I used this tutorial: https://medium.com/containermind/how-to-create-a-kubernetes-cluster-on-aws-in-few-minutes-89dda10354f4 https://medium.com/containermind/ho

I used this tutorial: https://medium.com/containermind/how-to-create-a-kubernetes-cluster-on-aws-in-few-minutes-89dda10354f4 https://medium.com/containermind/how-to-create-a-kubernetes-... It is also nice that I could do this on macs and linux. I used my personal MBP to do some and my office machine (system76 running Ubuntu.) The best advice would be to create, test, delete over and over and over. I used personal AWS funds to do this while in grad school, so the added pressure of making the best use of limited funds was great -- i would spin up dozens and dozens of machines, join, run, tear down in short timeframes. As usual, choose a simple project. I chose multi-machine TensorFlow inference a model since that is something that is an obvious candidate for elasticity. Funny story - I once spun up a K8 cluster and tried to delete the machines manually on AWS and witnessed how incredibly robust the cluster is (new nodes kept getting re-instantiated.) Lessons learned: 1. K8 is robust; 2. use kops to also tear down the cluster; AWS has their own tutorial, but I didnt like that -- it was too focused on tangential details.