When we released derived columns last year, we already knew they were a powerful way to manipulate and explore data in Honeycomb, but we didn’t realize just how many different ways folks could use them. We use them all the time to improve our perspective when looking at data as we use Honeycomb internally, so we decided to share. So, in this series, Honeycombers share their favorite derived column use cases and explain how to achieve them.

So, you want to implement run-time security in your Kubernetes cluster? If you are looking for an open-source tool, obviously Sysdig Falco is the way to go :). You can install Falco as a daemonSet, but as we wanted to make things even easier and natively integrated, we have packaged Falco as a Helm chart, the Kubernetes package manager.

We’ve launched a new iteration of Icinga Exchange last autumn and modernized the look and feel as well as improved the overall user experience. Since then we’ve solved a few issues and made some enhancements. Just small things to make it a little better.

If you ever (have to) ask yourself “When is the right time to address security issues?”, you’re already late to the party. Security isn’t that layer that you just add on top of your application before shipping it to production. Security is a mindset, that constant voice inside your head which asks “Is this safe?” each time you code something that pulls data out of storage or changes structures based on a user’s action.

The amount of data being generated today is unprecedented. In fact, more data has been created in the last 2 years, than in the entire history of the human race. With such volume, it’s crucial for companies to be able to harness their data in order to further their business goals. A big part of this is analyzing data and seeing trends, and this is where solutions such as Graphite and Grafana become critical.

Managing alert noise from monitoring systems like SolarWinds can be tricky and failing to order the noise can cause: Alert fatigue, Decreased MTTR, Missed alerts.

What’s surprising to see today is how business operations struggle to get an integrated view of all business metrics. With greater volumes of data being collected, data analysts just can’t keep up with the pace. This state of affairs alone doesn’t hit as hard as the fact that many in data analytics have just come to accept this situation as a norm and simply bear with this daily struggle.

In part one of this two-part series, we discussed why organizations should adopt a SIEM solution to ensure network security. In this second part, we’ll be demystifying the critical capabilities of SIEM tools and show you what to consider when picking a solution.

5 years. It's been an amazing journey to build Keymetrics and PM2 through the last 5 years. I've started to create PM2 when Node.js was at the beginning of its fame, then Keymetrics was built a year after. I would like to say THANK YOU, to all of you, users, customers, teammates, maintainers, contributors for having made these softwares reach this height.

Flask is a Python framework known for its ease of use. It inherits Python’s advantages of extensibility, broad support, and relative simplicity. It’s known as a microframework because it relies on extensions for much of its functionality. Flask avoids constraining the developer to a predetermined database or authentication mechanism, for example, and instead leaves room for choice.