Enhancing Incident Response with AI - Assisted Runbooks: A Framework for Smarter Troubleshooting

Site Reliability Engineering (SRE) teams rely on runbooks to help them troubleshoot and manage incidents, but traditional runbooks can be rigid, outdated, and hard to maintain - especially in fast - evolving tech environments. This paper explores how integrating AI - assisted runbooks, powered by structured prompts, can make incident response faster, more efficient, and more reliable. We present a framework that uses Large Language Models (LLMs) and structured prompting to create flexible, context - aware troubleshooting guides. Techniques like few - shot prompting, chain - of - thought reasoning, and self - refinement are key to this approach.

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Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2025-02-15
DOI
https://doi.org/10.21275/sr25212002547
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Incident Response with AI - Assisted Runbooks: A Framework for Smarter Troubleshooting

Binoj Melath Nalinakshan Nair
International Journal of Science and Research (IJSR)
Anomaly Detection Techniques and Applications
article

Enhancing Incident Response with AI - Assisted Runbooks: A Framework for Smarter Troubleshooting

Binoj Melath Nalinakshan Nair
article en

Abstract

Site Reliability Engineering (SRE) teams rely on runbooks to help them troubleshoot and manage incidents, but traditional runbooks can be rigid, outdated, and hard to maintain - especially in fast - evolving tech environments. This paper explores how integrating AI - assisted runbooks, powered by structured prompts, can make incident response faster, more efficient, and more reliable. We present a framework that uses Large Language Models (LLMs) and structured prompting to create flexible, context - aware troubleshooting guides. Techniques like few - shot prompting, chain - of - thought reasoning, and self - refinement are key to this approach.

International Journal of Science and Research (IJSR)Vol. 14(2)
Openalex Percentile: Top 99%
Anomaly Detection Techniques and Applications
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