Operations | Monitoring | ITSM | DevOps | Cloud

ZenOps and StackState announce a partnership for the distribution in France of StackState solutions for Kubernetes problem detection and resolution, observability of containerized environments and application performance management. ZenOps will be able to offer these solutions to enterprises and the public sector, drawing on its technical expertise in cloud-native approaches and providing first-level support.

In the last years, Kubernetes has grown tremendously and is considered by most companies to be the best platform to run applications today. In simple words, Kubernetes is an open-source container orchestration platform that allows you to run and manage containerized applications at scale. In this article, I will explain how you can run Kubernetes on AWS in 3 different ways. But before getting down the road, let me explain why it does make sense to run Kubernetes on AWS.

In the ever-evolving landscape of cloud computing, Azure stands out as a powerhouse for businesses seeking scalable, reliable, and efficient solutions. One of the fundamental aspects of Azure’s appeal is its vast array of resources catering to diverse needs. Azure offers a rich ecosystem of resources, ranging from virtual machines (VMs) and storage accounts to databases, networking components, and beyond.

Just a few years back, developing AI/ML (Machine Learning) models was a secluded endeavor, primarily undertaken by small teams of developers and data scientists away from public scrutiny. However, with the surge in GenAI/LLMs, open-source models, and ML development tools, there’s been a significant democratization of model creation, with more developers and organizations engaging in ML model development than ever before.

20 years in the making. Ubuntu 24.04 LTS brings together the latest advancements from the Linux ecosystem into a release that is built to empower open source developers and deliver innovation for the next 12 years.

In the context of IT service management, Service Level Agreements (SLAs) have long been the cornerstone for measuring and ensuring the quality of services provided to customers. However, as technology evolves and incidents become more complex, relying solely on SLAs may not be sufficient. This is where Service Level Objectives (SLOs) come into play, offering a more nuanced approach to Incident Response.