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You're ready to launch a critical Web application. Ensuring good application
performance is crucial, but time is short. How can you optimally test the
application and still meet your deadlines?
Rapid bottleneck identification (RBI) is a new testing methodology that allows
quality assurance (QA) professionals to very quickly uncover Web application
performance limitations and determine the impact of those limitations on the end
user experience. Developed through years of testing engagements across all types
of platforms, the RBI methodology dramatically reduces load testing cycles while
allowing more-and more thorough-testing. Using this approach, organizations
can improve application quality, enhance the customer experience, and lower the
cost of deploying new systems.
PERFORMANCE TESTING DEFINED
Performance testing can be roughly defined as "testing conducted to evaluate the
compliance of a system or component with specified performance requirements."
However, every application has at least one bottleneck, and few, if any, systems
ever meet initial performance requirements. To reflect this reality, let's redefine
performance testing as "testing conducted to isolate and identify the system and
application issues (bottlenecks) that will keep the application from scaling to meet
its performance requirements."
This philosophical shift in perspective-from testing as an evaluation to testing as
an active investigation to isolate and resolve problems-is what drove the creation
of the RBI methodology. RBI combines a comprehensive understanding of
bottlenecks with a refined testing methodology that enables organizations to create
highly scalable Web applications.
Before delving into the specifics of the RBI methodology, we must first establish a
common understanding of bottlenecks-and where they are found-as well as
draw a distinction between throughput and concurrency testing.
Bottlenecks-Key Performance Inhibitors
Any system resource-such as hardware, software, or bandwidth-that places
defining limits on data flow or processing speed creates a bottleneck. In Web
applications, bottlenecks directly affect performance and scalability by limiting the
amount of data throughput or restricting the number of application connections.
These problems occur at all levels of the system architecture, including the
network layer, the Web server, the application server, and the database server.
Historically, based on our experience testing actual customer applications,
bottlenecks have been distributed across these components as shown in Figure 1.
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