Optimization Insights
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While the main result of an optimization study is to identify the optimal configuration with respect to the defined goal & constraints, any suboptimal configuration that is improving on one of the defined KPIs can be also very valuable.
These configurations are displayed in a dedicated section of the Akamas UI and also displayed in other areas of the Akamas UI as textual badges "Best <KPI name>" referred to as (insights) tags.
The following figures show the Insights section displayed on the study page and the Insights pages that can be drilled down to.
The following figure shows the insights tags in the Analysis tab:
Please notice that "Best", "Best Memory Limit" and any other KPI-related tags are displayed in the Akamas UI while the study progresses and thus may be reassigned as new experiments get executed and their configurations are scored and provide their results for the defined study KPIs. See
After starting a study, any finished experiment is labeled by one or more insights tags "Best <KPI name>" in case the corresponding configuration provides the best result so far for those KPIs. Notice that for experiments involving multiple trials, tags are only assigned after all their trials have finished.
Of course, after the very first experiment (i.e. a baseline) finishes, all tags are assigned to the corresponding configuration. This is displayed by the following figure for a study where the KPIs named CPU with formula renaissance.cpu_used and direction minimize and MEM with formula renaissance.mem_used and direction minimize:
When the following experiments finish, tags are reevaluated according with respect to the computed goal score and the achieved results for any single KPI. In this study, experiment #2 provided a better result for both the CPU and the study goal, so it got both the tags Best CPU and Best renaissance.response_time(which is defined as the goal of the study). Notice that the blue star is displayed by Akamas (except for baseline) to highlight the fact that this was automatically generated by Akamas and not assigned by a user.
Afterward, experiment #3 got the tag as the best configuration while experiment #4 got the tag Best CPU. as improving on experiment #2. Therefore two configurations displayed the blue star.
A number of experiments later, experiment #7 provided better memory usage than the baseline so got the tag Best MEM assigned. At this point, three configurations have the blue start, thus making evident that there are tradeoffs when trying to optimize with respect to the goal and the KPIs.
