MFAT = "Multiple Factors at a Time" OFAT = "One Factor at a Time"
In the field of Design of Experiments, practitioners in a large variety of fields (including software testing) have found that an approach that varies multiple factors at a time in each test case is often preferable to an OFAT approach. This is because, MFAT approaches are often much more efficient (e.g., actionable information is revealed in fewer experiments), and effective (e.g., more complete information is revealed).
I'm aware of many examples of MFAT approaches (like pairwise) being used successfully in functional software testing but have not seen many examples in performance testing. There may well be tons of examples but I'm relatively experienced with performance testing.
I'm seeking specific examples of where MFAT approaches have been successfully used in performance testing. I've found articles and blog posts where people advocate MFAT approaches be used in performance testing (in addition to OFAT approaches), but I'm asking this question because I'm seeking first-hand experience reports and/or experience-based advice for when it might be especially important to test for possible interactions between different performance testing variables.
The image shown below is from Ben Simo's blog post encouraging performance testers to use run MFAT tests in addition to running OFAT tests. Do you follow this advice when doing performance tests? If so, has it been useful? If not, why do you feel an OFAT approach is sufficient?