Managed MLOps on AWS

An Overview of Canonical MLOps

Managed Canonical MLOps enables you to:

• Develop and deploy machine learning models on an end-to-end open source MLOps platform
• Focus on project delivery, while Canonical experts manage the infrastructure for you
• Benefit from security patching of your ML infrastructure
• Smoothly upgrade so you can build using the most innovative tools available

Canonical MLOps solution is a growing ecosystem of leading open source ML tools that are seamlessly integrated depending on the user's needs and validated on different platforms. Charmed Kubeflow, Canonical’s distribution of the upstream projects is the foundation of it.

With Charmed Kubeflow, data labs and MLOps teams need only train their data scientists and data engineers once to work efficiently. Charmed Kubeflow offers a centralized, browser-based data lab MLOps platform, improving governance and enhancing productivity.

Kubeflow is an open source MLOps platform for efficient AI and ML from research through development to production. Based on fully supported, best-of-breed open source technologies including Kubeflow, MLFlow and Tensorflow, Charmed Kubeflow enables secure, repeatable and efficient implementation of AI/ML applications from conception to production. Fully extensible Python and R support futureproof your investment.

Canonical MLOps is a cloud-native solution and runs on any Kubernetes, including EKS. It supports hybrid and multi-cloud scenarios, giving customers freedom to migrate their workloads and maximize their computing resources.