SOA is Dead? Really?

These days the popular topic among a set of the community is whether to find out whether SOA is dead or not? I think it started with Anne's blog. So SOA is dead?

I think its all about what you need. Since I don't want to define SOA my own way and make it partial, I'm gonna use what wikipedia says is SOA. "... Such an architecture will package functionality as interoperable services ...". Aren't we still doing this? Within industry or within research world, how many times we have to interact with external services and how many times we have to expose our interfaces to external parties. Also aren't we still making them services so that they reusable, loosly-coupled, encapsulated, etc., Aren't we stil doing that? I think people are still happy with it. Irrespective of whether you expose your services as Web services or REST, the architecture still works very well.

Let me take an example from the academic. In an academic setting LEAD infrastructure for eScience is solely based on SOA. It is considered as one of the pioneeting research applications using SOA and it still works very well. Not only it works, there are lot more continuations to this project applying same concepts to other scientific domains.

Let me go back to wikipedia article. If we look at the principles section, we still use and believe in reuse, standard compliance, monitoring, encapsulation, loose-coupling, abstraction, etc.,
We still desgin our systems using these principles and independent clients still like and consume our services because we adhere to these principles, so is SOA is really dead?

I agree service discovery failed at Web services world with UDDI, but it doesn't mean SOA as a whole failed.

Now let's remove the hype. Just like other arguments where we debated on WS-* vs Rest, Best ESB, this is somewhat depends on the motives of the companies. Think of it as this way. Being there for a long time, most companies know what SOA means and they use it. Consulting companies need some new thing or some set of buzz words to sell. So they gonna first kill what people know and then come up with something else. So its our responsibility is to listen to these arguments very well and decide what is best for us, rather than spending lot more money especially in this bad economy :)

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Scientific Applications and EC2 (or any other commercial IaaS provider)

Ian Foster makes a very good point about Ed Walker's article on comparing the executions of HPC applications onEC2 and super computers. Echoing his ideas, yes super computers can be faster compared to a cluster on EC2 only on the execution times. But if we take the total time, including queue time etc., then EC2 can compete with super computers. I totally agree.

But there are few more points I'd like to mention here.

The NAS benchmark Ed uses contains HPC applications implemented using OpenMP and most of the applications in this benchmarks utilizes the fast inter connects of the nodes in super computers. So I don't think its fare to compare the execution times within a HPC cluster to EC2, which I believe doesn't have fast inter-connects or powerfull computers.

Also there are lot more scientific applications that doesn't need or use fast inter-connets. There are quite a number of apps, like in fusion simulation, fluid dynamics, weather simulations, etc which are written using MPI. But thats not it. There are thousands of scientists around the world using their desktops or less than 10 nodes clusters consisting of commodity computers running their applications. They don't need super-computers to run their scientific experiments

Not only that. There are lots of programs that are embarassingly parallel and use MapReduce like programming model to implement them. Take Google's massive data mining programs for an example. They also don't necessarily need fast interconnects or best computers to run them, still they are good enough to work with real time.

So its very important to udnerstand that scientific applications are not always HPC apps.

How many scientists will have access to Grid resources and how many of those who has access to grids will get the chance to use it as and when they need it. For example, if a scientist has a paper deadline and needs to run thousand jobs, he can either submit all his thousand jobs to grid and wait till they are done, or if he has money, he can create few clusters on demand on EC2, divide his jobs among these jobs clusters and get his work done.

We can not simply put down on-demand IaaS resources saying they are not suitable for science. I think what we need is better scheduling algorithms which can schedule both on to grid, local and IaaS resources taking user requirements and different parameters like total execution times in to account.

(One more note. Ian mentions in his blog "before we conclude that EC2 is no good for science", I think he must have meant about HPC applications and not science apps in general)

See also my other post on a similar topic.

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Road Trip to Bloomington, IN from Redmond, WA - Summary

Since I drove to Redmond, obviously I had to drove back to Bloomington. This time I really wanted to go and visit Grand Canyon and Arches National Park. So we had to go south and then head east.

Summary

Total Distance : 3544 miles (including drive within Grand Canyon and Arches National Park)

Time: 8 days (with total driving time of about 45hrs)

Fuel Consumption :

Total Gallons : 122.754

Average Gas Price $2.705507 (lowest in Denver,CO $2.49, highest in Mexican Hat, UT $2.94)

Maximum Speed : 80mph + allowance (which I’m not gonna mention here ;) )

Driving Experience :

Best area to drive : Highway 89 from Kanab, UT to Page, AZ. Again this was just like driving as in Need-for-Speed III with the same scenes and narrow and winding roads through canyons.

Worst area to drive : From Cuba City, AZ to Mexican Hat, UT through Monument Valley. I was driving in the dark night at 70mph with lots of "Cows open range" and " Deer Crossing" signs. No one was driving on the same direction and it was only me.

Places visited : Shoshone Falls, Lake Powell, Grand Canyon, Arches National Park, Mexican Hat, Botanical Garden in St. Louis, MO.

Map

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