The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
Each year, more than 296 million packages are shipped around the world via DHL and their premium service, Time Definite International. And at DHL Express Switzerland, a local unit of the international logistics and shipping company, the IT team provides solutions for tracking customs clearance progress, analytics, mobile and optical character recognition (OCR) scanning, and warehouse management on every package that moves through Switzerland.
In the fast-evolving landscape of technology and software applications, ensuring optimal performance and reliability has become paramount. This article delves into two powerful tools that facilitate effective monitoring and management of digital systems: Prometheus and AppDynamics. With a focus on different aspects of application performance, these tools offer distinct advantages to businesses aiming to elevate their user experiences and operational efficiency.
In this post, we'll dive into what CrashLoopBackOff actually is and explore the quickest way to fix it. Fasten your seat belts and get ready to ride. Everyone working with Kubernetes will sooner or later see the infamous CrashLoopBackOff in their clusters. No matter how basic or advanced your deployments are and whether you have a tiny dev cluster or an enterprise multi-cloud cluster, it will happen anyway. So, let’s dive into what CrashLoopBackOff actually is and the quickest way to fix it.
Teréga, a gas storage and transportation company in southwest France, manages a network of 5,000 kilometers of natural gas pipelines. The company’s mission is to accelerate the energy transition currently taking place, both at a territorial and a European level. It aims to extend a culture of responsibility to all its business and day-to-day activities.
Artificial intelligence (AI) has emerged as a transformative force, empowering businesses and software engineers to scale and push the boundaries of what was once thought impossible. However as AI is accepted in more professional spaces, the complexity of managing AI systems seems to grow. Monitoring AI usage has become a critical practice for organizations to ensure optimal performance, resource efficiency, and provide a seamless user experience.
We as a company build monitoring software. And we have committed to diversity. It is just logical and consequent for us to apply this principle not only to the people who do the work, but also to the work itself. To the monitoring software we build. Especially to Icinga 2 which, in a perfectly monitored environment, runs on every single machine. I.e. on every single OS powering all those machines.