Introducing chaos engineering to Machine Learning deployments
By Vivek Raja; Data Scientist, NexStemA data scientist’s worst nightmare is seeing their Machine Learning model deployment fail at production. But there are ways to ensure that the deployment targets are resilient enough to handle incoming prediction traffic. This blog charts out a way to establish a well-architected Azure solution by applying chaos engineering approaches