Autoscaling the resources and services in your Kubernetes cluster is essential if your system is going to meet variable workloads. You can’t rely on manual scaling to help the cluster handle unexpected load changes. While cluster autoscaling certainly allows for faster and more efficient deployment, the practice also reduces resource waste and helps decrease overall costs.

Cloud deployments and containerization let you provision infrastructure as needed, meaning your applications can grow in scope and complexity. The results can be impressive, but the ability to expand quickly and easily makes it harder to keep track of your system as it develops. In this type of Kubernetes deployment, it’s essential to track your containers to understand what they’re doing.

With the widespread adoption of Kubernetes, the Cloud Native Computing Foundation (CNCF) ecosystem has evolved to include projects that address the challenges of using a container orchestrator system. One such challenge is managing and deploying clusters, which can become complex as organizations scale their Kubernetes requirements. Fortunately, Cluster API (CAPI) provides a solution.

Longhorn version 1.5 has been released, along with the latest patch. This release includes a number of new features and improvements that can benefit users. Here are some of the highlights.

Building, testing and deploying software is a time-consuming process that many organizations aim to minimize by automating repeatable work wherever possible. To do so, many organizations are utilizing a continuous integration, continuous delivery (CI/CD) philosophy in combination with cloud native tools like Kubernetes to develop and deploy software at scale.

Wouldn’t it be great if Rancher could provision and manage not only Kubernetes clusters but also the OS running on the cluster nodes? This is the goal we had in mind when we started working on Elemental. Elemental adds to Rancher the ability to install and manage a minimal OS based on SUSE Linux Enterprise technology, delivered and managed in a fully cloud native way. This simplifies the infrastructure (you only need a container registry) and day 2 operations.

In this post we will explain how to use OpenShift monitoring (alert manager) to monitor NeuVector using NeuVector prometheus-exporter NeuVector has published a Prometheus exporter which we will use in the post.