Skip to main content

Your submission was sent successfully! Close

Thank you for signing up for our newsletter!
In these regular emails you will find the latest updates from Canonical and upcoming events where you can meet our team.Close

Thank you for contacting our team. We will be in touch shortly.Close

  1. Blog
  2. Article

Canonical
on 14 November 2019

Canonical enhances Kubernetes reliability for edge, IoT and multi-cloud


14 November 2019: Canonical today announced high-availability clustering in MicroK8s, the workstation and appliance Kubernetes, and enterprise SQL database integration for its multi-cloud Charmed Kubernetes.

“The rapid rise of enterprise and edge Kubernetes creates a challenge for corporate IT, with thousands of edge nodes running Kubernetes, and hundreds of cloud Kubernetes clusters,” said Stephan Fabel, Director of Product at Canonical. “The next generation of Canonical’s Kubernetes offerings reduce the number of moving parts, and embrace standard corporate SQL databases for Kubernetes data stores, to address the operational consequences of Kubernetes cluster sprawl.”

Canonical’s MicroK8s gained popularity as an IoT, appliance and developer workstation Kubernetes, with a very small footprint suitable for edge devices and laptops. MicroK8s 1.16 added clustering, enabling rapid deployment of highly standardised small K8s clusters. The next step is to ensure high availability of these clusters, using Canonical’s Dqlite distributed SQL engine. Dqlite removes process overhead by embedding the database inside Kubernetes itself, and reduces the memory footprint of the cluster which is important for IoT.

RAFT and SQLite are well-understood best practices for distributed and embedded systems. Using Dqlite as the Kubernetes datastore simplifies the deployment of a resilient K8s cluster. Telco and retail edge applications can now achieve high reliability at very low cost on x86 or ARM commodity appliances such as clusters of Intel NUCs or Raspberry Pi boards.

The move to SQL as a data store is mirrored in Canonical’s multi-cloud Charmed Kubernetes, embracing corporate databases such as Oracle, SQL Server, MySQL and Postgres, and public cloud SQL offerings like AWS Relational Database Service (RDS). Administrators will be able to use these familiar SQL databases for Kubernetes cluster data instead of etcd.

“We retain etcd for those users who are comfortable with it,” said Fabel, “but enabling the standard enterprise database set makes it easier for many IT teams to operate K8s.”

<ends>

About Canonical

Canonical is the publisher of Ubuntu, the OS for most public cloud workloads as well as the emerging categories of smart gateways, self-driving cars and advanced robots. Canonical provides enterprise security, support and services to commercial users of Ubuntu. Established in 2004, Canonical is a privately held company.

Related posts


Benjamin Ryzman
18 September 2024

What is the 5G Edge and Multi-Access Edge Computing?

Ubuntu Telecommunications

Introduction The 5G Edge is revolutionising the telecommunications industry by significantly enhancing network performance, bringing computing power closer to users, and dramatically reducing latency, enabling faster and more efficient services. This advancement is crucial for a variety of applications across different sectors, including ...


Felipe Vanni
18 September 2024

Join Canonical in Sydney at Dell Technologies Forum

AI Partners

Canonical is excited to be exhibiting at the upcoming Dell Technologies Forum – Sydney on the 24th of September. This leading event brings together industry leaders and tech enthusiasts to explore the latest advancements shaping the digital landscape. Register to Dell Technologies Forum – Sydney Engage with Cutting-Edge Solutions Canonica ...


Canonical
17 September 2024

Introducing Data Science Stack: set up an ML environment with 3 commands on Ubuntu 

AI Article

Canonical, the publisher of Ubuntu, today announced the general availability of Data Science Stack (DSS), an out-of-the-box solution for data science that enables ML environments on your AI workstation. It is fully open source, free to use and native to Ubuntu.  It is also accessible on other Linux distributions, on Windows using Windows ...