Blog | Product Updates | 2 minutes read

Introducing Custom Parsing on LogDNA: A dead simple way to define your own log parsing rules

Introducing Custom Parsing on LogDNA: A dead simple way to define your own log parsing rules

We’re excited to announce that LogDNA’s built-in log parser offers custom parsing, now available in beta. This means you can now use our step-by-step wizard to wrangle non-standard log formats and run custom transformations on your logs, allowing you to easily search and graph log lines that were previously off limits. The best part is, it’s a simple three step process: search, extract, validate… done!

For most cases, automatic parsing may be all you need, especially if your logs are in common formats. However, you might want to add extra fields to your logs, deviate from the common syslog RFCs, or send IoT logs in non-standard formats. Now, regardless of how esoteric or specific your use-case is, you can customize LogDNA to work for you!

You can learn more in our log parsing docs, but for those of you that are visual learners, we’ve highlighted the process of creating a custom parsing template in three short gifs. We’ll also be hosting a live webinar tomorrow, November 14, 2018, where we’ll dig into the nitty gritty of custom parsing.

Custom Parsing in a Nutshell
You can find the “Parsing” section under your Settings sandwiched between “Integrations” and “Team”.

Step 1: Select a sample log line as your starting point.


Step 2: Pick a delimiter and field to capture.

Last step: Validate the output and activate your new parsing template!

We’d love to hear your feedback! Feel free to contact us directly or let us know what you think on Twitter. If you’d like to learn more about how custom parsing can be used for your specific use-case, feel free to schedule time with our customer success team.

We want to thank the customers that requested this feature for guiding us and providing early feedback and also give a huge shout-out to the team for getting this out the door: Jacob, Kristina, Mike, Nagi, and Qijing!

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