why-sophistication-will-win-out-in-the-machine-learning-ops-sector

MLOps tools are critical to companies deploying data-driven models and algorithms. If you develop software, you need tools that allow you to diagnose and anticipate problems with software that could cause you to lose meaningful revenue due to its failure. The same is true for companies that build data-driven solutions. If you don't have adequate MLOps tools for evaluating models, monitoring data, tracking drift in model parameters and performance, and tracking the predicted vs. actual performance of models, then you probably shouldn't be using models in production-critical tasks.