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AI-First Observability: Predictive Insights for Ops: Designing Intelligent, Self-Observing, Predictive, and Autonomous Operations for Modern Cloud, AI
Paperback
Publisher: Independently Published
Published: Jun 27 2026
Pages: 430
Weight: 2.18
Height: 0.87 Width: 8.50 Depth: 11.00
Language: English
Stop monitoring systems. Start building enterprises that think.
Modern enterprises generate billions of telemetry events every day-but visibility alone no longer guarantees reliability. The future belongs to organizations that can predict failures, understand complex systems, automate intelligent decisions, and continuously learn from every operational event.
AI-FIRST OBSERVABILITY is a practical, enterprise-grade guide to transforming traditional monitoring into predictive, autonomous, and business-aware operations. Written for architects, SREs, platform engineers, DevOps leaders, cloud professionals, and technology executives, this book shows how AI reshapes observability from passive dashboards into intelligent operational decision-making.
Inside, you'll learn how to:
- Build AI-first observability architectures for modern enterprises
- Engineer intelligent telemetry with OpenTelemetry
- Apply AI for anomaly detection, root cause analysis, and incident prediction
- Design knowledge graphs and digital twins for operational intelligence
- Implement LLM-powered operations copilots and Agentic AIOps
- Create self-healing, policy-governed autonomous operations
- Master Kubernetes, cloud-native, hybrid, multi-cloud, and edge observability
- Integrate observability with security, compliance, FinOps, and GreenOps
- Connect operational intelligence directly to business outcomes
- Govern AI responsibly with explainability, transparency, and enterprise controls
- Lead organizational transformation toward AI-first operations
- Design the autonomous enterprise of the future
Packed with enterprise architecture patterns, production lessons, realistic case studies, implementation frameworks, recommended diagrams, and 17 hands-on masterclass labs, this book goes far beyond explaining logs, metrics, and traces.
If you're ready to move from reactive monitoring to predictive intelligence, autonomous operations, and organizational intelligence, this book provides the roadmap.
Build systems that don't just report problems-build enterprises that understand themselves.
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