Engineering MLOps: From Model to Production, Emmanuel Raj, Larysa Visengeriyeva, Arpit Shah, 2022 (O'Reilly Media) - A comprehensive book covering the full MLOps lifecycle, including advanced deployment strategies like canary releases and A/B testing specifically for machine learning models.
Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing, Ron Kohavi, Diane Tang, Ya Xu, 2020 (Cambridge University Press) - This authoritative guide provides deep insights into designing, running, and analyzing online experiments, making it highly valuable for implementing rigorous A/B testing in production ML systems.
MLOps: A guide to the machine learning lifecycle, Google Cloud, 2024 - Official Google Cloud architecture guide discussing MLOps principles, including continuous delivery and experimentation strategies for deploying and managing machine learning systems at scale.