The Machine Learning Solutions Architect Handbook

Chapter 9: Building an Enterprise ML Architecture with AWS ML Services

To support a large number of fast-moving machine learning (ML) initiatives, many organizations often decide to build enterprise ML platforms capable of supporting the full ML life cycle, as well as a wide range of usage patterns, which also needs to be automated and scalable. As a practitioner, I have often been asked to provide architecture guidance on how to build enterprise ML platforms. In this chapter, we will discuss the core requirements for enterprise ML platform design and implementation. We will cover topics such as workflow automation, infrastructure scalability, and system monitoring. You will learn about architecture patterns for building technology solutions ...