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1.3 Examples of Issues Addressed by Performance Engineering Methods

Apart from mitigating business risk, performance engineering methods assist in answering a variety of questions about a software system. The performance engineer must frequently address questions related to capacity. For example:

  • Can the system carry the peak load? The answer to this question depends on whether the system is adequately sized, and on whether its components can interact gracefully under load.
  • Will the system cope with a surge in load and continue to function properly when the surge abates? This question is related to the reliability of the system. We do not want it to crash when it is most needed.
  • What will be the performance impacts of adding new functionality to a system? To answer this question, we need to understand the extra work associated with each invocation of the functionality, and how often that functionality is invoked. We also need to consider whether the new functionality will adversely affect the performance of the system in its present form.
  • Will the system be able to carry an increase in load? To answer this question, we must first ask whether there are enough resources to allow the system to perform at its current level.
  • What is the performance impact of increasing the size of the user base? Answering this question entails understanding the memory and secondary storage footprints per user as well as in total, and then being able to quantify the increased demand for memory, processing power, I/O, and network bandwidth.
  • Can the system meet customer expectations or engineering needs if the average response time requirement is 2 seconds rather than 1 second? If so, it might be possible to build the system at a lower cost or with a simpler architecture. On the other hand, the choice of a simpler architecture could adversely affect the ability to scale up the offered load later, while still maintaining the response time requirement.
  • Can the system provide the required performance with a cost-effective configuration? If it cannot, it will not fare well in the marketplace.

Performance can have an effect on the system’s functionality, or its perceived functionality. If the system does not respond to an action before there is a timeout, it may be declared unresponsive or down if timeouts occur in a sufficiently large number of consecutive attempts at the action.

The performance measures of healthy systems tend to behave in a predictable manner. Deviations from predictable performance are signs of potential problems. Trends or wild oscillations in the performance measurements may indicate that the system is unstable or that a crash will shortly occur. For example, steadily increasing memory occupancy indicates a leak that could bring the system down, while oscillating CPU utilization and average response times may indicate that the system is repeatedly entering deadlock and timing out.

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