Answer
It covers the full lifecycle of a model, from development and testing to deployment, monitoring, and retraining, using automated processes similar to modern software engineering practices.
Real-world example A company uses MLOps practices to automatically retrain and redeploy its recommendation model every time new customer data becomes available.