Log analysis is the process of reviewing, interpreting and understand computer-generated records called logs. Logs are generated by a range of programmable technologies, including networking devices, operating systems, applications, and more. A log consists of a series of messages in time-sequence that describe activities going on within a system. Log files may be streamed to a log collector through an active network, or they may be stored in files for later review. Either way, log analysis is the delicate art of reviewing and interpreting these messages to gain insight into the inner workings of the system.
Log analysis functions manipulate data to help users organize and extract information from the logs.
Organizations that effectively monitor their cyber security with log analysis can make their network assets more difficult to attack.
Log analysis is a crucial activity for server administrators who value a proactive approach to IT.
Logs provide visibility into the health and performance of an application and infrastructure stack, enabling developer teams and system administrators to more easily diagnose and rectify issues. Here’s our basic five-step process for managing logs with log analysis software:
Log analysis functions manipulate data to help users organize and extract information from the logs. Here are just a few of the most common methodologies for log analysis.
Normalization – normalization is a data management technique wherein parts of a message are converted to the same format. The process of centralizing and indexing log data should include a normalization step where attributes from log entries across applications are standardized and expressed in the same format.
Pattern Recognition – machine learning applications can now be implemented with log analysis software to compare incoming messages with a pattern book and distinguish between “interesting” and “uninteresting” log messages. Such a system might discard routine log entries, but send an alert when an abnormal entry is detected.
Classification and Tagging – as part of our log analysis, we may want to group together log entries that are the same type. We may want to track all of the errors of a certain type across applications, or we may want to filter the data in different ways.
Correlation Analysis – when an event happens, it is likely to be reflected in logs from several different sources. Correlation analysis is the analytical process of gathering log information from a variety of systems and discovering the log entries from each individual system that connect to the known event.
Organizations who wish to enhance their capabilities in a cyber security must develop capabilities in log analysis that can help them actively identify and respond to cyber threats. Organizations that effectively monitor their cyber security with log analysis can make their network assets more difficult to attack. Cyber security monitoring can also reduce the frequency and severity of cyber attacks, promote earlier response to threats and help organizations meet compliance requirements for cyber security, including:
The first step to an effective cyber security monitoring program is to identify business applications and technical infrastructure where event logging should be enabled. Use this list as a starting point for determining what types of logs your organization should be monitoring:
Event logging for all of these systems and applications can generate a high volume of data, with significant expense and resources required to handle logs effectively. Cyber security experts should determine the most important logs for consistent monitoring and leverage automate or software-based log analysis methods to save time and resources.
The Linux operating system offers several unique features that make it popular among its dedicated user base. In addition to being free to use, thanks to an open source development model with a large and supportive community, Linux automatically generates and saves log files that make it easy for server administrators to monitor important events that take place on the server, in the kernel, or in any of the active services or applications.
Log analysis is a crucial activity for server administrators who value a proactive approach to IT. By tracking and monitoring Linux log files, administrators can keep tabs on server performance, discover errors, detect potential threats to security and privacy issues and even anticipate future problems before they ever occur. Linux keeps four types of logs that system administrators can review and analyze: