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Six
key steps to load testing |
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Whether it's a whole new site design, a new Content Management System, an on-line shop upgrading to use Verified-by-Visa, or simply looking ahead to traffic peaks, risk reduction is important. So what forward planning will a Web Manager need to adopt to address the 'Will it Work?' question? News headlines like those resulting from this year's Glastonbury Festival ticket fiasco, continually reinforce the pitfalls that occur when a system is unable to cope with peak loads. This media attention plus the assumption that a new system will work for a single-user often leads organisations to implement Stress/Load Testing alone to see if a site can cope with real usage levels. This assumption often stems from programmers testing as they go along; which isn't the same as covering the entire functional space. Prior to stress/load testing, a full Functional Test/User Acceptance Test should be the starting point for any new project testing process. Following functional testing a system requires modelling and several preparatory stages before stress/load testing can begin. Modelling your systemWhen modelling website usage patterns average traffic figures are of little use. At its simplest, you need to identify from your web logs the peak traffic levels on the site. 24,000 hits a day doesn't mean 1,000 hits every hour. Find traffic levels during the busiest hour. Then use the average number
of pages per visitor to calculate equivalent pages per hour, and work
out the 'worst case number' of concurrent users on the site: for example,
360 visits per hour, at 10 pages per visit = 3600 pages per hour =1 page
per second. So here are the six stages we advise you to adopt for stress/load testing: 1. Identify 'User Journeys' 2. Build 'User Journey' scripts 3. Run scripts in single-user mode 4. Identify system flaws 5. Find bandwidth limitations 6. Run tests under load As the traffic volumes increase, and the performance of different User Journeys begins to decline, the test cases planned evolve to drill deeper and identify likely root causes. New test scripts are written to further expose the problem causes, and to rule out alternative explanations. Test team experience and expertise is vital here; as is a flexible and powerful test engine that can smoothly construct new test cases on the fly, and rapidly correlate data across a number of different runs and user journeys. Never approach testing with preconceived assumptions about potential
problems. In SciVisum's experience it's common for a team to have concerns
about a specific issue as their 'prime suspect' - but when testing begins
and real 'evidence' is produced, these may be shown to be wrong. The real
bottlenecks will be discernible and unambiguous from analysis of the test
data. It's sometimes a shock to find that perhaps the ISP is not the bottleneck
after all, and what's causing the problem is actually an element in the
application design.
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