Ebook

AI Observability in Action: Keeping Your ML Models on Track with Real-Time Insights

Rare are the data science and engineering teams who are prepared for “Day 2”—the day their models meet the real world. While most teams invest the majority of their time researching, training, and evaluating models, many are unprepared for the challenges that arise in production. The result? A lack of clear processes, tools, and strategies to monitor models effectively once deployed.

This eBook offers a comprehensive, production-first framework for anyone building, testing, or scaling real-time AI systems. Whether you're responsible for AI infrastructure, model reliability, or governance, this guide will help you level up your observability strategy.

Inside, you’ll discover:

• A blueprint for full-lifecycle AI agent operations—from build to monitor to govern

• Real-world examples of observability in action (not just metrics, but meaning)

•  How to spot model drift, bias, and degradation before your outcomes take a hit

•  Tips to reduce alert fatigue and streamline handoffs across MLOps, IT, and governance

•  A breakdown of the AgentOps Platform including Essentials, Professional, and Enterprise tiers