Optimization Study

An optimization study (or study for short) represents an optimization initiative aimed at optimizing a goal on a target system. A study instructs Akamas about the space to explore and the KPIs used to evaluate whether a con configuration is good or bad

Akamas supports two types of optimizations:

  • Offline Optimization Studies are optimization studies where the workload is simulated by leveraging a load-testing tool.

  • Live Optimization Studies are applied to systems that need to be optimized in production with respect to varying workloads observed while running live. For example, a microservices application can be optimized live by having Kubernetes and JVM parameters dynamically tuned for multiple microservices so as to minimize costs while matching response time objectives.


A study is described by the following properties

  • system: the system under optimization

  • parameters: the set of parameters being optimized

  • metrics: the set of metrics to be collected

  • workflow: the workflow describing tasks to perform experiments/trials

  • goal: the desired optimization goal to be achieved

  • constraints: the optimization constraints that any configuration needs to satisfy

  • steps: the steps that are executed to run specific configurations (e.g. the baseline) and run the optimization

The construct to be used to define an optimization is described on the Study template page.


An optimization study is an Akamas resource that can be managed via CLI using the resource management commands.

User Interface

The Akamas UI shows optimization studies in 2 specific top-level menus: one for offline optimization studies and another for live optimization studies.

Last updated