When users import a data file into Splunk, they’re faced with a dense, confusing block of characters in the data preview. What you really need is to make your data more understandable and more accessible. That’s where data parsing and event breaking come in.
In this brief video tutorial, TechOps Analyst, Hailie Shaw, walks you through an easy way to optimize and configure event breaking— spoiler alert: it boils down to two settings in props.conf.
This function within Splunk can greatly simplify the way you interact with your data. After learning it, you’ll get the insights you need, faster.
When importing data into your Splunk instance, you’ll want to be able to separate it based on events, which enables legibility and ease of interpretation. Because the imported data file isn’t pre-separated, event breaking is an essential skill. The most important part in separating data is the line breaker within the event boundary, which is how Splunk decides how to group and separate certain events.
LINE_BREAKER is how Splunk separates events into different lines. The default = a sequence of new lines, followed by all carriage returns within parentheses.
SHOULD_LINEMERGE is how Splunk merges separate lines into individual events. The default value = true, but should always be set to false as a best practice. If set to true, the value will automatically set to false once Splunk is supplied with your new regex, which provides a specific guide for breaking up new lines and preventing them from merging.
When you import the data file, the term “<event>” appears several times intermittently within the block of data, which is listed as one large event. By pasting the original block of data into regex101.com, users can identify the <event>s that should ideally begin new lines. Then enter the regex resulting from this step into Splunk in props.conf, which will populate the desired fields.
By selecting regex as the event-breaking policy and entering the pattern from regex101.com, the data preview will display your data separated into events (each beginning with “<event>”). The regex in props.conf defines both terms listed above. This data preview can now be saved as a new sourcetype.
Learning event breaking can help make your data more organized and legible for members of your team. Kinney Group’s Expertise on Demand service offers a wealth of Splunk tips and knowledge, tailored by analysts like Hailie to your team’s specific needs. Check out the blog for additional tutorials from our engineers. To learn more about Expertise on Demand, fill out the form below!