CD Pipeline Deploy & Validate Azure Endpoints with PyTest

🔄 End-to-End ML Pipeline: Deploy & Validate Azure Endpoints with PyTest
Automated Testing & Validation Framework for Production ML Models
*Description:*
Complete solution for deploying and validating machine learning models in Azure with automated testing! This repository showcases a professional ML pipeline that combines Azure ML deployment with comprehensive PyTest validation. Features both deployment workflows and automated integration tests ensuring your endpoints are production-ready and reliable.
🔍 Pipeline Highlights:
Automated endpoint deployment with Azure ML CLI
Integration testing with PyTest
Code coverage reporting (XML & HTML)
Automated endpoint validation
Security credential management
JUnit XML test reporting
⚙️ Technical Stack:
Azure ML Online Endpoints
PyTest Testing Framework
Azure CLI Integration
Coverage Reports
JUnit XML Reports
🎯 Perfect for: MLOps Engineers, ML Platform Teams, and QA Engineers looking to implement robust testing for ML deployments
More Azure Learning Resources:
Code: [github.com/Dee...]
Azure Machine Learning (DP-100) Playlist: [ • Azure ml ]
Azure DevOps Playlist: [ • azure devops ]
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Medium: [ / deepp.knowledge ]
*Essential Hashtags:*
#mlops #azureml #pytest #testing #mlvalidation #cicd #modeldeployment #endpointvalidation #integrationtesting #mlplatform #modelmonitoring #testautomation #pythontesting #datascience #devops #azure #codecoverage #qualityassurance #mlengineering #continuoustesting #modelvalidation #automatedtesting #mlpipeline #testframework #productionml