Just as an FYI, we[1] are working on an open source, cloud based Machine Learning / Big Data platform that might be of interest to you. It's not all ready yet, but when it is, there will be a simple REST API that allows you to define the kind of setup you want, "push a button" and have it all deployed. Our initial backend is AWS with plain jane EC2 nodes, but it will be possible to extend it to other configurations as well.
Right now we deploy a Spark/Hadoop Cluster with Apache SystemML, Mahout and MLLib installed. Zeppelin will be coming to the stack, as will other tools like TensorFlow, SparkR, CaffeOnSpark, etc.
We'll be offering our own hosted service based on this, but it'll be open source so you can deploy it in an environment of your own if you wish.
We'll do a "Show HN" when we have something ready, so keep an eye out if that sounds interesting.
I also plan to write up some tutorial and documentation based on our experiences building this out, but the priority right now is getting it built. :-)
If you'd like to do this in containers/Kubernetes, we'd love to highlight your work! Kubernetes runs great on AWS (as well as GCP, Azure and elsewhere), so no cloud migration required.
Great to hear, congrats on reaching 1.0! Please do reach out when you get there, we'd love to show off your work to the community.
I'm all for roll your own if you're building one of these services or have existing infrastructure, but I personally like the simplicity of "here, you set this up".
Disclosure: I work at Google on Compute Engine (which underlies all of these).
Even better, Ambari isn't actually limited to installing just Hadoop/Spark, etc. In principle, you could extend it to take care of installing pretty much anything.
http://hortonworks.com/hadoop/cloudbreak/
Disclosure: I work for Hortonworks
We totally agree - we'd love to help folks get started with common frameworks. Did you have any, in particular, that you'd like us to work on next?
I took a Spark course on eDX last year, but the environment was set up using a customized Vagrant config with no real-world use. I definitely prefer the Kubernetes approach.