An SCM such as Git is more than just a database for source code. It’s not only the thing you need to interact with to get code to production, but also a log of changes on a project. It’s not just the last couple of weeks of commits that are worth looking at. Any commit remains relevant weeks, months and years later. A commit serves multiple purposes. The first one is to explain a change during its review and the second is to explain a change to a future reader.

For decades, machine learning engineers have struggled to manage and automate ML pipelines in order to speed up model deployment in real business applications. Similar to how software developers leverage DevOps to increase efficiency and speed up release velocity, MLOps streamlines the ML development lifecycle by delivering automation, enabling collaboration across ML teams and improving the quality of ML models in production while addressing business requirements.

All good things need to come to an end. In this case, that’s true of the Sauce Sample Test Frameworks GitHub organization. While these sample frameworks are now gone, they’re not forgotten. In fact, we’ve replaced them with something better. In the past, this organization provided barebones examples of connecting to Sauce Labs with sample frameworks in a large variety of languages and tools. These frameworks were mainly based on Selenium and testing a basic web page.