MLOps Strategy Development and Implementation Guide

This document is a guide focused on the development and implementation of an MLOps strategy. It outlines the importance of aligning developers and operations teams, recognizing that model engineering is part of a broader ecosystem necessary for achieving business objectives through machine learning. The guide emphasizes the need for multi-disciplinary skills in DevOps, data engineering, machine learning, and production operations to effectively plan and execute an MLOps strategy tailored to specific team needs and capabilities. Key deliverables include workshops on MLOps strategy, data engineering, and model engineering, along with a comprehensive data landscape summary. The guide also details the engagement process, which involves discovery workshops to assess current processes and technology landscapes, followed by designing data flows and implementation plans. The document highlights the use of AWS managed services and the AWS Well-Architected Machine Learning Lens to enhance the strategy and roadmap, ultimately aiming to facilitate successful machine learning adoption.