Canonical at Kubecon Europe 2019
Thibaut Rouffineau
on 1 May 2019
Tags: Kubeflow , kubernetes , MicroK8s
Date: May 20-23
Location: Fira Gran Via, Barcelona, Spain
Booth: P10
KubeCon and CloudNativeCon are back in Europe and we should witness the next phase in the exploding popularity of Kubernetes and of this event…
Canonical will also be back at KubeCon, showcasing our multi-cloud Kubernetes portfolio:
- Ubuntu being the number 1 operating system for Kubernetes in the public cloud powering GKE, EKS or AKS.
- Charmed Kubernetes allowing 1.14 deployment anywhere on public cloud, Openstack, VMware or bare metal.
- MicroK8s, the single node Kubernetes for workstations and embedded deployments
Come and discuss how Ubuntu Advantage for Infrastructure, takes the pain out of deploying a supported, upstream Kubernetes. With one contract you can deploy Kubernetes on bare metal or Openstack for the same price with no additional paperwork. With the speed of deployment of Charmed Kubernetes you can change your mind, experiment with various combinations and it’s still the same price.
On the demo front, come and visit our booth to check out:
- Installing microK8s in less than a minute
- The Ubuntu AI story told with examples of virtual instance on AWS, using both normal VMs and GPU-enabled ones
- Self-service multi-cloud Kubernetes on bare metal, AWS, Azure, GCP, OpenStack and VMware
Run Kubeflow anywhere, easily
With Charmed Kubeflow, deployment and operations of Kubeflow are easy for any scenario.
Charmed Kubeflow is a collection of Python operators that define integration of the apps inside Kubeflow, like
katib or pipelines-ui.
Use Kubeflow on-prem, desktop, edge, public cloud and multi-cloud.
What is Kubeflow?
Kubeflow makes deployments of Machine Learning workflows on Kubernetes simple, portable and scalable.
Kubeflow is the machine learning toolkit for Kubernetes. It extends Kubernetes ability to run independent and
configurable steps, with machine learning specific frameworks and libraries.
Install Kubeflow
The Kubeflow project is dedicated to making deployments of machine learning workflows on Kubernetes simple,
portable and scalable.
You can install Kubeflow on your workstation, local server or public cloud VM. It is easy to install
with MicroK8s on any of these environments and can be scaled to high-availability.
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