EXCLUSIVE INTERVIEW

The Linux Desktop Will Have Its Day: Q&A With Canonical Founder Mark Shuttleworth

Canonical founder and CEO Mark Shuttleworth, developer of the Ubuntuopen source operating system, announced in December that he wasstepping aside to develop cloud product design and curry new partners.

He named Chief Operating Officer Jane Silber to take his place as CEO.Several weeks ago, Silber announced the hiring of open source industryveteran Matt Asay to fill her old job as COO.

Canonical, the London-based commercial sponsor of the Ubuntu Linuxdistribution, set high performance standards with its commitment fornew distro releases for its popular desktop and server editions everysix months.

LinuxInsider discussed with Shuttleworth the rise of adoption ofUbuntu Linux and how Canonical is adapting to the demands of winningconverts from other operating systems.


Listen to the podcast (27:20 minutes).


Here are some excerpts:

Linux Insider: Given the growing reach of the Ubuntu server and desktop editions, what do you see as the driving factors for their acceptance?

Mark Shuttleworth:

I think the most powerful drivers of the historicaland wonderful adoption rate of Ubuntu have been the combination of therelentless focus we’ve put into the delivery of the system and theterms under which we do it. On the delivery front we recognize thatthe distributions play an important but ultimately quite a humble rolein the formation of the open source ecosystem.

People think of Ubuntuas Linux, or Red Hat as Linux, or they think of Debian as Linux. Butactually the real work gets done in many upstream communities. Thedistributions get a lot of credit. And our focus has been to reallytry to serve those upstream communities well by delivering their codeto users on a very predictable schedule with the highest levels ofquality and integration.

So what that means to users is they get on avery predictable schedule a high-quality drop of the very best ofwhat’s available from the open source ecosystem which they canembrace with confidence.

LIN: What about developers?

Shuttleworth:

For the developers it means that their code landson peoples’ desks with us bearing the full brunt of interaction of endusers around that code. There is nothing stunningly insightful inthere. But by really focusing on the art of delivering a complete andeasy-to-use system, that represents the very best of what’s going on inthe ecosystem and is quite impartial in its assessment of that. Ithink we’ve really given users something that they really want.

LIN: What will take Ubuntu to the next level?

Shuttleworth:

In terms of looking forward and breaking into newareas of production, we are seeing sort of a real shift in the waypeople think about at Ubuntu in two different environments.

On theconsumer front, we’re seeing a shift in the way people think aboutalternative platforms to Windows amongst the PC companies. It used tobe a kiss of death to present yourself as a genuine alternative toWindows. But the success of the Web and the success of Apple havereally made the PC companies think that it is possible to offersomething that is perceived to be valuable even if it is not Windows.

So we’re seeing a rapid ramp-up of the number of PCs that ship aroundthe world with Ubuntu, which is good for us. And those are going tofolks who are not Linux enthusiasts and are not Linux specialists. Soit has really raised the bar on the quality and crispness of theexperience you have to deliver in order to keep those people happy.

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Charmed Kubeflow 1.4 Brings Smart, Agile MLOps to any Cloud

Machine Learning

Canonical is pushing the limits on its MLOps platform to automate the full lifecycle of feature engineering, training, and release workflows for machine learning (ML) models.

The Canonical Data Platform team on Tuesday announced the release of its MLOps platform Charmed Kubeflow 1.4. The new free release enables data science teams to securely collaborate on AI/ML innovation on any cloud, from concept to production.

Charmed Kubeflow is an open source MLOps platform released under the Apache License 2.0. The platform helps data scientists automate the workflow from ideation to production.

This latest release includes upstream Kubeflow 1.4 with many improvements over previous versions. It now includes support for MLFlow integration.

Charmed Kubeflow deploys in any environment without constraints, paywall, or restricted features. Data labs and MLOps teams only need to train their data scientists and engineers once to work consistently and efficiently on any cloud or on-premises installation.

The platform’s main benefit is a centralized, browser-based system that runs on any conformant Kubernetes. Other benefits include enhanced productivity, improved governance, and reduced risks associated with shadow IT.

The latest release adds several features for advanced model lifecycle management, including upstream Kubeflow 1.4. Future releases will continue to focus on empowering data scientists and data engineers, according to Rob Gibbon, product manager at Canonical.

“One area of focus for the product is composability and extensibility via a component ecosystem,” he told LinuxInsider.

“Additionally, we will be continually improving solution enterprise readiness, and of course tracking upstream Kubeflow to ensure data scientists continue to get access to the very latest features in a fully supported manner,” said Gibbon.

Getting Started

Kubeflow is available now. Data scientists can get started with it using Juju, the unified operator framework for hyper-automated management of applications running on both virtual machines and Kubernetes.

The new release is in the CharmHub stable channel now. It can be deployed to any conformant Kubernetes cluster using a single Juju command:
juju deploy kubeflow

The full installation guide is available here for free. The software is open source with 24/7 support or fully managed service options available from Canonical.

Engineers and data scientists can rapidly set up an evaluation environment with or without GPU acceleration using just a single system running MicroK8s. Evaluators can read the getting started guide. It takes less than 30 minutes to start improving AI automation.

Under the Hood

This release provides better model lifecycle management with Kubeflow 1.4 and MLFlow integration. Kubeflow 1.4 comes with major usability improvements over previous releases, including a unified training operator.

The new training operator supports the popular AI/ML frameworks TensorFlow, MXNet, XGBoost, and PyTorch. This greatly simplifies the solution, improving future extensibility and consumes fewer resources on the Kubernetes cluster.

Kubeflow 1.4 has support for MLFlow integration, enabling true automated model lifecycle management using MLFlow metrics and the MLFlow model registry.

MLFlow is an open-source platform for AI/ML model lifecycle management. It includes features for experimentation, reproducibility, and deployment. MLFlow also offers a centralized model registry.

Using Integration

Data scientists and data engineers can use the MLFlow integration capability to build automatic model drift detection and trigger a Kubeflow model retraining pipeline.

Model drift occurs as model accuracy starts to decline over time due to changes in the live prediction dataset versus the training dataset.

Enabling MLFlow on a Kubernetes cluster and integrating it with a Charmed Kubeflow deployment using the Juju unified operator framework is straightforward, and the MLFlow Juju operator is available in CharmHub for immediate deployment.

Charmed Kubeflow 1.4 fully supports multi-user deployment scenarios out of the box for all Kubeflow components, including Kubeflow notebooks, pipelines, and experiments.

Charmed Kubeflow 1.4

This update simplifies using Charmed Kubeflow to improve governance and reduce the occurrence of shadow-IT environments. It also helps to combat organizational data leakage.

The authentication provider integration guide provides more information on setting up multi-user access controls for the Charmed Kubeflow 1.4 MLOps platform. 

Jack M. Germain has been an ECT News Network reporter since 2003. His main areas of focus are enterprise IT, Linux and open-source technologies. He is an esteemed reviewer of Linux distros and other open-source software. In addition, Jack extensively covers business technology and privacy issues, as well as developments in e-commerce and consumer electronics. Email Jack.

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