Google is betting big on Tensor Flow, the leading open source machine learning liberary by Google. And off late Kubernetes, the opensource container orchestration tool which the search giant developed, opensourced and later donated to The Cloud Native Computing Foundation, is quickly becoming quite a standard in cloud development methodology by providing P-A-A-S level functionality in a vendor independent manner through Infrastructure As Code.
David Aronchick is the man behind Kubeflow who was working with Kuberneets team for the last 2.5 years and has recently moved on to leading Kubeflow. The project allows data scientists or developers to run machine learning processes in Kubernetes clusters.
Although currently the project only supports Google’s machine learning tools but over time they plan to add support for other tools as well. The plug and play opensource philosophy will be critical in developing the ecosystem around such a technology and it is already showing results in the form of 70 contributors, over 20 contributing organizations along with over 700 commits in 15 repositories with version 0.2 already in the pipeline. All of this in just 4 months of initial release.