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Canonical announces fully Managed Kubeflow AI operations ...
Massimiliano · 2026-05-21 · via Ubuntu blog

Canonical, the publisher of Ubuntu, today announced the general availability (GA) of Managed Kubeflow on the Microsoft Azure Marketplace. This solution enables AI teams to get a fully managed, production-ready MLOps platform in their own tenant.

Upstream Kubeflow is a powerful tool for machine learning, but it remains notoriously challenging to deploy and maintain. Organizations often find that their high-value data science teams waste a considerable portion of their capacity on infrastructure maintenance. Day-2 operations, such as manual upgrades and complex security patching, frequently stall model delivery and inflate operational costs.

Canonical Managed Kubeflow solves these challenges by giving enterprise and startup AI teams a fully operational, open source MLOps platform in under an hour – managed 24/7 by Canonical’s engineers – so data scientists can focus entirely on models rather than infrastructure. 

Enterprise-grade control and data governance

Managed Kubeflow on Azure removes the burden of monitoring and maintenance from platform engineering teams. Canonical’s expert engineers provide 24/7 management, including seamless version upgrades.

The platform is built on the following core pillars:

  • In-tenancy deployment: The service runs entirely in-tenancy within the customer’s Azure Virtual Network (VNet). Proprietary models and training data never leave the customer’s security perimeter.
  • Single Sign On: Native integration with Microsoft Entra ID, Okta or any other OpenID Connect (OIDC) compliant identity provider provides teams with securely designed, centralized authentication and access control.
  • Portability and control: Built on proven upstream Kubeflow, MLFlow and KServe, the platform ensures total portability as both the underlying application and automation code are open source. Your investment can travel with you if your strategy shifts toward hybrid or multi-cloud environments.

Accelerating Kubeflow time-to-value

The service is available directly via the Azure Marketplace as a transactable listing. Every subscription decrements a customer’s Microsoft Azure Consumption Commitment (MACC) on a 1-for-1 basis. This enables startups and large enterprises to bypass lengthy procurement cycles and deploy using existing Azure commitment.

The platform scales effortlessly to accommodate a diverse range of enterprise workload demands. Users can deploy lightweight environments for rapid prototyping and initial testing phases. For critical production workloads, built-in High Availability (HA) guarantees enhanced system reliability.

The service runs natively inside the robust Azure Kubernetes Service (AKS) environment. Administrators can configure independent worker pools featuring auto-scaling capabilities. Depending on your use case the service enables you to allocate cost-effective CPUs for development tasks and powerful GPUs for intensive model training. This optimizes Azure spend while simultaneously accelerating workflow performance.

For AI and data executives, the service solves the challenge of needing to staff specialized MLOps teams before achieving product-market fit. It combines flexibility with the reliability required for production-grade AI projects, all while ensuring data governance, significantly lowering the barrier to innovation

Get started with Managed Kubeflow on Azure 

Managed Kubeflow on Azure is available now on the Azure Marketplace. Organizations can deploy the service directly from the Azure Marketplace to begin scaling their AI operations immediately:

Deploy Managed Kubeflow on Azure

Additional resources

About Canonical

Canonical, the publisher of Ubuntu, provides open source security, support, and services. Our portfolio covers critical systems, from the smallest devices to the largest clouds, from the kernel to containers, from databases to AI. With customers that include top tech brands, emerging startups, governments, and home users, Canonical delivers trusted open source for everyone. Learn more at https://canonical.com/