News for Admins

Tech News

Canonical Releases Autonomous Clustering with MicroK8s

In the latest release of MicroK8s, Canonical has introduced autonomous high availability (HA) to the lightweight clustering tool. This addition, which is automatically enabled once three or more nodes are clustered, adds resilience for production workloads in both cloud and server deployments.

According to Alex Chalkais, product manager at Canonical, "The autonomous HA MicroK8s delivers a zero-ops experience that is perfect for distributed micro clouds and busy administrators."

What makes the automatic autonomous HA possible is the Dqlite data store. This data store is Canonical's raft-enhanced Sqlite, which is embedded inside Kubernetes. Dqlite dramatically reduces a cluster's memory footprint and automates the maintenance of the data store.

With this new feature in place, MicroK8s will automatically choose the best nodes to provide the data store and, in case of a node failure, the next best node is automatically promoted. An HA MicroK8s cluster will be able to withstand the loss of any node and still be able to meet production requirements with minimal cost and oversight.

This new addition will also go a long way to harden industrial Internet of Things (IoT) applications. Industry 4.0 workloads (such as AI inference and Kafka) are a perfect fit for HA MicroK8s on mission-critical control systems. This increased resilience of HA MicroK8s will be a boon to Kubernetes clusters that exist on edge nodes, such as remote branch offices, retail POS, cell towers, and autonomous automobiles.

For more information, read the official announcement from Canonical (

Buy this article as PDF

Express-Checkout as PDF
Price $2.95
(incl. VAT)

Buy ADMIN Magazine

Get it on Google Play

US / Canada

Get it on Google Play

UK / Australia

Related content

comments powered by Disqus
Subscribe to our ADMIN Newsletters
Subscribe to our Linux Newsletters
Find Linux and Open Source Jobs

Support Our Work

ADMIN content is made possible with support from readers like you. Please consider contributing when you've found an article to be beneficial.

Learn More”>


		<div class=