In this section you will be creating a study by using the creation wizard provided by Akamas.
The target application to optimize is Renaissance, a sample Java benchmark that comes already shipped with the Akamas-in-a-box installation. Your goal will be to make Renaissance consume less CPU and memory, a common optimization need for Java applications.
The study you will create needs to have the following properties:
renaissance.mem_used) would be a typical goal; another goal would be reducing the CPU usage of a Java application (that is minimizing the
The following picture represents the high-level architecture of how Akamas operates in this scenario.
To create the study, go to the Study menu in the UI and click on the Create button, then select Study:
The study creation wizard will now walk you through the different steps required to create the study.
First of all, choose a name and description for your study, then select the renaissance system and the renaissance-optimize workflow:
The next step is to define your optimization goal.
MINIMIZE option and select
cpu_used) metric from the renaissance component for the goal of reducing memory usage (or CPU consumption). Make sure that the metric you are selecting belongs to the proper (i.e.
renaissance) component of your system.
It's now time to select which parameters Akamas needs to tune in this study.
To start, you can include the following JVM parameters (by also setting the range for some of them):
Akamas supports constraints among parameters to avoid incorrect combinations of values. In this example, the JVM newSize parameter needs to be lower or equal to maxHeapSize. You can add a new constraint to tell Akamas to keep this relation into consideration during the optimization:
Now, you can select the metrics of interest among all the metrics provided by your components. You can do that by expanding the Choose metrics section and select all the metrics of the
Finally, you can define the steps the study will go through.
Typically, an Akamas study is composed of:
baselinestep, which is used to assess the system performance in the initial configuration (e.g. the settings currently in place for your system)
optimizestep, which is used to execute the actual AI-driven performance optimization
The Akamas study wizard already creates these two steps for you, so unless you want to add additional steps you just need to configure these two steps.
In this study, we simply configure the baseline configuration by setting
jvm_maxHeapSize to 1024M:
Then click on the Optimize step in the left panel to specify the optimization configuration.
For now, simply set the number of experiments to execute to 30:
Now click on Create Study.
You have now created your first study and you ready to start the optimziation!
You can review your study in the Definition tab or go and launch the study by pressing the Start button:
After running the study, you can explore the results your AI-driven performance optimization study.
Select your study from the UI Study menu.
The Summary tab displays high-level study information at a glance, including the best score obtained so far, a summary of the tuned parameters and their values for the optimal configuration (so far if the study is still running).
The Progress tab allows to follow the experiments and their workflow tasks execution (including logs for troubleshooting).
The Analysis tab shows the experiments score over time, plus a detailed table with key parameters and metrics for each experiment.
The Configuration Analysis tab lets you explore the additional insights and benefits of the configurations Akamas explored with respect to other key metrics besides the goal.
The Metrics tab allows you to check the metrics that the telemetry modules collected over time for each experiment.
You have just learned how to create a study using the Akamas wizard!
As a following step you may want:
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