Developing Automated Self-Healing Scripts to Monitor, Detect, and Resolve Issues in Remote Server Management Environments
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| Format: | Recurso digital |
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2022
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| _version_ | 1866901838679244800 |
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| author | Nagarkar, Sudeep |
| author_facet | Nagarkar, Sudeep |
| contents | <p><strong><span lang="EN-US">In the ever-evolving landscape of IT operations, remote server management has emerged as a cornerstone of modern infrastructure. However, the increased complexity and scale of distributed systems have brought new challenges in maintaining reliability and uptime. This has paved the way for self-healing scripts—automated, intelligent programs designed to detect, diagnose, and resolve system anomalies without human intervention. These scripts leverage real-time monitoring, pattern recognition, and decision logic to address failures ranging from simple service outages to complex configuration drifts. By minimizing the need for manual troubleshooting and accelerating issue resolution, self-healing scripts enhance the resilience of IT ecosystems. They are especially critical in environments that demand continuous availability, such as cloud platforms, edge computing frameworks, and container orchestration systems. This article explores the architecture, components, implementation strategies, and best practices for deploying self-healing scripts in remote server environments. Emphasis is placed on real-world use cases, integration with existing tools like Ansible and Prometheus, and the use of machine learning models to predict and prevent faults. Additionally, this paper discusses potential challenges such as false positives, scalability, and security considerations. The goal is to provide a comprehensive understanding of how self-healing mechanisms can transform reactive maintenance into a proactive, automated, and intelligent operational paradigm.</span></strong></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16751832 |
| institution | Zenodo |
| language | |
| publishDate | 2022 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Developing Automated Self-Healing Scripts to Monitor, Detect, and Resolve Issues in Remote Server Management Environments Nagarkar, Sudeep Self-Healing Scripts, Remote Server Management, Automation, IT Resilience, Fault Tolerance. <p><strong><span lang="EN-US">In the ever-evolving landscape of IT operations, remote server management has emerged as a cornerstone of modern infrastructure. However, the increased complexity and scale of distributed systems have brought new challenges in maintaining reliability and uptime. This has paved the way for self-healing scripts—automated, intelligent programs designed to detect, diagnose, and resolve system anomalies without human intervention. These scripts leverage real-time monitoring, pattern recognition, and decision logic to address failures ranging from simple service outages to complex configuration drifts. By minimizing the need for manual troubleshooting and accelerating issue resolution, self-healing scripts enhance the resilience of IT ecosystems. They are especially critical in environments that demand continuous availability, such as cloud platforms, edge computing frameworks, and container orchestration systems. This article explores the architecture, components, implementation strategies, and best practices for deploying self-healing scripts in remote server environments. Emphasis is placed on real-world use cases, integration with existing tools like Ansible and Prometheus, and the use of machine learning models to predict and prevent faults. Additionally, this paper discusses potential challenges such as false positives, scalability, and security considerations. The goal is to provide a comprehensive understanding of how self-healing mechanisms can transform reactive maintenance into a proactive, automated, and intelligent operational paradigm.</span></strong></p> |
| title | Developing Automated Self-Healing Scripts to Monitor, Detect, and Resolve Issues in Remote Server Management Environments |
| topic | Self-Healing Scripts, Remote Server Management, Automation, IT Resilience, Fault Tolerance. |
| url | https://doi.org/10.5281/zenodo.16751832 |