Monitoring Data Center Site Infrastructure Using AIOPS Architecture

Eduvest Pub Date : 2023-01-30 DOI:10.59188/eduvest.v3i1.732
Ajay Reddy Yeruva
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Abstract

Artificial intelligence for IT operations, or AIOps, has expanded significantly in current years. But the bulk of AIOps apps is used in the IT industry. In contrast, the data center infrastructure area has limited applications. A work design or technique could not be easily copied from one or more domains due to drastically differing business circumstances & data properties, as demonstrated by numerous real-world examples. This article presents an AIOps framework for the domain of monitoring data center infrastructure. Core modules, including technological architectures, machine learning algorithm, large data, & business applications, are provided, & the specifics are built into practices. Instead of covering every aspect of the architecture job, this article concentrates on the technical aspect. In other words, this article will not examine NFRs (non-functional requirements), which include performance, availability, manageability, & security
使用AIOPS架构监控数据中心站点基础设施
用于IT运营的人工智能(AIOps)近年来得到了显著扩展。但是大部分AIOps应用程序都是在IT行业使用的。相比之下,数据中心基础设施领域的应用有限。由于商业环境的巨大差异,工作设计或技术不能轻易地从一个或多个领域复制。数据属性,如许多实际示例所示。本文介绍了用于监视数据中心基础设施领域的AIOps框架。核心模块,包括技术架构、机器学习算法、大数据等;提供商业应用程序&具体细节已纳入实践。本文不涉及架构工作的每个方面,而是集中于技术方面。换句话说,本文将不检查nfr(非功能需求),其中包括性能、可用性、可管理性、&安全
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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