The latest News and Information on Containers, Kubernetes, Docker and related technologies.
With massive adoption of Kubernetes at enterprises worldwide, we are seeing Kubernetes going to new extremes. On the one hand, Kubernetes is being adopted for workloads at the edge and delivering value beyond the data center. On the other hand, Kubernetes is being used to drive Machine Learning (ML) and high-quality, high-speed data analysis capabilities.
More and more employers are looking for people experienced in building and running Kubernetes-based systems, so it’s a great time to start learning how to take advantage of the new technology. Elasticsearch consists of multiple nodes working together, and Kubernetes can automate the process of creating these nodes and taking care of the infrastructure for us, so running ELK on Kubernetes can be a good options in many scenarios.
Kubernetes monitoring can be complex. To do it successfully requires several components to be monitored simultaneously. First, it’s important to understand what those components are, which metrics should be monitored and what tools are available to do so. In this post, we’ll take a close look at everything you need to know to get started with monitoring your Kubernetes-based system.
I joined Civo just over a year ago (straight out of a web development bootcamp) and had to quickly become familiar with concepts of Kubernetes and modern cloud-native software development as we prepared to launch our #KUBE100 beta. So, I, along with the rest of the team, thought about how we could help new users learn the basics of Kubernetes in a simple, practical, and fun way. This is how KubeQuest was born.
Kubernetes namespaces enable you to organize cluster objects, such as applications, devices and variables. Once you define namespaces, you can use this classification to filter, group and manage objects. You can use the same namespaces in duplicated environments and apply policies to specific clusters segments. Kubernetes namespaces are also important for defining roles and ensuring proper access configuration. If you're monitoring Kubernetes, you should try out MetricFire.
Trying to improve the reliability of your Kubernetes deployment? Start with these 5 chaos experiments. Kubernetes 1.20 is scheduled to be released next week, and this version contains a number of amazing enhancements including graceful node shutdown, more visibility into resource requests, and snapshotting volumes. But the change generating the most buzz is the deprecation of Docker as a container runtime.
Cloud-native is the ultimate buzzword lately. So, is “cloud-native storage” just an attempt to grab on to this concept, hoping for a little boost? Actually, there is something more to it, and I’ll unpack that here. The premise of cloud-native storage is simple: its native habitat is a Kubernetes cluster. When we design with the assumption that a technology will exist in Kubernetes, we get to look around and see what functionalities already exist in that system.
