Introduction
The final section of this blog series will cover the process of creating and deploying the machine learning project using Azure DevOps.
MLOps Architecture
Prerequisite
Azure DevOps Account
Databricks Workspace
Setup CI/CD pipeline
Step 1: Get the Project Template
Step 2: Understand YAML Pipeline Structure
Step 3: Update master yaml pipeline
3.1 Get your Databricks URL and update.
Step 4: Create Azure Artifact Feed
Step 5: Update build-publish template
Get the created feed name and update the template
Step 6: Create the Master Pipeline
Step 7: Create variable of Databricks token
Run the Pipeline
Step 6: Udpate the Feed detail in the deploy-to-environment
Once build part is run now you can fetch the feed details since the feed update with package.
Instruction on how to fetch given in the troubleshooting section below.
Update the template wiht the created feed value.
Vaildate the Deployment
Best Practices & Tips
Version control
Deploy to Prod from Main branch only
Security consideration
Key vault to store the Secret.
Orchestrate Job run using Airflow
Troubleshooting
Issue: Forbidden Error during the Artifact download
Solution: Make sure Build service has the Contibutor access assigned.
How to fetch the Azure Artifact Feed Detail
Step: 1 Make sure the Feed is created and you have Package in it.
In my case the package is availble in the Azure Artifact Feed.
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