• With Charmed Kubeflow on AWS, users can now quickly launch and manage their machine learning workloads.
  • In 2022, 35% of organizations were expected to adopt AI, according to IBM’s Global AI Adoption Index.

Canonical Ltd., an Ubuntu software provider, released its machine learning operations toolset Charmed Kubeflow on Amazon Web Services Inc.’s cloud marketplace.

Charmed Kubeflow is available as a software application on AWS, simplifying the deployment and management of machine learning workloads for businesses. The software is an enterprise-grade variant of Kubeflow, an open-source MLOps toolkit designed to work with Kubernetes, the ubiquitous container orchestration software for application containers. It provides various utilities that make operating artificial intelligence on Kubernetes simpler.

Canonical says Charmed Kubeflow on AWS helps enterprises experiment with machine learning processes. It occurs when an increasing number of organizations demonstrate an outsized interest in artificial intelligence and machine learning. According to IBM Corporation’s Global AI Adoption Index, 35% of businesses will adopt AI in 2022. With the proliferation of generative AI initiatives such as ChatGPT, interest in the technology is proliferating.

Charmed Kubeflow on AWS, according to Canonical, is designed for businesses looking to launch their AI and machine learning initiatives because it is simple to deploy and offers unlimited computing power to experiment without limitations.

Charmed Kubeflow creates a trustworthy application layer for model development, iteration, and production deployment by automating machine learning workflows. Additionally, it offers complete visibility into those workloads so teams can evaluate any difficulties and precisely plan their infrastructure expansion needs.

Users can deploy their models on end devices after the complete experimental phase. Simultaneously, Charmed Kubeflow will guard against cyberattacks with frequent scanning, patching, and updates to the most recent version of the machine learning libraries in use. Users may move artifacts from the Charmed Kubeflow appliance to an AWS or data center deployment for production-grade deployments.

According to Aaron Whitehouse, senior director of public cloud enablement at Canonical, Charmed Kubeflow is the best platform for businesses looking to experiment with machine learning for the first time. He said, “The Charmed Kubeflow appliance on AWS gives companies a great way to test out machine learning possibilities quickly and easily, with a clear pathway to a scalable hybrid/multi-cloud deployment if those pilot projects are successful.”

A fully managed version of Charmed Kubeflow on AWS is now accessible through the AWS Marketplace for businesses needing infrastructure support.