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Introduction to KUDO: Automate Day-2 Operations (I)

Operators are one of the most powerful tools when you are working with Kubernetes, especially when you are in a scenario where Stateful conditions are required like ordered and automated rolling updates, or graceful deployment/deletion and scaling/termination. The problem, however, is writing and building Operators require deep knowledge of Kubernetes internal and a lot lines of code.

Using Kubebuilder requires writing thousands lines of controller code in GO and existing implementations often don't cover the entire lifecycle. You can also go for Operator Framework in order to use Ansible or Helm charts but both have some limitations.

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Cloud-Native Benchmarking With Kubestone

Intro

Organizations are increasingly looking to containers and distributed applications to provide the agility and scalability needed to satisfy their clients. While doing so, modern enterprises also need the ability to benchmark their application and be aware of certain metrics in relation to their infrastructure.

In this post, I am introducing you to a cloud-native bench-marking tool known as Kubestone. This tool is meant to assist your development teams with getting performance metrics from your Kubernetes clusters.

How Does Kubestone Work?

At it's core, Kubestone is implemented as a Kubernetes Operator in Go language with the help of Kubebuilder. You can find more info on the Operator Framework via this blog post.
Kubestone leverages Open Source benchmarks to measure Core Kubernetes and Application performance. As benchmarks are executed in Kubernetes, they must be containerized to work on the cluster. A certified set of benchmark containers is provided via xridge's DockerHub space. Here is a list of currently supported benchmarks: