Written by John Stimmel, Principal Cloud Specialist Account Executive, LogicMonitor It’s common knowledge that Kubernetes (commonly referred to as “K8”s) container management and orchestration provide business value by enabling cloud-native agility and superior customer experiences. By their nature, the speed and agility of Kubernetes platforms come with complexity.

As a recovering practitioner, one of the things I was always less than thrilled to do was patching. I dreaded having to run updates, ensure everything was configured correctly, and finding windows of time to reboot without knocking an application offline. Just like your cloud workloads — everything changes when it has to be done at scale. Kubernetes has always been built around the DevOps concepts of rapid development, delivery, and iteration.

A recent Kubernetes Adoption Report showed that 68% of surveyed IT professionals adopted containers more during the pandemic. Among their goals were accelerating deployment cycles, increasing automation, reducing IT costs, and developing and testing artificial intelligence (AI) applications. But, what role does container technology play in this? This guide shares what containers are, how container orchestration works, and more.

In the ever-evolving landscape of software development, testing plays a crucial role in ensuring the quality, reliability, and performance of applications. As technology continues to advance, the future of testing is deeply intertwined with automation, offering immense potential for improving efficiency, speed, and accuracy in the testing process.

This article provides a basic overview of the structure, mechanisms, and benefits of Kubernetes for beginners.

As complex as Kubernetes is, much of it can be distilled to one simple question: how do we keep containers available for as long as possible? All of the various utilities, features, platform integrations, and observability tools surrounding Kubernetes tend to serve this one goal. Unfortunately, this also means there’s a lot of complexity and confusion surrounding this topic. After all, most people would agree that availability is important, but how exactly do you go about achieving it?

The motivation behind automating Kubernetes deployments stems from the need to accelerate development cycles, minimize manual errors, and achieve consistent deployments. In today’s application development where container orchestration is a crucial aspect, automating the Kubernetes deployment is inevitable. Despite challenges such as maintaining security and handling complex dependencies, automation remains a powerful solution.

Civo is excited to announce more information on our high-performance cloud GPUs, tailored for machine learning, scientific computing, and generative AI. It’s designed to streamline your project from start to finish, all with just a few clicks. But, what really sets our service apart?

Kubernetes 1.30 brings a plethora of enhancements, including a blend of 58 new and improved features. From these, several are graduating to stable, including the highly anticipated Container Resource Based Pod Autoscaling, which refines the capabilities of the Horizontal Pod Autoscaler by focusing on individual container metrics. New alpha features are also making their debut, promising to revolutionize how resources are managed and allocated within clusters.

One significant challenge that every dynamic, fast-paced business in the cloud faces is efficiently managing their clusters’ workloads while minimizing unnecessary expenses. But it’s not just overages that these businesses must worry about. Especially common is the underutilization of resources, which can lead to unnecessary costs and inefficiencies.