Coauthors: Jeremy Lewi (Google), Josh Bottum (Arrikto), Elvira Dzhuraeva (Cisco), David Aronchick (Microsoft), Amy Unruh (Google), Animesh Singh (IBM), and Ellis Bigelow (Google).

On behalf of the entire community, we are proud to announce Kubeflow 1.0, our first major release. Kubeflow was open sourced at Kubecon USA in December 2017, and during the last two years the Kubeflow Project has grown beyond our wildest expectations. There are now hundreds of contributors from over 30 participating organizations.

Kubeflow’s goal is to make it easy for machine learning (ML) engineers and data scientists to leverage cloud assets (public or on-premise) for ML…


A quick guide to the ML Ops talks on offer

We are excited that O’Reilly’s Open Source Software Conference (OSCON) has added “AI Enhanced” as an official track this year, exploring topics around applied artificial intelligence and machine learning. A majority of those talks will tackle the open source tools and best practices that ML professionals are developing to operationalize machine learning models & workflows.

There will be a bunch of Kubeflow contributors and users attending OSCON to discuss how they are approaching ML Ops.

To get the most out of the conference, attend one of the Kubeflow-related talks listed below. …


The Kubeflow Product Management Working Group is excited to announce the release Kubeflow v0.5, which brings significant improvements to users’ model development experience!

New features in Kubeflow 0.5 include:

  • A Go binary, kfctl, to simplify configuring and deploying Kubeflow
  • An improved UI for managing notebooks that makes it easy to:
  • Run multiple notebooks simultaneously
  • Attach volumes to notebooks
  • The Fairing library to build, train, and deploy models from notebooks or your favorite Python IDE

Demo Kubeflow 0.5 by building, training and deploying an XGBoost model

We thought the best way to illustrate Kubeflow 0.5’s …


An update from the Product Management team on what shipped with Kubeflow 0.4, including more details on Pipelines and examples on building, training and deploying models from Jupyter notebooks.

Kubeflow is building the leading Kubernetes-based open source community for Machine Learning (ML) software application development. Today, we’re pleased to announce that Kubeflow 0.4 is available and includes many important enhancements to speed the development of ML applications. Here we’ll review the new Pipelines functionality, take a look at Kubeflow 0.5 planning, and introduce two new community initiatives: the Kubeflow User Survey and the upcoming Kubeflow Day in Los Angeles.

Over…


The Kubeflow Product Management Team

Just a year ago, we released Kubeflow 0.1 at KubeCon Austin. Since then, the project and its community have grown significantly, both in members and contributions. As of December 18th, there are 100+ active Kubeflow members with the support of over 30+ organizations. In the last 6 months alone, the number of unique PR authors per month has nearly doubled from 40 to 80. (You can page through all these stats yourself here). Even better, many supporting projects have collaborated with the Kubeflow community to extend and expand the value of the ecosystem. …


Vartika Singh (NVIDIA), Jeffrey Tseng (PM for RAPIDS, NVIDIA), Pete MacKinnon (Red Hat), Abhishek Gupta (Google)

Data science workflows are complex, non-trivial to manage, and compute intensive. NVIDIA and the Kubeflow team are trying to simplify the process and, at the same time, speed them up.

Today, we’re announcing the availability of the NVIDIA RAPIDS GPU-accelerated data science libraries as an image on the Kubeflow Pipelines.

Inherently complicated, data science pipelines span the iterative phases of ingestion, validation, training, deployment, and more. They scale across clusters of servers running software from different parts of the workflow. And they are often…


The Kubeflow Product Management Team

Kubeflow is building the leading Kubernetes-based open source community for Machine Learning (ML) software application development. We wanted to provide details on new features and valuable new functionality that’s been committed into the upcoming Kubeflow 0.4 release, and how they’ll benefit AI development. As of December 10, the Kubeflow 0.4 release development for the P0 and P1 priority open items is ~65% completed and a preview of the release is expected to be available by the end of the month.

Over the last year, the Kubeflow Community has effectively organized and delivered 90-day software releases…


30 talks with new tech, production stories, and GraphQL advice

This year’s GraphQL Summit conference was in San Francisco on October 25-26. It was an incredible event with tons of talks, panels, and hallway discussions about moving the GraphQL community forward.

If you couldn’t make it this year, we’ve put together a three-minute highlight video to capture the electric atmosphere at the event:

And now, without further ado, here’s the full playlist on YouTube with all 30 talk videos:

GraphQL Summit 2017 video full playlist

If you’ve got some time off in the coming weeks, that’s a great opportunity to kick back, make some tea, and start absorbing the…


Plus, details on the GitHub Diversity Scholarship

GraphQL Summit 2017 is only a month away, on October 25 and 26, and we’re excited to roll out the full list of speakers who will be sharing their GraphQL best practices and adoption stories. Stay tuned for the full conference schedule with talk times early next week.

Tickets are selling fast, so reserve your seat now! Use the promo code GRAPHQLFTW for 10% off, or use the new buddy pass promotion to get 2 tickets for 20% off.

Everything you need to know about using GraphQL today (and tomorrow)

We couldn’t be more excited about this lineup, which was carefully selected by a panel of representing some of the major…


Tips to supercharge your GraphQL dev in 5 minutes or less

A long time ago (about 20 minutes) in a galaxy far, far away (North Jersey)…

Let’s be real: It can be hard to find the time to consume a dense, 10-minute read about technical best practices. As much as we love churning those posts out on the Apollo publication, we don’t want time to stand between you and leveling up your GraphQL skills.

That’s why we’re excited to launch Apollo Mission Briefing, a brand new video series starring the newest member of the Apollo team, Peggy Rayzis! She’ll be making topical, bite-sized videos featuring the GraphQL tips and tricks that you most want to learn. …

Thea Lamkin

open source strategy @kubeflow, formerly @apollographql @docker & @newrelic. makes a mean frittata.

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