Kubernetes, the cluster manager for containerized workloads, is a hit. With the Big K doing the heavy lifting in load balancing and job management, you can turn your attention to other matters.But like nearly every open source project, it’s a work in progress, and almost everyone who works with Kubernetes will find shortcomings, rough spots, and annoyances. Here are four projects that lighten the load that comes with administering a Kubernetes cluster.[ Roundup: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Get a digest of the day’s top tech stories in the InfoWorld Daily newsletter. ]
Kube-applier
A key part of the Kubernetes success story is its uptake with IT brands other than Google.

Cloud storage firm Box has picked up on Kubernetes and open-sourced some of the bits it’s used to aid with its internal deployment; kube-applier is one such project.To read this article in full or to leave a comment, please click here

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