Consistency and AIOps/MLOps – reliance and trust

Maintaining trust, reliance, and consistency within your internal product teams as well as with your customer base is an act of committing to a specific ritual. Ritualizing the acquisition of clean data, tracking the flow through your infrastructure, tracking your model training, versions, and experiments, setting up a deployment schedule, and monitoring pipelines that get pushed to production are all part of the necessary work that needs to be done to make sure there’s a handle on the comings and goings of your AI/ML pipeline. This ritualizing is what’s referred to as MLOps or AIOps. In this section, we will explore the benefits of AIOps/MLOps and how they help you stay consistent.

If you’re managing an ML pipeline, you will need to learn how to depend on an MLOps team and set up your team for success. You don’t want to get caught losing $20,000 in 10 minutes (as we saw in our Profit margins section...