Slides of a presentation b y Ridhav Mahajan Mahajan at the Chief Data & Analytics Officer Sydney on March 21st 2018. "If you have put machine learning models into production, you’ve lived the truth of the maxim that 90% of what makes machine learning work is the logistics, not the learning. That 90% comes from many things, including the need to stage and deploy multiple versions of each model, to carefully collect and curate updated training data and to monitor model performance. Lately we have added scale, speed and the need to handle multiple machine learning frameworks at the same time to make the problem more difficult. This talk will cover Rendezvous architecture, that uses recent advances in streaming micro-services, containerization, and orchestration and solved many of the problems involved in continuous deployment of machine learning models."