AI on Ubuntu: the path
to production

The best data science and MLops tools across your infra

Develop AI models on high-end Ubuntu workstations. Train on racks of bare-metal or public clouds with hardware acceleration. Deploy to cloud, edge and IoT. All on Ubuntu.

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  • Tesla
  • Nvidia
  • Facebook
  • OpenAI


Best of breed data science tools.

The most productive tools for AI / ML development, with guides and resources available.

  • Jupyter
  • Keras
  • Scikit Learn
  • TensorFlow
  • PyTorch


Multi-framework model serving.

Effective model deployment across devices mesh. Low-latency inference serving.

  • Seldon
  • KFServing
  • Onnx
  • TensorRt
  • XGBoost

ML operations

Infrastructure for production data science.

Centralised or multi-cloud training infrastructure for better resource allocation and data governance.

  • Kubeflow
  • ML-Flow
  • Pachyderm
  • Juju

Data lake

Analyse epic amounts of data, wherever it is.

Build large-scale data lakes optimised for machine learning on bare metal, virtual or cloud infrastructure with open source.

  • Kafka
  • Cassandra
  • Elastic
  • Hadoop

Hardware control

Drivers, storage, networking, CPU, GPU, DPU.

Enjoy full control over your firmware, in a safe environment, tested by millions.

  • Nvidia
  • AMD
  • Intel
  • ARM

Portable to scale

Give your workloads consistency everywhere.

Portable from desktop to vast multi-clouds. Fast-deploy on every major public cloud with GPU acceleration.

  • Server brand
  • Openstack
  • AWS
  • Google Cloud
  • Microsoft Azure

Every Kubeflow operator you need

Lifecycle management of your data stack on Kubernetes

  • Make use of open source lifecycle management code and compound the benefit of .
  • Composable operators for data scientists to stand up and integrate the applications they need, on a laptop, workstation or cluster.
  • Install, configure, upgrade, remove.

Kubeflow Topology

Ubuntu Advantage

Canonical AI services

Enterprise support, deployment, training and fully managed Kubeflow

  • Rely on 24/7 enterprise support with guaranteed SLAs.
  • Provide specialised MLOps training to your sysadmins, devops engineers and data scientists. Any infra and level of expertise, tailored to your data.
  • Off-load the complexity of Kubeflow deployment and management to Canonical engineers.

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MLops for devices and Micro clouds

Industrial grade data pipelines from cloud to edge

  • High-throughput inference at the edge with fast model updates.
  • Build your AI/ML on top of the most reliable edge infra.
  • Ubuntu Core for IoT, for zero-ops K8s with high-availability, Kubeflow for inference and distributed training.

Ubuntu for IoT Kubeflow at the edge ›

Kubeflow to the

Learn more about AI/ML and Kubeflow

Get started with AI and Machine learning today.

Or contact our experts to get started with consulting, training or outsourced operations.

Kubeflow Topology