Create a Code-With Experience between partners and customer, driving in the best practices deploying a MLOps solution using trunk-based development, for understanding best practices of Machine Learning Operationalization and Software Engineering combined.​

Automation: Automated processes with a reduced lead time, delivering value faster and frequently.​

Engineering Practices: Land Agile and Software Engineering Practices contributing to maturity levels and impacting the Developer Velocity Index​.

Knowledge Transfer: Empowered and Skilled Developers and Engineers, leaving them with more confidence and knowledge to build solutions inside Azure.​

• DevOps​
• Infrastructure as Code​
• MLOps

• Software Engineers
• Data Engineers
• Data Architects

In this workshop, you will deploy a MLOps reference arquitecture. It demostrates how apply the worflow in a sample project along with a CI/CD implementation for Azure DevOps.

1. Follow these quickstart instructions to setup your lab environment before starting the Hands-On Lab.

2. Follow the Hands-On Lab instructions.

• Azure DevOps
• Azure Machine Learning
• Azure Data Lake Storage Gen2
• Azure Data Factory
• Azure Event Grid

We welcome feedback and comments from Microsoft SMEs & learning partners who deliver this workshop.

Having trouble?

• First, verify you have followed all written lab instructions (including the quickstart documents).
• Next, submit an issue with a detailed description of the problem.
• Do not submit pull requests. Our content authors will make all changes and submit pull requests for approval.

If you are planning to present a workshop, review and test the materials early! We recommend at least two weeks prior.

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