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What the DOI identifies

AI-Powered Chatbot Solution for Efficient Network Troubleshooting in Hybrid Cloud Environments

10.46243/jst.2026.v11.i04.pp01-15 · JournalArticle — an article in a journal · Digital · Visual · Language · en

Published 2026-04-27

Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 11 · no. 04 · pp. 1

Principal agents

• Subbarao Duggisetty (author → Author)
• Longman Publishers (publisher → Publisher)

Also in the record, outside the Kernel: the abstract, the licence, 4 links, 51 references. Source: Crossref (member 25296), registered 2026-08-26, last deposited 2026-09-20.

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System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

Each element by the standard's name and the Handbook's (in grey), read off the record.

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        "value": "Hybrid Cloud environments combining AWS and on-premises infrastructure presents complex network troubleshooting challenges. Traditional manual diagnostic methods are time-consuming, error-prone, and struggle to correlate logs across distributed systems in real-time. This study addresses the creation of AI-based chatbot application to network fault-finding in hybrid cloud systems, involving the AWS CloudWatch, VPC Flow logs and on- premises infrastructure. The chatbot operates with natural language processing (NLP) to instruct users on the troubleshooting steps on the basis of the historical and live network data. The system increases operational efficiency and reduces the time to resolution by automating root cause analysis, log correlation and remediation suggestions. Using Anthropic Claude (Sonnet), Lex AI chatbot achieved 99.67% accuracy and reduced Mean Time to Resolution (MTTR) from 47.0 minutes to 40.13 minutes improvement. The chatbot enhances user experience in real-time and interactive, 24/7 availability, reduce human error, eliminating the necessity to depend on support teams. The paper shows how AI can streamline troubleshooting and optimize network diagnostics of hybrid networks with complex architectures.",
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