Machine Learning Lens - AWS Well-Architected Framework - Machine Learning Lens

This whitepaper is in the process of being updated.

Machine Learning Lens - AWS Well-Architected Framework

Publication date: April 2020 (Document Revisions)

Abstract

This document describes the Machine Learning Lens for the AWS Well-Architected Framework. The document includes common machine learning (ML) scenarios and identifies key elements to ensure that your workloads are architected according to best practices.

Introduction

The AWS Well-Architected Framework helps you understand the pros and cons of decisions you make while building systems on AWS. Using the Framework, allows you to learn architectural best practices for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. It provides a way for you to consistently measure your architectures against best practices and identify areas for improvement. We believe that having well-architected systems greatly increases the likelihood of business success.

In the Machine Learning Lens, we focus on how to design, deploy, and architect your machine learning workloads in the AWS Cloud. This lens adds to the best practices included in the Well-Architected Framework. For brevity, we only include details in this lens that are specific to machine learning (ML) workloads. When designing ML workloads, you should use applicable best practices and questions from the AWS Well-Architected Framework whitepaper.

This lens is intended for those in a technology role, such as chief technology officers (CTOs), architects, developers, and operations team members. After reading this paper, you will understand the best practices and strategies to use when you design and operate ML workloads on AWS.