SRE with AIOps : Building resilient systems with AIOps, ML-driven observability, and agentic AI

Description: 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....

সম্পূর্ণ বিবরণ

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Behl, Shalini, 1983-, Kanikarapu, Giridhar (Author)
বিন্যাস: Livre numérique
ভাষা:Anglais
প্রকাশিত: New Delhi : BPB Publications 2026.
Paris : Cyberlibris
অনলাইন ব্যবহার করুন:Accès Université d'Orléans et IFPM
টীকা: Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789378542343.jpg
Cyberlibris (ScholarVox) corpus Informatique
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• SRE with AIOps, Building resilient systems with AIOps, ML-driven observability, and agentic AI, Sunny Behl, Giridhar Kanikarapu, New Delhi, BPB Publications, 2026, 1 vol. (337 p.), 978-93-7854-234-3
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041 0 |a eng 
100 1 |a Behl, Shalini,  |d 1983- 
245 1 0 |a SRE with AIOps :  |b Building resilient systems with AIOps, ML-driven observability, and agentic AI   |c Sunny Behl, Giridhar Kanikarapu. 
260 |a New Delhi :  |b BPB Publications. 
260 |a Paris :  |b Cyberlibris,  |c 2026. 
500 |a Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789378542343.jpg 
500 |a Cyberlibris (ScholarVox) corpus Informatique 
505 0 |a 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 
506 |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris 
520 |a Description: 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 
700 1 |a Kanikarapu, Giridhar.  |4 aut 
776 0 |t SRE with AIOps  |o Building resilient systems with AIOps, ML-driven observability, and agentic AI  |f Sunny Behl, Giridhar Kanikarapu  |c New Delhi  |n BPB Publications  |d 2026  |p 1 vol. (337 p.)  |z 978-93-7854-234-3 
856 4 |5 452349901:89403118X  |u https://ezproxy.univ-orleans.fr/login?url=https://univ.scholarvox.com/book/88980639  |z Accès Université d'Orléans et IFPM 
997 |0 1478025  |1 Livre numérique  |a Ressource numérique  |b INSA  |b ENSA  |c 0/Bibliothèque numérique/  |c 1/Bibliothèque numérique/ScholarVox (ebooks)/