Log files contain rich and useful management data. With the right software tools and a few navigation tips, you can maximize and implement the information that logs provide.
Log management tools enable you to easily identify trends, security threats and unusual activity, which is beneficial for both short- and long-term data center management.
Log management software is essential to make sense of the information found in log files and track trends for data center maintenance. These programs and functions help generate, transmit, analyze and archive large chunks of data.
Before you start to use log file management software, you should learn the basics of how to access and navigate them. For a Linux-based system, this is done using two native logging tools -- systemd and rsyslog -- but there are other options, too.
Both have their own benefits, including what information they display and how they simplify formatting. One benefit of using Linux is that database file queries are recorded at a granular level, which makes navigation easier.
Systemd lets you see all the possible messages written within the system and helps find journalctl-generated logs. It is also consistent across distributions, so you can use the same commands regardless of what Linux distribution you're using.
Even though systemd is a common logging method, rsyslog offers more features. One main capability is being able to write log messages to a specific database. You can also configure rsyslog logs on one main server for centralized access.
Available log management tools
Beyond the log management tools found in Linux distributions, there are a few software options that you can use for effective log file management. Systemd and rsyslog require you to dig into each individual file to gather information, so they make more sense for batch management. But they do not always provide trends or analysis that is optimized for a good user experience.
Graylog is compatible with Linux and Windows device logging. It also provides centralized configuration management for third-party data collectors, such as Beats, Fluentd and NXLog. Because it is based on a web server, you can monitor a wide variety of log information sources through one interface. You can also easily set configurations to notify you of high-level alerts related to data center activity.
Once you've selected log management tools, you must decide how granular you want to get with functionality.
Log file is Linux-based and provides daily overviews. After filtering out normal event logs, it mails you log file summaries and flags any potential abnormalities. You can have a local Linux user get this digest, but it's better to use an external user account.
Once you've selected log management tools, you must decide how granular you want to get with functionality. For programs such as log file, there are different levels of reporting, from daily digests to paranoid-level updates and workstation-specific trends. With Graylog's web-based interface, you can filter log sources and expand capabilities through the Graylog marketplace.
Implementing best practices
Best practices are essential for effective log management and long-term data center performance. They're also necessary because there is no standardized approach to log file creation, which can cause confusion when going through file data.
You can streamline log file information a few ways depending on what collection methods you use. Systemd-journald produces log file messages in a singular timestamp host service format. But if you run log files for a different operating system, you can look into tools such as Apache Log4j for Java. For legacy system integration, make sure whatever tools you use are compatible with your log aggregation and analysis tools and that they deliver useful log data.
Once you've gotten your software set up, avoid adding unusual data fields on each log. This complicates aggregation and it can make it difficult for you to find similar data across groups of log files. If you want to group data, add a schema within your log management tools to avoid data mix-ups.
Security should also be a part of your best practices. For log files with sensitive information, consider what measures make sense for your organization and what data needs protection. Options for protection include not capturing sensitive data in logs, encryption or scrubbing data after a specified period of time.
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