The Architectures Powering Machine Learning at Google, Facebook, Uber, LinkedIn

One thing that we can do to mitigate those risks is to draw inspiration from some of the biggest companies in the world that are deploying machine learning at scale. Today, we would like to discuss some of the reference architectures used by AI powerhouses like Google, Facebook, LinkedIn, and Uber to enable their machine learning pipelines. One of the best-known efforts in this area, Uber's Michelangelo is the runtime powering hundreds of machine learning workflows at Uber. From experimentation to model serving, Michelangelo combines mainstream technologies to automate the lifecycle of machine learning applications. The architecture behind Michelangelo uses a modern but complex stack based on technologies such as HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.