Archive for the ‘strategy’ Tag

Dimensions of Scalability

Designing for scalability is one of the primary challenges of system and software architecture.  For those of us who practice architecture, it’s also great fun thanks the high number of variables involved, the creativity required to discover exploits, the pattern matching to apply tricks and avoid traps, and the necessity to visualize the system in multiple possible futures.

In the broadest terms, “Is it scalable?” = “Will it break under growth?”  A few manifestations that are a bit more useful include “Will performance hold up as we add more users?”, “Will transaction processing time stay flat as the database grows?”, and “Will batch processing still complete within the allotted window as the size of our account base, data warehouse, or whatever multiplies?”.  Architects imagine the kinds of demand parameters that might occur over the life cycle of the system and incorporate mitigation plans.

These examples all pertain to the performance characteristics of a system.  However, there are other dimensions of scalability that are equally important when considering that system in a business context.

Strategic Dimensions

  1. Performance Scalability:  “An observation about the trend in performance in response to increasing demands.”
    Demand can refer to any of several parameters depending on the system such as number of concurrent users, transactions rates, database size, etc.  Performance measures may include event processing time, batch throughput, user perception, and many others.  In any case, we consider a system to be scalable if we observe a flat or nearly flat performance curve (i.e., little or no performance degradation) as any given demand parameter rises.  In reality, even highly scalable systems tend to be scalable through some finite range of demand beyond which some resource tends to become constrained causing degradation.
  2. Operational Scalability:  “An observation about the trend in effort or risk required to maintain performance in response to increasing demands.”
    This may be best illustrated by example. Consider a web application that is experiencing sharp increases in usage and a mid-tier performance bottleneck as a result.  If the application was designed for mid-tier concurrency, the mitigation effort may be simply adding more application servers (i.e., low effort, low risk).  If not, then significant portions of the application may need to be redesigned and rebuilt (i.e., high effort, high risk).  The former case is operationally scalable.  As with performance scalability, operational scalability occurs in finite ranges.  Continuing the previous example, at some point the database may become the bottleneck typically requiring more extensive remedial action.
  3. Economic Scalability:  “An observation about the trend in cost required to maintain performance in response to increasing demands.”
    We consider a system to be economically scalable if the cost of maintaining its performance, reliability, or other characteristics increases slowly (ideally not at all, but keep dreaming) as compared with increasing loads.  The former types of scalability contribute here.  For example, squeezing maximum performance out of each server means buying fewer servers (i.e., performance scalability) and adding new servers when necessary is cheaper than redeveloping applications (i.e., operational scalability).  However, other independent cost factors can swing things including commodity vs. specialty hardware, open source vs. proprietary software licenses, levels of support contracts, levels of redundancy for fault tolerance, and the complexity of developmental software which impacts testing, maintenance, and release costs.

Rocky Roads

Since the underlying theme of these additional dimensions is business context, it should be noted that rarely does an architect get to mitigate all imaginable scalability risks.  Usually this is simple economics.  In the early days of an application, for example, the focus is functionality without which million-user performance may never get to be an issue.  Furthermore, until its particular financial model is proven, excessive spending on scalability may be premature.

However, a good technology roadmap should project forward to anticipate as many scale factors as possible and have its vision corrected periodically.  Scalability almost always comes down to architecture and an architectural change which is usually pervasive by definition is the last thing you want to treat at a hot-fix.

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