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SRE with AIOps Building resilient systems with AIOps, ML-driven observability, and agentic AI [#1031377]
SRE with AIOps
by Sunny Behl, Giridhar Kanikarapu
English | 2026 | ISBN: 9378542344 | 282 pages | True EPUB | 9.64 MB
As digital ecosystems grow more complex and customer expectations reach new heights, the convergence of site reliability engineering (SRE) and artificial intelligence for IT operations (AIOps) is redefining how modern enterprises ensure resilience, performance, and reliability at scale. Intelligent automation and data-driven operations are no longer optional; they are the foundation of competitive advantage. This book is your essential guide to merging these two powerful disciplines to build faster, smarter, and more resilient operations.
This book begins with the foundational principles of SRE: SLOs, SLIs, error budgets, and toil reduction, before progressing through AIOps tooling, observability, and the unified knowledge base. Readers explore intelligent incident management, change and problem management, advanced anomaly detection using autoencoders and isolation forests, causal inference for root cause analysis, and the AIOps-powered SRE assistant. The book also explores chaos engineering, generative AI-powered SRE chatbots, and enterprise-scale AIOps adoption, culminating in a strategic roadmap for autonomous operations, predictive governance, and the role of LLMs and agentic AI in the future of reliability engineering.
By the end of this book, readers will possess both the strategic mindset and the technical depth to architect, lead, and scale intelligent operations. Whether you are an SRE practitioner, IT architect, or technology leader, you will be equipped to move from reactive firefighting to proactive, self-healing operations, delivering measurable reliability and business impact.
What you will learn
● Apply SRE principles, SLOs, SLIs, and error budgets effectively.
● Evaluate and operationalize AIOps platforms for SRE goals.
● Build unified observability models from logs, metrics, and traces.
● Automate incident triage, correlation, and postmortem workflows.
● Deploy advanced anomaly detection using ML models.
● Design chaos engineering experiments to validate SLOs.
● Architect generative AI chatbots for incident and runbook automation.
● Scale AIOps across enterprise teams with measurable outcomes.
Who this book is for
This book is for SREs, IT operations managers, cloud architects, and technology leaders who want to evolve from traditional operations to intelligent, AI-driven reliability practices. Readers should have intermediate experience in DevOps, SRE, or IT operations and a working familiarity with monitoring tools and cloud infrastructure.
Table of Contents
1. SRE Principles Driving Modern Operations
2. AIOps Tools for SRE
3. AIOps Knowledgebase
4. Intelligent Incident Management for SREs
5. Streamlining Change and Problem Management
6. Path to Productivity and Reliability
7. Advanced Anomaly Detection
8. Causal Inference and Efficient Root Cause Analysis
9. Intelligent SRE Assistant
10. Chaos Engineering and Reliability Testing
11. Generative AI-powered SRE Chatbot
12. Scaling AIOps Across the Enterprise
13. Future Trends in SRE and AIOps
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