使用APPINSIGHT为中小企业提供主动监控

A. Buja
{"title":"使用APPINSIGHT为中小企业提供主动监控","authors":"A. Buja","doi":"10.26483/ijarcs.v13i5.6901","DOIUrl":null,"url":null,"abstract":"Data Security is a worldwide concern mostly for small medium enterprise (SMEs) and frameworks, approaches, methods are constantly evolving that has a connection with cloud computing, information systems, artificial intelligence, blockchain. Many developers, administrators or product teams running blind. Those are not knowing of problems with their application or do not have the information to fix the problems. The things which can go wrong with web and mobile applications or services is unlimited like dependency failures, resources, and crashes. Main argument is an evaluation of benefits by using Cloud as infrastructure and application on proactive monitoring called Azure Application Insights (AppInsight) towards target like web application, web API, PKI etc. The findings, demonstration of the study should reveal and support our main hypothesis that there is direct link between the proactive monitoring and the main factors that affects utilizing the cloud services. To address this need, in this paper, we introduce AppInsight, the best practice and a model of proactive approach to monitor different targets using Microsoft technology on Azure Cloud services. AppInsight – a model of proactive monitoring includes several functionalities: (1) identifying availability, (2) failures dependencies, (3) performance and (4) using telemetry data generates ad-hoc solution to fix potential failure of web application, web API etc. AppInsight a feature of Azure Monitor used to monitor live applications. AppInsight will automatically detect performance anomalies, and includes powerful analytics tools to help you diagnose issues. You will get a range of telemetry data of analytics of your target which is monitored by AppInsight. To evaluate this tool, we conduct an empirical evaluation by comparing data from actual live monitoring of Y target. Demo Video: https://www.youtube.com/watch?v=q7R8-c0ge7M","PeriodicalId":287911,"journal":{"name":"International Journal of Advanced Research in Computer Science","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PROACTIVE MONITORING FOR SMEs USING APPINSIGHT\",\"authors\":\"A. Buja\",\"doi\":\"10.26483/ijarcs.v13i5.6901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data Security is a worldwide concern mostly for small medium enterprise (SMEs) and frameworks, approaches, methods are constantly evolving that has a connection with cloud computing, information systems, artificial intelligence, blockchain. Many developers, administrators or product teams running blind. Those are not knowing of problems with their application or do not have the information to fix the problems. The things which can go wrong with web and mobile applications or services is unlimited like dependency failures, resources, and crashes. Main argument is an evaluation of benefits by using Cloud as infrastructure and application on proactive monitoring called Azure Application Insights (AppInsight) towards target like web application, web API, PKI etc. The findings, demonstration of the study should reveal and support our main hypothesis that there is direct link between the proactive monitoring and the main factors that affects utilizing the cloud services. To address this need, in this paper, we introduce AppInsight, the best practice and a model of proactive approach to monitor different targets using Microsoft technology on Azure Cloud services. AppInsight – a model of proactive monitoring includes several functionalities: (1) identifying availability, (2) failures dependencies, (3) performance and (4) using telemetry data generates ad-hoc solution to fix potential failure of web application, web API etc. AppInsight a feature of Azure Monitor used to monitor live applications. AppInsight will automatically detect performance anomalies, and includes powerful analytics tools to help you diagnose issues. You will get a range of telemetry data of analytics of your target which is monitored by AppInsight. To evaluate this tool, we conduct an empirical evaluation by comparing data from actual live monitoring of Y target. Demo Video: https://www.youtube.com/watch?v=q7R8-c0ge7M\",\"PeriodicalId\":287911,\"journal\":{\"name\":\"International Journal of Advanced Research in Computer Science\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advanced Research in Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26483/ijarcs.v13i5.6901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Research in Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26483/ijarcs.v13i5.6901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

数据安全是一个全球关注的问题,主要是中小型企业(sme),与云计算、信息系统、人工智能、区块链相关的框架、方法和方法不断发展。许多开发人员、管理员或产品团队盲目行事。这些人不知道他们的应用程序有问题,或者没有解决问题的信息。web和移动应用程序或服务可能出现的问题是无限的,比如依赖失败、资源和崩溃。主要论点是对使用云作为基础设施和应用程序的好处进行评估,称为Azure应用程序洞察(AppInsight),针对web应用程序,web API, PKI等目标进行主动监控。研究的结果和论证应该揭示并支持我们的主要假设,即主动监测与影响云服务利用的主要因素之间存在直接联系。为了满足这一需求,在本文中,我们介绍了AppInsight,这是一种使用Microsoft技术在Azure云服务上监控不同目标的最佳实践和主动方法模型。AppInsight——一个主动监控模型,包括以下几个功能:(1)识别可用性;(2)故障依赖;(3)性能;(4)使用遥测数据生成临时解决方案来修复web应用程序、web API等的潜在故障。AppInsight: Azure Monitor的一个功能,用于监控实时应用程序。AppInsight将自动检测性能异常,并包括强大的分析工具,以帮助您诊断问题。你会得到一系列的遥测数据,分析你的目标,这是由AppInsight监控。为了对该工具进行评价,我们通过对比Y靶的实际实时监测数据进行了实证评价。演示视频:https://www.youtube.com/watch?v=q7R8-c0ge7M
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PROACTIVE MONITORING FOR SMEs USING APPINSIGHT
Data Security is a worldwide concern mostly for small medium enterprise (SMEs) and frameworks, approaches, methods are constantly evolving that has a connection with cloud computing, information systems, artificial intelligence, blockchain. Many developers, administrators or product teams running blind. Those are not knowing of problems with their application or do not have the information to fix the problems. The things which can go wrong with web and mobile applications or services is unlimited like dependency failures, resources, and crashes. Main argument is an evaluation of benefits by using Cloud as infrastructure and application on proactive monitoring called Azure Application Insights (AppInsight) towards target like web application, web API, PKI etc. The findings, demonstration of the study should reveal and support our main hypothesis that there is direct link between the proactive monitoring and the main factors that affects utilizing the cloud services. To address this need, in this paper, we introduce AppInsight, the best practice and a model of proactive approach to monitor different targets using Microsoft technology on Azure Cloud services. AppInsight – a model of proactive monitoring includes several functionalities: (1) identifying availability, (2) failures dependencies, (3) performance and (4) using telemetry data generates ad-hoc solution to fix potential failure of web application, web API etc. AppInsight a feature of Azure Monitor used to monitor live applications. AppInsight will automatically detect performance anomalies, and includes powerful analytics tools to help you diagnose issues. You will get a range of telemetry data of analytics of your target which is monitored by AppInsight. To evaluate this tool, we conduct an empirical evaluation by comparing data from actual live monitoring of Y target. Demo Video: https://www.youtube.com/watch?v=q7R8-c0ge7M
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信