jaehyeon-kim/ideas.txt

## ideas.txt
**** Web Server (UI)
ShinyProxy
https://github.com/openanalytics/shinyproxy
https://github.com/openanalytics/shinyproxy-demo
http://www.shinyproxy.io/

Modularizing Shiny app code - http://shiny.rstudio.com/articles/modules.html

http://stackoverflow.com/questions/25306519/shiny-saving-url-state-subpages-and-tabs


**** Application Server
plumber
http://plumber.trestletech.com/
https://github.com/trestletech/plumber

http://www.londonr.org/presentations/2016/01/LondonR_-_APIs_in_R_with_plumber_-_Mark_Sellors_-_20160126.zip
http://dfac.github.io/code/2016/02/23/Converting-R-code-to-API/
http://www.programmableweb.com/news/how-to-turn-your-predictive-models-apis-using-domino/how-to/2015/07/22?page=2#apiu

Building a High Availability REST API Engine for R
http://schedule.user2016.org/event/7BYY/building-a-high-availability-rest-api-engine-for-r
Nick Elprin Domino Data Lab
Modern businesses require APIs that have rock solid uptime, where deploying a new version never drops a request, where you can promote and roll back versions, and that perform with low latency and high throughput. Domino has built our R

API endpoint functionality leveraging open source tools such as nginx and tresletech’s plumber package, to support modern data science teams desire to reduce time from modeling to productionalization. In this talk, we discuss lessons we

have learned building this functionality using the R ecosystem. We describe some of the technical challenges building such a platform, and some best practices for researchers who want to make their R models easily deployable as APIs.

Domino’s technology has served millions of requests for clients ranging from online media to energy companies. We will tell you how we did it.


RServer + supervise
http://stackoverflow.com/questions/32485131/how-to-make-an-upstart-service-to-rserve


R Message Queue
https://r-forge.r-project.org/projects/r-message-queue/


Others
RServe (+ supervisor)
OpenCPU
DeployR
Domino

R.NET, rClr, F# R Provider
JRI, Renjin


**** MISC
R’s lazy evaluation mechanism, promise
meta programming...


**** Microservices
http://brunorocha.org/python/microservices-with-python-rabbitmq-and-nameko.html
http://blog.apcelent.com/how-to-setup-microservices-python-zeromq-docker-example.html
http://codeahoy.com/2016/07/10/writing-microservices-in-python-using-flask/
	**** Web Server (UI)
	ShinyProxy
	https://github.com/openanalytics/shinyproxy
	https://github.com/openanalytics/shinyproxy-demo
	http://www.shinyproxy.io/

	Modularizing Shiny app code - http://shiny.rstudio.com/articles/modules.html

	http://stackoverflow.com/questions/25306519/shiny-saving-url-state-subpages-and-tabs


	**** Application Server
	plumber
	http://plumber.trestletech.com/
	https://github.com/trestletech/plumber

	http://www.londonr.org/presentations/2016/01/LondonR_-_APIs_in_R_with_plumber_-_Mark_Sellors_-_20160126.zip
	http://dfac.github.io/code/2016/02/23/Converting-R-code-to-API/
	http://www.programmableweb.com/news/how-to-turn-your-predictive-models-apis-using-domino/how-to/2015/07/22?page=2#apiu

	Building a High Availability REST API Engine for R
	http://schedule.user2016.org/event/7BYY/building-a-high-availability-rest-api-engine-for-r
	Nick Elprin Domino Data Lab
	Modern businesses require APIs that have rock solid uptime, where deploying a new version never drops a request, where you can promote and roll back versions, and that perform with low latency and high throughput. Domino has built our R

	API endpoint functionality leveraging open source tools such as nginx and tresletech’s plumber package, to support modern data science teams desire to reduce time from modeling to productionalization. In this talk, we discuss lessons we

	have learned building this functionality using the R ecosystem. We describe some of the technical challenges building such a platform, and some best practices for researchers who want to make their R models easily deployable as APIs.

	Domino’s technology has served millions of requests for clients ranging from online media to energy companies. We will tell you how we did it.


	RServer + supervise
	http://stackoverflow.com/questions/32485131/how-to-make-an-upstart-service-to-rserve


	R Message Queue
	https://r-forge.r-project.org/projects/r-message-queue/


	Others
	RServe (+ supervisor)
	OpenCPU
	DeployR
	Domino

	R.NET, rClr, F# R Provider
	JRI, Renjin



	**** MISC
	R’s lazy evaluation mechanism, promise
	meta programming...


	**** Microservices
	http://brunorocha.org/python/microservices-with-python-rabbitmq-and-nameko.html
	http://blog.apcelent.com/how-to-setup-microservices-python-zeromq-docker-example.html
	http://codeahoy.com/2016/07/10/writing-microservices-in-python-using-flask/