The Bleemeo Community Edition is the Open Source and self hosted version of the Bleemeo monitoring solution. It is composed of three main components: And some third party components: In this article, we will show you how to install and configure these components to have a fully working monitoring infrastructure.

Mobile learning consists of learning on the go, via your smartphone or tablet. In a business setting, mobile learning offers the possibility for employees to follow their training wherever they are, with online courses and other content being accessible at all times. This learning method is available on many learning management system (LMS) platforms but, as we will see later, it is necessary to be vigilant in the choice of the latter because mobile learning comes with some technical constraints.

Artificial Intelligence (AI) - or more specifically Machine Learning (ML) - and automation were big topics for many of our customers in 2022. Common reasons for the interest in AI and automation were to: increase efficiency, reduce manual processing, minimise human error and - especially for the use of ML - identify ‘unknown unknowns’.

Open-source software is driving some of the most exciting innovations today. According to The Linux Foundation, open-source constitutes about 70 to 90% of all modern software solutions. But it isn’t all fun and games: open-source software is free, which brings about operational inefficiencies due to a lack of financial support for their developers. Platforms like Switch and SubStack started incentivizing paid subscription models to solve this problem.

As the Internet of Things (IoT) continues to grow, transforming the way we live and work, it should be expected that there will be various security challenges to battle. This means that as a business owner, you should be ready to secure your devices and connections. Statista reports that there are currently 15.14 billion IoT-connected devices worldwide.

Stack overflows have notoriously plagued the development processes. They often can go undetected and can present themselves in obscure ways. We have implemented software mechanisms to protect against them, but these have limitations and still don’t protect against all conditions. With the maturity of the ARM architecture, wouldn’t it be better to have a fool-proof mechanism for detecting overflows?