Introduction Kubernetes solves the problem of orchestrating containerized applications at scale by replacing the manual processes involved in their deployment, operation, and scaling with automation. While this enables us to run containers in production with great resiliency and comparably low operational overhead, the Kubernetes control plane and the container runtime layer have also increased the complexity of the IT infrastructure stack. In order to reliably run Kubernetes in production, it is therefore essential to ensure that any existing monitoring strategy targeted at traditional application deployments is enhanced to provide the visibility required to operate and troubleshoot these additional container layers.
One of the nicer features of Kubernetes is the ability to code and configure autoscale on your running services. Without autoscaling, it's difficult to accommodate deployment scaling and meet SLAs. This article will show you how to autoscale your services on Kubernetes using Horizontal Pod Autoscale.
Ankur Agarwal, Rancher's Head of Product Management, describes new features in Rancher 2.2. Learn how to monitor multiple Kubernetes clusters in this step-by-step tutorial and how our new preview release process works.
Monitoring a Kubernetes cluster allows engineers to observe its resource utilization and take action when something goes wrong. This article explores what you should be monitoring and how to go about it with Rancher, Prometheus, and Grafana.
Rancher 2.2 has reached GA and is available for immediate use. It's packed with features for Day 2 Kubernetes operations, designed to make clusters and their workloads more available and easier to manage. This article describes the main features in 2.2, their benefits, and when to use them.