Ever tried to start up a Spring Boot app only for a busted cache to stop it in its tracks? Cache abstraction and error handling might be a way to keep things smooth.
Gatling and JMeter have different features based on what you're looking for, but they're not without their disadvantages. Taurus can help fill in the gaps.
Docker Swarm makes it relatively easy to scale apps. With the help of Terraform and Packer, you can set up scaling for an app using cloud-native infrastructure.
Using Anypoint Platform, you can develop a full cycle of API applications. Using RAML, you can define your service’s APIs, build an app, and share the API.
Spring Boot, Maven, and Tomcat can form a powerful alliance. This sample web app shows the interplay between them and how you can easily configure them for your needs.
Sibanjan Das offers up a tutorial for building a web-based cluster and prediction analysis application through using R with the open source Shiny framework. Oh yeah, and he embedded the app directly into this DZone article... shine on you crazy data scientist.
For clouds, you have to decide if multi-tenancy and its possible security issues are important to you. $146 billion dollars says multi-tenant app architectures matter.
SonarQube (and the SonarGraph plugin) can automatically scan your code base for cyclic dependencies. Their combined power replaces some lost functionality.
You can customize a Mule caching strategy so that the Mule cache scope actions can operate on the Redis data store. You can also try other third-party caching frameworks.
If you have Redis, Node.js, and the Heroku toolbelt installed on your machine, then you've got everything you need to build a real-time chat application.
