Operations | Monitoring | ITSM | DevOps | Cloud

We created Focalboard to be a self-hosted, open source alternative to tools like Trello, Notion, and Asana. One of the most common use cases for each of these tools is managing projects. When we looked for a project management solution to coordinate the development of Focalboard itself, the choice was clear: We would use Focalboard to build Focalboard (just like Mattermost uses Mattermost to build Mattermost).

In my introduction to this blog series, I talked about why Unified Endpoint Management (UEM) is more relevant than ever before. While reading this blog put your own experiences into perspective with how you and your company were forced to work during COVID-19.

Modern applications enable enterprises to scale faster with better efficiency and resilience. The main advantage of a multi-cloud/hybrid cloud infrastructure is in its highly distributed architecture that offers proximity – bringing end users closer to the service provider.

The largest remote working experiment the world has ever faced is entering a new phase as the era of hybrid work begins. For IT and DevOps teams on the frontline, this is a time of enormous pressure. Along with its many benefits, hybrid working can also bring considerable disruption. Enabling and supporting the hybrid model is the next big challenge facing organizations around the globe. We wanted to find out what this new reality means for these teams.

But it’s better than nothing… Most of the industry is racing to adopt better observability practices, and they’re discovering lots of power in being able to see and measure what their systems are doing. High data availability is better than none, so for the time being, what we get is often impressive. There’s a qualitative difference between observability and data availability, and this post aims to highlight it and orient how we structure our telemetry.

A modified version of this blog post appeared in the June 2021 issue of Signal magazine. Decisions that need to be made in an instant require answers in real time, but existing big data systems are unable to return queries quickly enough for real-time analytics. And with growing data being queried by more connected users than ever before, it’s getting increasingly challenging to maintain fast reaction times.