Examples of a parameter include:
Configuration knobs (e.g. JVM garbage collection type)
Resource settings (e.g. amount of memory allocated to a Spark job)
Algorithms settings (e.g. learning rate of a neural network)
Architectural properties (e.g. how many caching layers in an enterprise application)
Type of resources (e.g. AWS EC2 instance or EBS volume type)
Any other thing (e.g. amount of sugar in your cookies)
The following table describes the parameter types:
A parameter is described by the following properties:
a name that uniquely identifies the parameter
a description that clarifies the semantics of the parameter
a unit that defines the unit of measurement used by the parameter
Although users can create parameters with any name, we suggest using the naming convention context_parameter where
context refers to the technology or more general environment in which that metric is defined (e.g. elasticsearch, jvm, mysql, spark)
parameter is the parameter name in the original context (e.g. gcType, numberOfExecutors)
This makes it possible to identify parameters more easily and avoid any potential name clash.
Parameters are displayed in the Akamas UI when drilling down to each system component.
For each optimization study, the optimization scope is the set of parameters that Akamas can change to achieve the defined optimization goal.