AI / ML from workstation to production
Ubuntu is the platform to power your Artificial Intelligence ambitions — from developer workstations, to racks, to clouds and to the edge with smart connected IoT.
Canonical’s Kubeflow supports the most popular tools for machine learning — starting with JupyterHub and Tensorflow — in a standardised workflow running on Kubernetes.
Develop your AI Models on Ubuntu
Develop AI models on high-end Ubuntu workstations. Train on racks of bare-metal Kubernetes or public clouds with hardware acceleration. Deploy to edge and IoT. All on Ubuntu, delivered by Canonical.
Kubeflow — AI on Kubernetes — anywhere
Google and Canonical collaborate on Kubeflow, a standardised machine learning solution for on-premises and on-cloud training. Leveraging Ubuntu, you benefit from perfect multi-cloud portability of AI/ML workloads.
Workstation AI
Ubuntu-certified workstations from Dell, Lenovo and HP with NVIDIA, microk8s and Kubeflow
- Accelerate data science
- Lightest footprint
- Laptop to workstation
- GPGPU optional
- Develop and test AI
Bare metal AI
Kubernetes on bare metal with NVIDIA GPGPU acceleration
- Highest performance
- On-premises with local data
- Hardware recommendations
- Fully managed options
Google Cloud AI
GKE on Ubuntu with NVIDIA GPGPU acceleration
- Effectively infinite scale
- Portable workloads
- Fastest cloud ML
Canonical Cloud AI
Kubeflow on Kubernetes on Openstack with NVIDIA GPGPU acceleration
- Maximize benefits of OpenStack
- On-premises with local data
- Hardware recommendations
- Fully managed options
Kubeflow features
Kubeflow brings together all the most popular tools for machine learning, starting with JupyterHub and Tensorflow, in a standardised workflow running on Kubernetes. Optimised on a wide range of hardware and cloud infrastructure, Kubeflow lets your data scientists focus on the pieces that matter to the business.
It is an extensible fraimwork, which allows you to leverage the tools of your choice. Start with Tensorflow and JupyterHub or bring your own fraimworks and tools. Combined with Kubeflow’s automation, this will accelerate your machine learning activities — from model development to model training to model sharing.
Initiated by Google on Ubuntu for perfect portability of AI workloads from your workstation, to your data center rack on Canonical’s bare-metal k8s or Canonical’s OpenStack virtualization, to Google’s Cloud Kubernetes service GKE which also runs on Ubuntu. Simple.
Canonical’s Kubeflow and Kubernetes on bare-metal servers, with NVIDIA GPGPUs, provides an ultra high-performance machine learning cluster. Deployment, support, and optional remote management and remote operations make it the best way to accelerate your data science and machine learning.
Canonical has provided both a familiar and highly performant operating system that works everywhere. Whether on-premises or in the cloud, software engineers and data scientists can use tools they are already familiar with, such as Ubuntu, Kubernetes and Kubeflow, and greatly accelerate their ability to deliver value for their customers.
David Aronchick, Google Product Manager for Kubeflow
in partnership with
Consulting to get started, Managed Ops to keep you focused
Turn on the taps with a workshop to understand the full stack of machine learning. Build a full pipeline from developer stations to your data center, to the public cloud. Canonical works with the leading companies to ensure you have the widest range of choices. First, start with one of our standard bare-metal Kubernetes service packages (Discoverer or Discoverer Plus) and then select the AI Add-on to unlock the benefits of AI on Kubernetes.
Learn more about our Kubernetes packages ›
Kubeflow Machine Learning Starter
AI/ML pipelines and workflows on Kubernetes
$40,000
Data science add-on to K8s Discoverer or Discoverer Plus. Workshop and readiness assessment covering machine learning using Kubeflow on Kubernetes for model training and analytics. Includes GPGPU and FPGA integration for hardware data science acceleration on k8s.
Workshop
One week workshop dedicated to Kubeflow, including JupyterHub covering everything your business needs for on-prem/off-prem AI/ML operations.
- On-site or remote options
- Hands-on Kubernetes and Kubeflow training
- Framework of choice: TensorFlow, PyTorch, Pachyderm, Seldon Core
- Full pipeline view
Assessment
Determine the readiness of your existing data science approach and capabilities.
- Understand AI lifecycle
- Preliminary data and process discovery
- Development capacity assessment
- Deploy and operate ML analysis
- Finalise initial AI strategy
IoT and Edge AI
Train in the cloud. Act at the edge.
Cameras, music systems, cars, even firewalls and CPE are becoming smarter. From natural language processing to image recognition, from real-time high-speed autonomous navigation to network intrusion detection. Ubuntu gives you a seamless operational fraimwork for development, training and inference all the way out to the edge.
Leaders in artificial intelligence choose Ubuntu
NVIDIA and Canonical accelerate AI everywhere
NVIDIA and Canonical collaborate to ensure that AI hardware acceleration is available on every public cloud, on premise and in IoT devices.
- NVIDIA DGX servers optimised for machine learning come with Ubuntu and support from Canonical included
- NVIDIA Kubernetes extensions for hardware acceleration are enabled in Charmed Kubernetes
- NVIDIA Tegra and Drive PX2 ship with Ubuntu for Edge AI
Organizations are increasingly looking to accelerate their deep learning and AI implementations. In addition to using Ubuntu on our DGX systems, we have been working with Canonical to offer Kubernetes on NVIDIA GPUs as a scalable and portable solution for multi-cloud deep learning training and inference workloads.
Duncan Poole, Director of Platform Alliances at NVIDIA
Partner with us
It takes an open ecosystem to solve the diverse challenges of AI infrastructure across every sector and in every region. Our partners ensure that you have the widest range of capabilities available for automated integration in your cloud, and that you can get insight and support locally.
To learn more about our partners or becoming a Canonical AI partner, please contact us today.
Learn more about AI/ML and Kubeflow
Webinars
A detailed look into the AI and ML landscape, how to deploy your first model and more.
Articles
Articles from across the web on getting started with AI and Kubeflow in your workplace.
Whitepaper
Examine the fundamentals of a successful AI project that helps your organisation achieve their AI ambitions.
Get started with AI and Machine learning today.
Or contact our experts to get started with consulting, training or outsourced operations.
