The AWS Well-Architected Framework: A Focus on Machine Learning

In recent years, machine learning has transitioned from the realm of research and development to becoming widely adopted, driven by the proliferation of data sources and scalable cloud computing resources. AWS customers now leverage AI/ML across diverse applications such as call center operations, personalized recommendations, fraud detection, social media content moderation, audio and video analysis, product design, and identity verification. Industries benefiting from AI/ML include insurance, healthcare, manufacturing, finance, media, and telecom. Machine learning, with its ability to uncover patterns in data through algorithms, empowers users significantly, emphasizing the importance of responsible deployment. AWS is dedicated to developing AI and ML services that are fair and accurate, providing tools and guidance for building responsible AI and ML applications. This paper outlines proven best practices for designing and continuously improving ML workloads, offering guidance and architectural principles applicable across cloud platforms while including specific resources for implementing these practices on AWS.