Tag Archives: Design

Message Oriented Middleware

In last post I talked about what is middleware, I will focus on message implementation of same today. Message oriented middleware or MOM mostly uses message queues to send and receive data between two systems.

In simple terms, a message is anything that is being sent from one system to another. Mostly MOM uses XML formats, sometimes SOAP based requests or plain texts. An example MOM system will send message to a  message queue or MQ, from where the receiver will pick up the message.

Advantages of Message Oriented Middleware

  1. Persistence: In normal client-server architecture, we will need to make sure both the systems to be available to have a successful communication. Whereas if we are using MQs, one system can still send messages even if the second is down.
  2. Support for Synchronous and Asynchronous communication: by default the communication is asynchronous but we can implement a synchronous system where a request message sender will wait for the response from other party.
  3. Messages can be consumed at will: If one system is busy when messages are received (which do not need immediate response), it can consume the messages when load is less. For example, a lot of systems are designed to consume the messages at non business hours.
  4. Reliability: As messages are persistent, threat of losing information is low even if one or more systems are not available. Additional security mechanism can be implemented in MQ layer.
  5. Decoupling of systems: Both client and server work independently, and often do not have knowledge for other end. System A creates a message and adds to message queue, without concerning who will pick it up as long as it gets the response message (if required). So one system can be written in Java and other can be in Dot Net.
  6. Scalability: As both machines involved in interaction are independent of each other, it is easier to add resources at either end without impacting the whole system.
  7. Group communication: Sender can send message to multiple queues or same queue can have multiple listeners. In addition Publisher- Subscriber approach can help broadcast a message.

Types of Messaging:

Point to Point: This is a simple messaging architecture where a sender will directly send a message to receiver through message queue.

Publisher-Subscriber (Pub-Sub): This type of communication is required when sender wants to send messages to multiple receivers. Topics are defined to which subscriber can subscribe and receive requests based on same. For example, say a core banking system can trigger messages on various events like new account open, a withdrawal is made, interest rate changed etc. For an event, multiple other systems might want that information to take an action, so say for all withdrawal events, systems like fraud detection, mobile messaging system, daily reporting system, account maintenance system subscribe. Whenever, publisher publishes the message to “Withdrawal” topic, all of these systems will receive the message and take appropriate action.

Understanding Open/Closed Principle

Open closed principle is an important rule in software design, which we need to follow when designing a software system. It states “A Software code should be open for extension but closed for modification”.

What does that mean? Let’s take a very simple example from day to day life. We all use TV remotes. Say, we have created a very simple software code for remote operations like on/ off, vol increase/ decrease, channel change etc. Now what should be my design considerations

1. Any one should be able to extend the code to add new functionality, for example, for advanced TV’s one should be able to add functionality for subtitle language selection, operator specific options etc.
2. At the same time I need to make sure that no one should be able to alter existing core functionality like vol increase/ decrease, so that it does not break down the functions which are working fine perfectly.

Point 1 is what we say open for extension and point 2 states closed for modification principle. The open/ closed principle helps maintainability of code perfectly, by making sure we do not break what is working fine with flexibility of adding new features at the same time.

Implementing Scalability

These days there is a lot of buzz around the word ‘scalability’ in IT world. The concept is actually not new, I have been designing scalable systems for last 9 years, but the idea has definitely changed since then.

How meaning of scalability has changed in last few years?

If 5-6 years back, I was creating a system to support say 10K users, and someone would have told me to make it scalable, I would have thought of making the system it in such a way that it can support double or may be 4 times or max 10 times the users in next 3-4 years. But with the applications like facebook, amazon, ebay, twitter the idea about scalable system is different. Now the user base can increase exponentially in matter weeks. And that is what every organization wants.

What is the impact of change?

Impact of the change is that  now you do not want a system which will need a good amount of change if your user base is increasing. Earlier, as number of users used to grow slowly, it will give you time to think, design, redesign, upgrade the system, but now, as user base can increase with much more speed, you want a system which can scale up within minutes and it should be able to it automatically.

How to achieve scalability in today’s world?

As the demand has changed, so has technology. Cloud computing has made it much easier for us to create scalable systems. Key component choices to be made while creating a scalable solution

1. Design: Design of application/ code should be able to handle infinite load.

2. Database: If you are expecting your data load to grow beyond a few million, you might want to go for NOSQL over RDBMS.

3. Hardware: you should be able to add in new hardware and replicate the application on new servers within minutes. Cloud system can help you here.

4. Load balancing: If our application is getting distributed/replicated over multiple servers, we will need to take care of load balancing so that no server will choke.