anchor.diff:  * The API will be accessible only by people providing a Facebook OAuth token
   * Each API must have a monitoring / metrics facility
   * Each service may be packaged as a standalone jar, to be run using `java -jar`.
  -* Performance of POST and GET
  -* I will measure the startup time of each server (not that important, but interesting)
  +* On the performance side, I will measure:
  +** request time of POST and GET
  +** the startup time of each server (not that important, but interesting)
  +** the memory footprint of the application
   * Finally, I will give the final size of the package.
   
   == The candidates
  
positive.code: = A comparison of Microservices Frameworks
  :hp-tags: Tech, Microservices, REST
  
  Microservice is probably one of the most used term nowadays, while we are speaking about software architecture. Although the concepts aren't that new, it is one of the biggest buzzword of the two last years.
  
  To summarize, big monolithic architectures tend to become not very maintainable and extendable when they grow over a certain size. Moreover, they don't scale well (you scale by multiplying big applications), and you can't replace bad old parts easily.
  
  One of the biggest advantages of microservices is to address these concerns: instead of building an entire application as one block, one can build it as a set of services which will communicate over some kind of messaging system (most of the time, REST / HTTP). Given that, you will be able to replace one piece if you need to, you can scale only one piece because you need to, and so on.
  
  But there is a counterpart: as you're building a distributed system, you will have the disadvantages of a distributed system. Building a distributed system as microservices architecture is not that easy, but fortunately there are many frameworks to help you. This article will present some of them.
  
  
negative.code: Note that Restlet and Spark doesn't claim to be MicroServices frameworks, but Restlet is known to be a very good REST framework, and Spark is so lightweight that I couldn't resist to try it against bigger frameworks like Spring Boot.
  
  == Dropwizard
  
  
  == Vertx
  
  