Category: Software Architect

97 Things Every Software Architect Should Know – 14/97

Application architecture determines application performance. That might seem rather obvious, but real-word experience shows that its not. For example, software architects frequently believe that simply switching from one brand of software infrastructure to another will be sufficient to solve an application‘s performance challenges. Such beliefs may be based on a vendor‘s benchmark trumpeting, say, 25% better performance than the closest competition‘s. But, taken in context, if the vendor‘s product performs an operation in three milliseconds while the competition‘s product takes four milliseconds, the 25% or one-millisecond advantage matters little in the midst of a highly inefficient architecture at the root of an application‘s performance characteristics.

In addition to IT managers and vendor benchmarking teams, other groups of people – vendor support departments, and authors of application performance management literature – recommend simply ?tuning? the software infrastructure, by fiddling with memory allocations, connection pool sizes, thread pool sizes, and the like. But if the deployment of an application is insufficiently architected for the expected load, or if the application‘s functional architecture is too inefficient in its utilization of computing resources, then no amount of ?tuning? will bring about the desired performance and scalability characteristics. Instead a re-architecting of internal logic, or deployment strategy, or both, will be required.

In the end, all vendor products and application architectures are constrained by the same fundamental principles of distributed computing and underlying physics: applications, and the products they use, run as processes on computers of limited capacity, communicating with each other via protocol stacks and links of non-zero latency. Therefore people need to appreciate that application architecture is the primary determinant of application performance and scalability. Those quality attributes cannot be miraculously improved with some silver-bullet switch of software brands, or infrastructure ?tuning?. Instead, improvements in those areas require the hard work of carefully-considered (re-) architecting.

97 Things Every Software Architect Should Know – 13/97

Business users specify their needs primarily through functional requirements. The non-functional aspects of the systems, like performance, resiliency, up-time, support needs, and the like, are the purview of the architect. However, often the preliminary testing of non-functional requirements is left until very late in the development cycle, and is sometimes delegated completely to the operations team. This is a mistake that is made far too often.

The reasons are varied. There is presumably no sense in making something fast and resilient if it doesn’t actually perform the required function. The environments and tests themselves are complex. Perhaps the early versions of the production system will not be as heavily utilized.

However, if you aren’t looking at performance until late in the project cycle, you have lost an incredible amount of information as to when performance changed. If performance is going to be an important architectural and design criterion, then performance testing should begin as soon as possible. If you are using an Agile methodology based on two week iterations, I’d say performance testing should be included in the process no later than the third iteration.

Why is this so important? The biggest reason is that at the very least you know the kinds of changes that made performance fall off a cliff. Instead of having to think about the entire architecture when you encounter performance problems, you can focus on the most recent changes. Doing performance testing early and often provides you with a narrow range of changes on which to focus. In early testing, you may not even try to diagnose performance, but you do have a baseline of performance figures to work from. This trend data provides vital information in diagnosing the source of performance issues and resolving them.

This approach also allows for the architectural and design choices to be validated against the actual performance requirements. Particularly for systems with stringent requirements, early validation is crucial to delivering the system in a timely fashion.

Technical testing is also notoriously difficult to get going. Setting up appropriate environments, generating the proper data sets, and defining the necessary test cases all take a lot of time. By addressing performance testing early you can establish your test environment incrementally avoiding much more expensive efforts once after you discover performance issues.