System Analysis and Error Detection: An approach towards server monitoring using Natural Language Processing

Abstract

Advanced technologies bring advancement and benefits to the majority of fields. Different applications have been developed in areas related to machine learning and data mining. But our server subsystems still require more of human intervention to analyze things. Hence an approach has been discussed to make the primitive servers as a smart server with the help of data analysis and machine learning techniques. There are various tools which can monitor a number of systems with automation, but automation cannot give answers like with what kind of errors my system got impacted more? How my system performs under load and without load? All these answers can be achieved through system analysis. Hence, the term “analysis” can be described as the process of studying complex structures to get meaningful results in order to build system that are smart and robust. In the era of data explosion, where a system is much complex now, a tool would be needed with which can compute such queries Although for analysis, various tools and techniques exists but their schema could not handle the big data or large number of data and automation scripts cannot provide optimized results hence there is a huge need to have modern techniques for better optimization. The automated results are not reliable enough as it still requires more of expert knowledge to analyze it further. In this paper, the focus with term “Analysis” is in point of view to check the behavior of the system parameter i.e., CPU utilization through visualization in real time and automatic error parsing and detection of error is taken under consideration so that a domain expert is no longer required to solve our problem instead the server admin person can analyze own.