Last month, we announced Logz.io Security Analytics — a security app built on top of the ELK Stack, offering out-of-the-box security features such as threat intelligence, correlation, and premade integrations and dashboards. In this article, I’d like to show an example of using both the ELK Stack and Logz.io Security Analytics to secure an AWS environment.

We recently had a presentation at Activate 2018 about entity extraction in the context of a product search. For example: how to tell, when the user typed in Activate 2018, that the intent was to run conference:Activate AND date:201

Servers take a lot of requests daily, we know that…We also know that the server responds instantly. But who makes the request? What do they want, and what exactly are they looking for? Where do these visitors come from? How often they are making a request: once a month, once a day, almost every minute? Well, answers to these, and potentially a lot more questions, can be found in a single place - the server log file.

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!

One of the most important aspects of developing an efficient system is to have clean, helpful logs that will help you understand what errors are being triggered, and what information is being processed. When you are first creating an application, you might not know what logging framework will be most suitable for your future needs, or you could simply want your system to remain agnostic regarding the logging implementation to be used.