According to a recent survey, available skill sets is one of the leading decision factors for organizations in determining which application platform to use, while scalability and availability are next. This reveals one of the main obstacles for bringing enterprise applications to the cloud: How do you take something as disruptive as cloud computing, and bring it to an enterprise environment, without forcing a complete re-write?
In my recent talk at the CloudSlam (online) Conference, I tried to summarize the challenges people face when trying to deploy enterprise applications on the cloud. Try to imagine a scenario where you have an existing JEE system, and your system is under load. At this point you would like to add more machines to accommodate that load. What will happen to your application in this case? Will your application be able to take advantage of the additional capacity? How do you know how many machines should be added to meet the load in the first place?
The answers I usually hear to these questions are fairly consistent. If you’re lucky, you’ll only require configuration changes to be at a point where you can utilize the extra resources. Knowing how many machines to add in order to meet a certain load is yet another challenge. Going through the normal capacity planning process could take weeks with the way systems are currently running.
At the same time, if you’re going to deploy our application in a static manner (reserved instances, static IP, …), it would probably make it simpler to deploy your existing application on the cloud, but it probably won’t make much economical sense. So the question I was trying to answer is how we get from the static application deployment most of us are using today, to a point where we can get end-to-end scaling and elasticity of our application from the load-balancer to the database without going through a complete re-write.
In this presentation, I tried to suggest a set of solutions to overcome the various challenges I mentioned earlier and how to apply them in a gradual manner to avoid huge initial investments and high risk. There were also some interesting questions toward the end, centered specifically around one of the hardest problems – getting the data pieces sorted out in a such a dynamic environment. Those who missed this presentation can now view it online:
Note: The voice quality isn’t that great, plus the desktop sharing on Webex didn’t give a clear indication when my desktop was actually shared, so the beginning of the talk is missing the first two or three slides. If you have questions or want to get a copy of the presentation, just shoot me an email.
During the upcoming JavaOne conference there will a hands-on lab session by 
Daniel Templeton from Sun Microsystems (PetClinic in the Clouds: Scaling a Classic Enterprise Application) where users can go through the steps and deploy a Pet Clinic application on the cloud.
In addition to that lab, I’m going to have a Technical Session (Alternative to Google Application Engine for Java™ Technology-Based Applications).
For those that are not going to join the JavaOne event and want to get some hands-on experience on how the steps that i outlined in the presentation can be implemented in real application, I’d recommend looking Pet Clinic demo that is available on Amazon cloud using our cloud framework.
I’m happy to say that the number of customers that are already using this approach through our Enterprise Cloud middleware platform is growing quickly and were seeing more and more application that would traditionally considered as not “cloud compatible”, being deployed on the cloud. Below are few of the public references that were mentioned just recently on Jim Liddle‘s blog:
- Telco application running on Amazon EC2 and GigaSpaces
- Using GigaSpaces to Trade in the EC2 Cloud
