The easiest way to automate the deployment, scaling, lifecycle and management of your applications. Operate the latest Kubernetes, from the experts behind Ubuntu and the Kubernetes community.
Start with a Kubernetes cluster of two machines — one master node and one worker node.
Accelerate Deep Learning workloads by adding GPUs at scale, with totally automated deployment.Start GPU tutorial
Get Kubernetes up and running on a single system with LXD, or a public cloud such as AWS, GCE or Azure.
Monitor, profile and debug your applications.
Centralize all logs and metrics and get awesome dashboards for your cluster.
Run stateful applications on bare metal or private clouds.
Setting up your Deep Learning framework is now easier than ever with the new GPU integration of the Canonical Distribution of Kubernetes*. Perfect for production grade, on bare metal or in the cloud.
The Canonical Distribution of Kubernetes enables automatic discovery of GPU devices. Work as well with LXD to get a fine grain control mechanism to orchestrate video workflows and maximize the throughput of your clusters.
Kubernetes can be complemented by another layer to transform it into a PaaS, to maximise the proficiency of the development teams. It will provide complete freedom to deploy and manage your applications.
from $200/ year per node
Canonical offers two support packages: Standard and Advanced.
from $19,500 one off fee
Canonical offers two Kubernetes consulting packages: Kubernetes Explorer and Kubernetes Discoverer.
To contact us for more information or to discuss your specific needs, email us at firstname.lastname@example.org.