Earlier today I read an interview with fellow IBMer Andrew Spyker that touched on the use of declarative programming models in the new WebSphere XML Feature Pack. I think most of you are probably comfortable with what a declarative programming model is, especially in comparison to imperative programming models, but I really like Andrew’s explanation in the interview:
… declarative programming asks the user what they want to do. This is as opposed to imperative programming (ex: Java code working with the DOM or JAXB APIs) which asks the user how they want to do what they want to do.
Andrew goes on to make the point that not only is code written in the declarative style easier to adapt and maintain over time, it also lends itself to better optimizations. The reason for this is pretty obvious based on his definition above. Code written in the imperative style explicitly tells the computer how to do what the user wants to do. While some optimizations to this code can be, and often times are, inserted by a compiler, it doesn’t lend itself to the same optimizations that code written in a declarative style does. When coders simply tell a system what they want to do, as is the case in the declarative style, the system can decide the most efficient way to carry out that action.
While not the focus of the interview, Andrew does mention that declarative programming models may be particularly useful in the realm of cloud computing. I believe that line of thought has quite a bit of merit. As far as application environments go, most of the cloud computing movement to date has been centered on driving efficiencies through the use of virtualizing complete application stacks. This provides us with the necessary encapsulation to be able to very easily and quickly bring complete stacks online, all the while allowing us to run more of those stacks, with the same set of compute resources, when demand dictates.
There is no doubt that this type of virtualization is a good thing and when leveraged correctly can bring significant improvement with respect to the responsiveness of our applications. However, we can’t stop by putting a box around our application stacks. If we truly want to get the most out of the dynamic environments offered by cloud computing platforms, we have to look inside that stack as well to drive efficiencies into the code that makes up our applications.
What’s the best way to do that? Well, the fact is that right now the community of developers who are well prepared to write code that harnesses the power of massive, highly scalable cloud platforms isn’t exactly bursting at the seams. To address that many initiatives are being launched that seek to make these type of programming skills part of core computer science curriculums in colleges and universities across the world. While I do not at all dispute the fact that those initiatives are necessary and valuable, I also can’t help but wonder if that’s the best and only way.
What if we focused more on the use of declarative programming models as the style of choice when writing applications deployed on cloud environments? In this way developers write applications that tell the cloud platform what they want to do and it’s up to that platform to decide exactly how to do it. This approach means that developers do not need deep knowledge on how to best harness the often times massive and complex underlying infrastructure of a cloud platform to meet their needs. Instead the cloud platform makes decisions, being presumably much more equipped to do so, about how to most efficiently take the action the user is requesting.
To me this approach is a win-win for developers and cloud platform providers. Obviously developers can get back to focusing on the business logic they are trying to provide, and cloud platform providers have more control over exactly how its resources are leveraged which can only help in terms of meeting user demands and SLAs. I acknowledge that declarative programming techniques will also be a new set of skills for some developers, but to me this seems more easily achieved than learning how to best use complex cloud environments within application code. I say we put the burden for leveraging massive compute resources squarely on the shoulders of the cloud platforms.