Summary
In this chapter, you experienced the essential tasks surrounding MLOps. You built a complete automated pipeline that trains a model, publishes the model to the model store, and deploys it to a model-serving infrastructure, all with RHODS. You also created a pipeline that can perform rollbacks of model deployments. Finally, you implemented a canary deployment setup for your model deployments. These are the essential skills an MLOps engineer needs.
One thing to note is that RHODS is evolving fast. New versions are getting released frequently and by the time you are reading this book, the screens may look a bit different and some of the methods of configuring the platform may change a little. We suggest that when performing the exercises in this book, you use OpenShift version 4.13.
In the next chapter, we will take you through the operational tasks of MLOps. These are the activities that you must perform after deploying a model to production. They include monitoring, logging...
