ABSTRACT

This chapter proposes performability as the over-arching aspect of enterprise architecture. The chapter discusses aspects of response time and how it can be managed either by managing the demand of resources or the resources themselves. Much of the processes or tasks involved in computational work is serial, and in such cases, the final performance of the computational work will depend on the performance of the elements in the execution chain. Some work can, of course, be run in parallel, such as scientific programs or parallel data paths provided to speed up data transmission or storage I/O, but for performance planning and capacity work, it is wise to take the worst case of everything operating serially and not in parallel. The latter half of the chapter focuses on frameworks for evaluation of performance. It describes several techniques and methods for evaluating performance like Rate-Monotonic Analysis (RMA), Performance Assessment of Software Architectures (PASA), Layered Queuing Network (LQN) modeling, Colored Petri Nets (CPN), Architecture Trade-off Analysis Method (ATAM) and so on. The chapter’s appendix discusses queuing systems that are essential pre-requisite to enable the digital transformation. Analytical queuing models offer powerful means for understanding and evaluating queuing processes. However, the use of these analytical models is somewhat restricted by their underlying assumptions. The limitations pertain to the structure of the queuing system, the way variability can be incorporated into the models, and the focus on steady-state analysis. Because many business processes are cross-functional and characterized by complex structures and variability patterns, a more flexible modeling tool is needed. Simulation, discussed in the latter half of this chapter, offers this flexibility and represents a powerful approach for analysis and quantitative evaluation of business processes.