Many purchased and proprietary applications log activities and messages to flat files. These files can contain an overwhelming number of messages. Mining important logged messages from the flat file is necessary to identify specific messages about events of interest that are logged. In Unix / Linux environments, messages logged to flat files can be seen in a continuous stream as they are appended by executing a tail-f command. This is somewhat ineffective as a continuous stream does not isolate messages of interest. Windows users are even more handicapped. Some single purpose log monitoring tools exist, but their utility to analyze and trigger actions based on monitoring messages is limited.
So, how can you effectively and efficiently cull the mass of messages in the file to find the message of interest and then execute an automated action based on the situation or event noted?
Examples where applications write messages of interest to flat files and where an automated action can improve performance and efficiency include:
Application – Symantec Antivirus
Event – Security risk found
Action – Clean by deletion and / or notify support desk
Application – UNIX Server
Event – File system on disk is corrupt and unusable
Action – Run “fsck” utility on volume
Using NerveCenter’s LogAgent utility, flat file logs can be monitored for messages containing keywords which can then be relayed to NerveCenter’s syslog utility. The NerveCenter syslog utility converts all inbound entries to Traps which are processed by NerveCenter. Once in NerveCenter, desired, or necessary actions can be triggered in NerveCenter models.
To learn more about the NerveCenter solution, follow this link:
To watch our NerveCenter Model Club video demonstrating Flat File Monitoring with NerveCenter LogAgent, click here