Showing posts from 2015

Microservices using Pivotal Cloud Foundry

Have you ever faced the following issues in your projects: 1. Roll out features quickly to production: The customer needs very minor changes to functionality/UI and would like that to be rolled out at the earliest, because they have a higher business impact. However, we are not able to deliver it, because though it is a small change, we have to go through the whole nine yards of release processes involving full regression etc.  2. Move your application from one datacenter to another: You need to move your application to a different data center in a different geography due to various reasons (like legal, merger and acquisition etc). This might seem to be a herculean task to you. More often than not, you would get caught in a web of discovering (often surprising yourself!), a myriad of system configurations spread across file system, database, even worse within the code!!!. This is only going to make your task even more daunting. 3. Scale out your application based on modules:

Map Reduce Explained

In this post, I'm going to write about Map Reduce Algorithm.  Map Reduce has taken the computing world by storm in recent years. It's massive scalability has given an edge to solving complicated problems. Map Reduce is often explained by the famous counting example (word count more often than not). I would also take the same route, albeit, a different example., let us count the number of books with the same name. Example: Suppose, there are 3 book shelves and each of them have different books. For brevity, let us say there are 4 different books in each of these shelves. First Shelf: "Harry Potter and the Half-Blood Prince" (count: 3) "The Da Vinci Code" (count: 1) "Think and Grow Rich" (count: 2) "The Bridges of Madison County" (count: 2) Second Shelf: "Harry Potter and the Half-Blood Prince" (count: 2) "The Da Vinci Code" (count: 2) "Think and Grow Rich" (count: 3) "The Bridges

Spring Integration - Bulk processing Example

In this post, I'm going to share my experience in using Spring Integration for a bulk processing task. This was the first time I was using Spring Integration and it did not disappoint me. It was pretty robust in terms of error handling and definitely scalable. Disclaimer: The actual task being performed has been modified into a fictitious e – commerce domain task, since I cannot reveal the original task which is customer specific and confidential. However, the nature of the task in terms of processing of clob and xml remain the same and the complexity of the original task has been retained. Also, the views posted on this post are strictly personal. Objective: The objective is to work upon customer information from an ecommerce application and process it and save it into database as clob data. The task is to perform data processing by reading xml from a file in the file system and then store it as clob into a table. Following is the high level of tasks required t