Quick Guides
  • Free Trial options
  • Quick Guides: Akamas in a sandbox
    • [AIAS-01] Guide: Explore an Optimization Study for a Kubernetes microservices application
      • [AIAS-01] Architecture overview
      • [AIAS-01] Explore the Study
      • [AIAS-01] Explore the System
      • [AIAS-01] Explore the Workflow
      • [AIAS-01] Explore the analysis
      • [AIAS-01] Explore the results
    • [AIAS-02] Guide: Create a study to optimize Java performance using the Akamas UI
      • [AIAS-02] Architecture overview
      • [AIAS-02] Create the Study
      • [AIAS-02] Define the optimization goal
      • [AIAS-02] Define the optimization parameters
      • [AIAS-02] Define the performance metrics
      • [AIAS-02] Define the optimization steps
      • [AIAS-02] Explore the results
    • [AIAS-03] Guide: Create a study to optimize K8s microservices costs using the Akamas CLI
      • [AIAS-03] Architecture overview
      • [AIAS-03] Create the system
      • [AIAS-03] Create the Workflow
      • [AIAS-03] Create the Study
      • [AIAS-03] Explore the results
  • Quick Guides: Akamas in a box
    • [AIAB-00] Install Akamas-in-a-box
      • [AIAB-00] Setup your Linux box
      • [AIAB-00] Install Akamas
    • [AIAB-01] Optimize a Java-based application (Renaissance benchmark)
      • [AIAB-01] Architecture overview
      • [AIAB-01] Create the System and its associated components
      • [AIAB-01] Configure the Telemetry
      • [AIAB-01] Create the workflow
      • [AIAB-01] Create and run the study
      • [AIAB-01] Explore the results
    • [AIAB-02] Optimize a Java-based application (Konakart) with JMeter
      • [AIAB-02] Architecture overview
      • [AIAB-02] Create the system and its components
      • [AIAB-02] Automate performance tests
      • [AIAB-02] Create the Telemetry Provider
      • [AIAB-02] Create the workflow
      • [AIAB-02] Create the study
      • [AIAB-02] Explore the results
    • [AIAB-03] Optimize a Java-based application (Konakart) with LRE
      • [AIAB-03] Architecture overview
      • [AIAB-03] Setup LoadRunner Enterprise
      • [AIAB-03] Create the system and its components
      • [AIAB-03] Create the telemetry instances
      • [AIAB-03] Create the workflow
      • [AIAB-03] Create the optimization study
    • [AIAB-04] Optimize a Java-based Kubernetes application (Online Boutique)
      • [AIAB-04] Architecture overview and setup
      • [AIAB-04] Setup Online Boutique
      • [AIAB-04] Setup Akamas
      • [AIAB-04] Create the system and its components
      • [AIAB-04] Create the workflow
      • [AIAB-04] Create the Study
      • [AIAB-04] Explore the results
Powered by GitBook
On this page

Was this helpful?

Export as PDF
  1. Quick Guides: Akamas in a box
  2. [AIAB-01] Optimize a Java-based application (Renaissance benchmark)

[AIAB-01] Architecture overview

Previous[AIAB-01] Optimize a Java-based application (Renaissance benchmark)Next[AIAB-01] Create the System and its associated components

Last updated 2 years ago

Was this helpful?

In this scenario, the goal is to make Renaissance run faster by optimizing the Java Virtual Machine (JVM) parameters.

The following picture represents the high-level architecture of how Akamas operates in this scenario.

In the following, you will first create a System with two components corresponding to the JVM and the Renaissance application (which only for your first studies is represented by a benchmark). Then you will create a Telemetry Instance from the CVS Telemetry Provider so as to collect metrics generated in CSV format by Renaissance. Finally, you will create a Workflow to automate the whole process of applying a benchmark configuration, launching the benchmark, collecting the resulting metrics. This will allow you to create your optimization Study to identify the optimal configuration.

Before starting, you need to login to Akamas with the following command:

akamas login --user --password