Recently, I outlined my general performance testing approach in a three part series called "Testing for Performance:" part 1: Assess the problem space, part 2: Build out the test assets, part 3: Provide information. My approach draws heavily from Scott Barber's 13 part series on User Experience Not Metrics and his book (co-authored with J.D. Meier, Carlos Farre, Prashant Bansode, and Dennis Rea) Performance Testing Guidance for Web Applications.
I share these resources first, because I'd approach your question just as I do in that article series: outline a test strategy, understand the system, draft some usage models, and figure out which tests you'll need to address your specific concerns around your distributed environment. Any unique challenges introduced by your distributed environment (a globally disperse user population, a complex physical environment, etc…) would need to be accounted for in your models, environment setup, and your initial test scenarios.
If your environment is your biggest concerns, when you design your tests, start with the assumption that your workload model is correct in regards to what users do, but vary where they do it (geographically) and vary some of your assumptions around the final deployment diagram and how it may change. With some types of changes, you wouldn't expect to see any difference. With other changes you may just be trying to confirm predications of scalability or failover/recovery. Depending on which aspects of your applications you're testing and what your test environments look like, you may need to geographically distribute your load generators, leverage virtual machines or a cloud environment, or look at leveraging test tools with integrated latency simulators.
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