Testing and monitoring are essential for stable machine learning solutions. However, not many companies have operationalized ML prototypes yet. As a result, there is little experience as to which tests are important and how exactly monitoring should take place. This presentation introduces some of the best practices of ML pioneer Google. Learn how to design tests for ML applications in the areas of data, models, infrastructure and monitoring.