Rally provides a framework for performance analysis and benchmarking of individual OpenStack components as well as full production OpenStack cloud deployments
Go to file
Andrey Kurilin c239b13b27 Rework docker build
* put Dockerfile at root level and remove all hooks for autobuilds at
  hub.docker.org
* run the similar wokrload as `tox -e self` using rally docker image
* rewrite workload that is used by `tox -e self` at python
* push docker image at gate pipeline

Change-Id: Iddd4b3ad518dcf46bf9cb1d67e0b161ad1728166
2020-03-21 15:37:33 +02:00
.zuul.d Rework docker build 2020-03-21 15:37:33 +02:00
doc Fix pep8 job according to latest set of rules 2020-01-03 16:14:10 +02:00
etc Rework docker build 2020-03-21 15:37:33 +02:00
rally Rework inner code for JUnit reports 2020-03-03 11:46:59 +00:00
rally-jobs [evil] Remove OpenStack related plugins 2018-06-20 19:01:47 +03:00
samples [evil] Remove OpenStack related plugins 2018-06-20 19:01:47 +03:00
tests Rework docker build 2020-03-21 15:37:33 +02:00
.coveragerc [CI] Fix coverage job 2016-06-27 15:39:13 +03:00
.dockerignore Rework docker build 2020-03-21 15:37:33 +02:00
.gitignore [ci] Start fixing CLI job 2017-10-12 12:13:18 +03:00
.gitreview OpenDev Migration Patch 2019-04-19 19:32:06 +00:00
bindep.txt Rework rally-install-* jobs 2020-02-14 13:44:20 +02:00
CHANGELOG.rst Merge "Ensure python 3.8 is supported" 2020-02-28 10:30:15 +00:00
CONTRIBUTING.rst [docs][6] Re-design docs to cover all user-groups 2017-01-10 11:25:00 -08:00
DOCKER_README.md Rework docker build 2020-03-21 15:37:33 +02:00
Dockerfile Rework docker build 2020-03-21 15:37:33 +02:00
install_rally.sh install_rally.sh: moved zypper pkg manager up to handle case when 2019-06-03 14:43:11 -06:00
LICENSE Initial commit 2013-08-03 09:17:25 -07:00
optional-requirements.txt Fixing docker-check jenkins job 2016-09-20 16:56:00 +03:00
README.rst update git.openstack.org to opendev 2019-04-25 23:59:52 +00:00
requirements.txt Remove six usage 2020-02-21 16:15:31 +02:00
setup.cfg Include min python version at setup.cfg 2020-03-17 15:36:10 +02:00
setup.py Stop checking installation on ubuntu-xenial nodes 2020-03-03 13:45:55 +02:00
test-requirements.txt Add some tests for verify function 2020-03-03 14:36:47 +00:00
tox.ini Rework docker build 2020-03-21 15:37:33 +02:00
upper-constraints.txt Ensure python 3.8 is supported 2020-02-28 09:17:43 +02:00

Rally

Rally is tool & framework that allows one to write simple plugins and combine them in complex tests scenarios that allows to perform all kinds of testing!

Team and repository tags

image

Latest Version

Gitter Chat

Trello Board

Apache License, Version 2.0

What is Rally

Rally is intended to provide a testing framework that is capable to perform specific, complicated and reproducible test cases on real deployment scenarios.

Rally workflow can be visualized by the following diagram:

Rally Architecture

Who Is Using Rally

Who is Using Rally

Documentation

Rally documentation on ReadTheDocs is a perfect place to start learning about Rally. It provides you with an easy and illustrative guidance through this benchmarking tool.

For example, check out the Rally step-by-step tutorial that explains, in a series of lessons, how to explore the power of Rally in benchmarking your OpenStack clouds.

Architecture

In terms of software architecture, Rally is built of 4 main components:

  1. Environment - one of key component in Rally. It manages and stores information about tested platforms. Env manager is using platform plugins to: create, delete, cleanup, check health, obtain information about platforms.
  2. Task component is responsible for executing tests defined in task specs, persisting and reporting results.
  3. Verification component allows to wrap subunit-based testing tools and provide complete tool on top of them with allow to do pre configuration, post cleanup as well process and persist results to Rally DB for future use like reporting and results comparing.

Use Cases

There are 3 major high level Rally Use Cases:

Rally Use Cases

Typical cases where Rally aims to help are:

  • Automate measuring & profiling focused on how new code changes affect the OpenStack performance;

  • Using Rally profiler to detect scaling & performance issues;

  • Investigate how different deployments affect the OS performance:

    • Find the set of suitable OpenStack deployment architectures;
    • Create deployment specifications for different loads (amount of controllers, swift nodes, etc.);
  • Automate the search for hardware best suited for particular OpenStack cloud;

  • Automate the production cloud specification generation:

    • Determine terminal loads for basic cloud operations: VM start & stop, Block Device create/destroy & various OpenStack API methods;
    • Check performance of basic cloud operations in case of different loads.