A common sentiment among our prospects after they see our demo for the first time is: “That’s it? It can’t be that simple!”. The truth is – yes it can be, and it should be. ML and AI should make IT Ops simpler, and a big part of that is usability. If your ML & AI powered IT Ops tools take months to set up and weeks to learn, and then don’t provide a substantially improved user experience, you’re obviously using the wrong tools.

One of the most frustrating service calls you’ll receive is from a client experiencing a network performance issue. The issue could be caused by any number of different things and typically would require you jumping into your car and driving to the client site. The hours drag on while you manually trace wires and test ports to troubleshoot the issue. The longer it takes you to figure it out, the longer you’re interrupting your client’s business.

I’ve just finished getting through security at O’Hare—what an adventure! There were crowds at the check-in, a long security line (luckily I had TSA pre-check), and what seemed like 500 gates I had to pass to get to my gate at the far end of the terminal. We all understand why there are security checkpoints at the airport. They ensure that only those people who belong at the gate are at the gate, and also that there are no malicious actors on airplanes. But why are there so many gates?

Network monitoring at scale is an age-old problem in IT. In this post, I’ll discuss a brief history of network monitoring tools — including the pain points of legacy technology when it came to monitoring thousands of devices — and share my modern-day solution using Sensu Go and Ansible.

When we started working on our data platform to measure the performance of DNS and CDN providers we knew that we had a lot of valuable data. The challenge was to take full advantage of that data and allow easy integration and detailed analysis. To achieve this, we built a robust API which provides access to our full feature stack.