On one of our monthly check-in calls, the Director of Infrastructure and Operations at one of our largest customers, was telling me how the one big problem he was still trying to solve is optimizing their OPEX or at least make it more predictable. He cited a popular Content Delivery Network (CDN) that they spend millions with as an example. The company had launched a new service and he spoke about how the CDN cost had quadrupled.

There are more than eight hundred pages of documentation for Pandora FMS. The science – and art, I think – of monitoring is very extensive. The needs of a large company are different from those of a medium or small organization. But even two large companies are not the same and their needs may be totally different.

Our product & dev team has been cranking out so many small, medium and big updates the last ~2 months, we thought we'd do a comprehensive sum up. Grab some coffee ☕️ and strap yourself in: the list is quite long!

The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to observability data. For another, most customers have to lean on a hodgepodge of tools that might blend open source and proprietary, require extensive onboarding as team members have to learn which tools are used for what, and have a steep learning curve in general.

We are pleased to announce the general availability (GA) of Elastic 7.12. This release brings a broad set of new capabilities to our Elastic Enterprise Search, Observability, and Security solutions, which are built into the Elastic Stack — Elasticsearch and Kibana.

We are proud to announce the 1.0 release of the Elastic APM PHP Agent! If you are interested in this work, please try the agent and let us know how it works for you and what features you miss! The best way to give feedback and ask questions is in our discussion forum, or if you find an issue or you would like to submit a pull request, jump to our GitHub repository. The agent is Apache-licensed, and we are more than happy to receive contributions from the community!

We are often asked what’s the difference between Anodot and Datadog. Since both platforms monitor data at scale, using machine learning to detect anomalies and incidents, the differentiation might be unclear. So we’re using the real estate here to quickly clarify what each platform is built for, and why – despite some overlaps in features – these are two fundamentally different creatures.

After we’d fixed Aparna’s network issue, James came to see me at my desk. Masks on, socially distanced and all that, but it was nice to have some face-to-face time. James is cool – that dry British humor and not your classic IT Ops dude. He’s been here forever and mentored me when the CIO, Charlie, hired me as the first SRE here a year or so ago. I lucked out really.

In the 21st century, it’s quite easy to manipulate machines and computers. Our worries are no longer if something is doable, but if something can be perfected. Therefore, we mostly search for new ideas and ways to make our work impeccable. For example, if you’re using a particular software and you realize that the software is excellent, but it could be better in some ways that would allow you to work even faster, you’ll explore the alternatives.

As an IT professional, chances are you’ve come across the phrase Please Do Not Throw Sausage Pizza Away while hearing about protocols, network design, and implementation issues. How about Or Please Do Not Touch Steve’s Pet Alligator? If these ring a bell then you’re on the right track: These are smart memory aids linked to the seven layers of the Open System Interconnection (OSI) model.