Enterprise AI Architecture — Volume II: Running the Stack
Building AI applications is only the beginning. The real challenge is operating, governing, securing, and scaling AI systems in production.
Enterprise AI Architecture — Volume II Running the Stack provides a practical framework for managing the operational layers of modern enterprise AI systems. Built around the Nine-Layer Enterprise AI Architecture, this volume focuses on the technologies, processes, and governance practices required to move from successful prototypes to reliable enterprise platforms.
Covering MLOps, model serving, observability, evaluation, governance, security, compliance, and enterprise operations, this book equips architects, engineers, and technology leaders with the tools and patterns needed to run AI systems safely and effectively at scale.
Whether you are deploying your first production AI workload, establishing an enterprise AI platform, or defining governance controls for responsible AI adoption, this volume offers practical guidance grounded in real-world architecture principles and operational best practices.
In This Volume You will Learn
- Enterprise AI operational architectures
- Model serving and inference platforms
- MLOps and model lifecycle management
- Observability and evaluation frameworks
- AI governance and guardrail strategies
- Security, compliance, and risk management
- Enterprise platform engineering practices
- Production readiness and operational excellence
- Scalability, reliability, and performance optimization
- Building sustainable AI operating models
Designed For
- Enterprise Architects
- AI Architects
- Solution Architects
- Platform Engineers
- MLOps Engineers
- Security and Governance Teams
- CIOs and CTOs
- Technology Leaders
Enterprise AI Architecture — Volume II serves as a practical field guide for organizations seeking to operate AI systems that are scalable, observable, governable, secure, and built to last.