ML Governance is often discussed either in abstract terms without practical details or using detailed AI ethics examples. This talk will focus on the day-to-day realities of ML Governance. How much documentation is appropriate? Should you have manual sign-offs? If so, when and who should perform them? When is an escalation needed? What should a governance board do? What if you are in a regulated industry? How can MLOps help? And most importantly, what is the point of all this governance and how much is too much? This talk will show how each organisation can best answer these questions for their own context by referring to examples and public resources.