Canonical Managed Kubeflow
by Canonical
Develop and deploy AI models on a scalable MLOps platform, fully managed by specialized engineers.
Overview
Set up Managed Kubeflow on Microsoft Azure in under an hour and start building AI models instantly on a fully operational open source MLOps platform – fully managed 24/7 by Canonical’s engineers.
Harness all the benefits of Kubeflow without worrying about underlying infrastructure and operations.
AI capabilities
Rapid automated deployment enables teams to start working on AI models in under an hour, removing the complexities of setting up and maintaining ML infrastructure. Develop AI models including Large Language Models (LLMs), Vision Language Models (VLMs) and other multi-modal models on a scalable MLOps platform and let Canonical’s specialized engineers maintain your infrastructure, giving you the freedom to harness Kubeflow’s extensive benefits and accelerate your AI initiatives. The deployment also includes MLFlow – the proven industry standard for tracking and model registry – along with full observability, running on Azure Kubernetes Service (AKS).
Managed Services
Our managed service completely removes operational burdens by providing exhaustive coverage of your applications’ operations like monitoring, alerting, upgrades and patching, incident and recovery protocols, and more.
Ecosystem Integration
We’ve designed our Managed Kubeflow with integration in mind. It is fully compatible with Canonical’s multicloud and hybrid solutions as well as Azure’s extensive ecosystem, including Azure Blob Storage, Azure CosmosDB, and Azure OpenID. You get full control over your configuration, which autoscales within the parameters you select, according to your workload requirements.
Offer subject to Canonical Ubuntu Pro Terms & Conditions.
For private offers or enterprise support options, please Contact Us.
