Sometimes, claims call the same service for the same information over and over again. This behavior is called chattiness. Caching can help us optimize this chattiness.
If you're working on a small project or don't have the funds to pay for an automated bug tracking solution, you can create your own bug tracker in your JS source code.
Using Spring Data with Cassandra 3 extends Spring's power into more NoSQL. This detailed tutorial includes setting up Apache Cassandra and some basic interactions.
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.
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.
Chatbots continue to work their way into ever-more solutions, but how should we evaluate their effectiveness? In this post we take a look at a potential framework for doing just that.
Data-driven testing facilitates test procedures, demonstrates more capability in discovering bugs, and ensures quality with logical input to assure successful deployment.
Nulls and the dreaded NPE can be awful, but by maintaining encapsulation, keeping your code simple, and using nulls only in certain situations, you can come out on top.
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.
