Automate processes helps us to keep pace with business demand with quicker and quality deploys of code, both features and bug fixing.
In this article, I’d like to explore a sample of chain in order to achieve a complete automatic pipeline, from the code check out to the deploy of the package into a dedicate environment.
Continue reading Continuous Delivery with Jenkins + Docker + Git
Writing new code and deploy that to production environment might be the trivial part of the process, especially when you’re engaged to evolve the components without system down or, worse, unexpected troubles when users are connected.
Let’s make this short journey of what has happened to me from my experience.
Continue reading Writing, testing and deploying code in Continuous Delivery
Understanding how messages are processed in a Mule Flow is the first step to build a correct flow suitable for your purpose.
In this article I’m going to illustrate the different ways to model a flow following some base guidelines.
Continue reading Mule – Synchronous and Queued-asynchronous flows
I’ve just finished reading a very well written book about micro services.
From all the things described and illustrated, one of these has drawn my attention for clarity and simplicity.
I rewrote this picture applying the same concept on different case due copyright of the original picture.
In my example, I took a different type of accommodation you can have in your daily life. From own house to Hotel and I applied the same concept on different provider “as a service”.
The difference in not in “What” but in “Who” does what’s done.
Spring Retry project make available to setup a retry policy for that operations which, depending on a large numbers of different reasons, failed.
In this article I showed an easy way to apply this technology including some considerations of the different configuration types.
Continue reading Spring @Retry annotation
Dealing with data streaming is always a challenging task to accomplish. Data that can achieve a big dimension needs a scalable system to avoid sudden failures. Apache Spark “Streaming” cube is a framework library born to deal with streaming process data processing. Let’s have a look at it.
Continue reading Streaming using Apache Spark
A first glance at this powerful platform for distributing data across different node clients in order to improve the scalability of the application which adopts this solution of distributed cache (and not only).
In this post, I’ll show you an example using one features of Apache Geode accessing the data through Spring Data platform.
Continue reading Pivotal GemFire – Apache Geode