@MohsenJOfficial Site wrote:
I'm a newbie to MLOps and abit confused about the use and the implementation of staging and testing environment in the mlops-stack template.
as far as I understand the staging environment is where we run the integration test. But in the ci-cd pipeline the integration_test is deployed and run the test target. And in the staging environment it deploys the all the workflow without running them. why is that? I'd appreciate any explanation.
Hello,
You're right, there's a subtle difference between how MLOps Stacks handles testing vs staging environments. Here's the breakdown:
Testing Environment: This is where you run unit tests and potentially some basic integration tests. These tests focus on individual components of your ML workflow (data processing, model training, etc.) in isolation. The CI/CD pipeline typically deploys the code for these tests and executes them directly.
Staging Environment: This environment mimics production as closely as possible. Here, you deploy the entire ML workflow but might not run all the steps automatically. Instead, the focus is on manually testing the integration between all components and ensuring everything works together seamlessly before pushing to production.
This separation allows for efficient testing:
Unit and basic integration tests are faster to run in the CI/CD pipeline, providing quicker feedback.
Staging lets you thoroughly test complex interactions and real-world data scenarios before risking production issues.
I hope the information may helps you.
