We recently released uptime monitoring, a pretty big addition to our set of features. Our customers have often requested it, and it was a logical next step for us to add uptime monitoring to our app. In today’s post, we’ll explain how we went from considering uptime monitoring impossible to build, to building it in a week. We’ll break down how seemingly over-engineering can really pay off in the end.

If Netflix was a series, it would be a blockbuster. Each season would be nothing short of dramatic to the chagrin of investors. Want to crunch some numbers? The video streaming service had an $11.5 billion valuation in January 2011. It had about 26 million subscribers at the end of that year. Ten years later, Netflix reported it had about 204 million subscribers and a valuation of over $220 billion. The Los Gatos, CA, giant made a staggering $25 billion in 2020 in annual revenue.

The pandemic made Zoom ubiquitous. Everyone from preschoolers to CEOs use it to meet with others. Much of what we used to do by walking down the aisle, boarding a plane, or entering a classroom can now be handled on a Zoom call. Remote work has given rise to another trend: the fear of missing out (FOMO). At many companies, employees move from one Zoom meeting to another, forcing them to choose between Zoom fatigue and FOMO.

Network anomalies vary in nature. While some of them are easy to understand at first sight, there are anomalies that require investigation before a resolution can be made. The MITRE ATT&CK framework introduced in Kemp Flowmon ADS 11.3 streamlines the analysis process and gives security analyst additional insight by leveraging knowledge of adversaries' techniques explaining network anomalies via the ATT&CK framework point of view.

In modern cloud architecture applications are broken down into independent building blocks usually as microservices. These microservices allow teams to be more agile and deploy faster. Microservices form distributed systems in which communication between them is critical in order to create the unified system. A good practice for such communication is to implement an event-driven architecture.

Severe weather in South Carolina comes with the territory, and for a local communications service provider like HTC, that translates to service outages for the internet, streaming video, phone, and wireless networks it provides to predominantly rural communities. When these events strike, the Emergency Operations Center (EOC) at HTC faces enormous pressure not only to maintain services, but to prioritize customer support efforts and restore services as quickly as possible.

This blog is the second in a four-part series on infrastructure automation for government agencies that are modernizing digital systems while grappling with budget and staffing constraints and the challenges of COVID-19.

When we talk about metrics in software delivery, a lot of developers think of execution metrics — things like throughput, delivery and number of deploys. But in reality, those metrics don’t motivate anyone — at least not without connecting them to a bigger picture. I’ve worked in software for 23 years. I’m a three-time founder and four-time CTO, responsible for leading a 200+ member distributed engineering organization.

In the first article in this series, we explained how to set up your developer environment to begin creating Mattermost plugins. In the second, we examined the structure of server-side and web app plugins and how to deploy them. Now, it’s time to dive deeper into the server side of the application, which is written in Golang.

In a relatively short amount of time, Kubernetes has evolved from an internal container orchestration tool at Google to the most important cloud-native technology across the world. Its rise in popularity has made Kubernetes the preferred way to build new software experiences and modernize existing applications at scale and across clouds. With Kubernetes, companies can host workloads running on a single cloud, as well as workloads across multiple clouds.