Event Log Analyzer

Site: www.eventloganalyzer.org Keyword: Event log analyzer Software: Lepide Event Log Manager Event log analyzer- A step ahead event mining techniques Event logs play a very important part in today’s IT systems, where several applications, operating systems and network devices run on local or remotes systems. Event logging and monitoring has become a widespread practice with IT organizations for they provide resourceful information about the state of a system or a network. Event monitoring in real time environment has been a topic of research for many years and different tools and techniques have been developed to accomplish the task in an appropriate manner. Technologies such as data mining and data clustering have been most prominent in the area of event log analysis. However, both these technologies have suffered from some or the other shortcoming because of which the focus have shifted towards better and more platform independent event log analyzers. Since event monitoring provides real time information on systems that helps in conducting event analysis, different event processing techniques are being used. Event correlation is one such prominent technique in event log analysis. In event correlation a set of events that takes place in a given time interval is interpreted and then processed for the task of fault management in a domain or a network. However, the tools used for event correlation are mostly platform dependent and difficult to deploy in small or medium sized businesses with limited computing resources. Event monitoring through most of the event correlation tools takes place with the help of algorithms like the APRIORI algorithm which are sometimes inefficient in correlating longer event patterns. The need of event log analyzers have also emerged due to the inefficiencies of data mining techniques, which identify event logs on the basis of certain patterns. The frequent event type patterns monitored during event mining help in the analysis of potential risks or errors, thus aiding network management tasks. However, the existing data mining techniques have several shortcomings. First being that only frequent event patterns are monitored and the infrequent patterns are avoided. But, infrequent event log patterns are often the source of anomalous or unexpected behavior in the system or the network, because of which leaving those can prove to be detrimental in event analysis. Efficient data clustering technology are seldom used to tackle this problem of data mining the events. Due to his very reason, the importance of developing event log analyzers which are capable of correlating monitored event logs and event streams without ignoring the infrequent logs has increased. Platform independent and easy to deploy Event log analyzer such as Lepide Event Log Manager proves to be the optimum solution for effective real time event analysis. Event log analyzers are considered better than the data mining techniques as these are platform independent and suitable for monitoring smaller networks. With event log analyzer, it is possible to monitor the event logs of an entire network without the need of slicing the event patterns as in data clustering methods. It is possible to create and

maintain a database to record the event logs of all the systems within a network. Upon analysis of the events collected in the database, faults or network issues can be detected either by identifying set patterns of events which do not occur in any pattern. Events can be searched for and filtered out on the basis of event IDs, event type, event source, etc to obtain the network status, therefore aiding in fault management and analysis. Summary: Data mining techniques and data clustering technology used to analyze event logs often suffer from shortcomings. For this reason, event log analyzer developed as a standalone event monitoring tool helps in correlating and processing the logs with accuracy. Author Bio: The author of this article is the head of department of computer engineering and has many years of research experience on data mining technologies. In this article, he has discussed about the insufficiencies of event log processing technologies and how an independent platform like the event log analyzer can help resolve the problems.