Skip to main content
  1. Blog
  2. Article

Canonical
on 28 July 2017

The Canonical Distribution of Kubernetes: Development Summary #4


This blog was originally posted by Tim Van Steenburgh

July 21st concluded our most recent development sprint on the Canonical Distribution of Kubernetes (CDK). Here’s a look at what we did.

Fixes and Improvements

Check out the full list on GitHub. Here are some notables:

  • Made load balancer port configurable
  • Changed default --service-cluster-ip-range to a /16 CIDR to allow more NodePort IP addresses
  • Fixed etcd snapshot action
  • Increased default worker node constraints to 4 cpu, 4GB RAM

Testing

  • Added a test to ensure dashboard is operational after deploy
  • Added a test for the built-in microbot example
  • Added a Jenkins job to test master charms with stable snaps. When this is green it means we can release whatever new fixes/features we have queued up in the charms, giving us the confidence to do more frequent releases.

Features

  • Calico spike. We want to provide a CDK + Calico deployment option that works on any cloud, just like our CDK + Flannel option. We’ve decided to go with a Calico-on-Flannel (Canal) approach initially. Canal combines the network policy enforcement of Calico with the ease-of-deployment of Flannel. Work begins in the current sprint!
  • RBAC spike. We mapped out the work necessary for enabling RBAC via charm config. Work begins in the current sprint!
  • Updated the canonical-kubernetes-elastic bundle. This bundle has been added to our Jenkins build process and updated with the latest 1.7 charms.

If you’d like to follow along more closely with CDK development, you can do so in the following places:

Until next time!

Related posts


Benjamin Ryzman
9 June 2026

What is RDMA over Converged Ethernet (RoCE)?

AI Networking

Previous articles walked through RDMA (Remote Direct Memory Access) as a programming model and InfiniBand as the fabric that was built around it. Both led to the same conclusion, even if it was never stated outright: moving data, not compute, becomes the bottleneck once systems scale. So what happens when you want RDMA, but you’re ...


Freyja Cooper
5 June 2026

Beyond tokens per watt – using Ubuntu 26.04 LTS for AI

AI Article

Tokens per watt (TpW) – the measure of useful AI work produced per watt of energy consumed – is the metric at top of mind for CEOs, heads of AI, and infrastructure teams alike. With the tremendous cost of GPU clusters, extracting as much value as possible from the expense is critical. But in the ...


Gabriel Aguiar Noury
4 June 2026

A look into Ubuntu Core 26: Deploying AI models on Renesas RZ/V series for production

Internet of Things Article

Welcome to this blog series which explores innovative uses of Ubuntu Core. Throughout this series, Canonical’s Engineers will show what you can build with our releases, highlighting the features and tools available to you. In this blog, Asa Mirzaieva, engineer from the Silicon Alliances team, will show you how to deploy optimised AI model ...