Discover the importance of log normalization

What is log normalization?

Every activity on devices, workstations, servers, databases, and applications across the network is recorded as log data. Log normalization is the process of converting each log data field or entry to a standardized data representation and categorizing it consistently. In log normalization, the given log data is converted into consistent representations and categorizations. This is done to record errors and other important details that might not otherwise be obvious.

Each log data field is transformed into a particular data representation and categorized, and as a result becomes useful for storing dates and times in a single format. To display an example:

127.0.0.1 user-identifier andy [12/Nov/2021:20:25:11-0700] "GET /apache_pb.gif HTTP/1.0" "127.0.0.1" refers to the client's IP address when a server request is made.
"user-identifier" refers to the client's identification protocol.
"andy" refers to the user ID.
"[12/Nov/2021:20:25:11-0700]" refers to the date and time the request was made.
""GET /apache_pb.gif HTTP/1.0"" refers to the client’s request.

When various log formats are utilized, normalizing the data and having a consistent format throughout the server makes analysis and reporting much easier. It is very resource-intensive, especially for complex log entries.

Different log formats

CSV

Information from the comma-separated values (CSV) logs can be used to troubleshoot issues that may occur when dealing with configuration data. The information can be broken down into:

• Summary log
• Detail log
• Error log

CSV files are easy to convert to other file types because they are not hierarchical or object-oriented.

JSON

JavaScript Object Notation (JSON) is a text-based data storage format. It's a structured format that makes analyzing the logs much easier and can be queried for individual fields as well. JSON is an efficient format for log handling because of these added properties.

Syslog

Syslog is designed to be simple, with only three parts to each message:

• Gives a numerical description of the facility and severity
• Contains hostname or IP address of the log source
• Log message content

It is designed to be human-readable rather than easily parsed by machines.

XML

Extensible Markup Language (XML) is a text format derived from the Standard Generalized Markup Language that is simple and flexible. Third-party programs can readily extract data using XML since it provides a technique for standardizing and reliably formatting messages. System log messages are tagged using a defined format when XML logging is enabled.

CEF

Common Event Format (CEF) is a log management format that facilitates interoperability by making it simpler to gather and store log data from various devices and applications. It sends messages in the syslog format. The most extensively used logging format, it is comprised of a CEF header and a CEF extension that include log data in key-value pairs, and is supported by a wide range of vendors and software systems.

What is the difference between normalization and parsing?

In normalization, parsers are used to collect all important information from a raw log file, whereas is the process of breaking down large quantities of log data to make them easier to understand and collect.

Importance of log normalization in log management process

• When logs are normalized, essential attributes are extracted from the logs that are received in various forms and stored in a single data model. This makes event classification and operations quicker.
• When data is normalized, it is much easier to determine which machine learning model will produce good results.
• Logs must be normalized in order to monitor important network activity. Log normalization can differentiate regular network activity from irregular network activity.

Technical workers can swiftly drill down on application-related issues using log data, such as identifying regions of dysfunctional performance with the help of log management tools. However, managing logs is no easy task and has the potential to get complicated. That's where EventLog Analyzer comes into play. It is a powerful log management tool that covers end-to-end log management and can support multiple log formats. With several notable features (application auditing, security analytics, log management, etc), it is the solution to all your log management needs. Check out the free, 30-day trial of EventLog Analyzer to see all the features in action.