MLOps and share some of the surprises and lessons they've learned along the way!
Prerequisites
- Access to an Azure subscription.
- Service Principal (valid Client ID and secret) which has the contributor permission the subscription.
- VS Code installed.
- Docker Destop installed.
Use Case
- Enterprise scale data engineering and data science development framework.
- ML Ops to help data science teams collaborate accross the organization.
- AI Solution Centre or Centre of Excellence.