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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24205
Article Published : 9239
Total Authors : 24597
Total Reviewer : 847
Total Countries : 165
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| Paper Title: | An Intelligent DevOps Observability Platform with Automated Self-Healing Mechanisms for Cloud Infrastructure |
| Authors Name: | Dr.K.Anitha , Roshini P , Harini K , Pooja Sri M , Preethi R |
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IJRTI_211072
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| Published Paper Id: | IJRTI2604247 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | The purpose of this work is to improve reliability and performance in modern cloud and DevOps environments through intelligent monitoring and automated recovery. Traditional monitoring systems are reactive and detect issues only after failures occur, resulting in downtime and operational losses. As system complexity increases, manual monitoring becomes inefficient and time-consuming. The proposed AI-Driven DevOps Observability & Self-Healing Web Platform continuously collects logs and performance metrics in real time. Machine learning algorithms analyse system behaviour to detect anomalies and predict potential failures before they impact users. Upon identifying abnormal conditions, the system automatically triggers corrective actions such as service restart or resource scaling. A centralised web dashboard provides real-time visualisation of system health and alerts. The platform reduces manual intervention and enhances system uptime. The developed prototype demonstrates improved stability and proactive incident management in a simulated DevOps environment. |
| Keywords: | DevOps, Observability, Anomaly Detection, Self-Healing Systems, Machine Learning |
| Cite Article: | "An Intelligent DevOps Observability Platform with Automated Self-Healing Mechanisms for Cloud Infrastructure", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b791-b796, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604247.pdf |
| Downloads: | 000205514 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604247
Registration ID:211072
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b791-b796 Country: Tiruvannamalai, Tamil Nadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604247 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604247 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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