Tsung is a multi-protocol distributed load testing tool.
It can be used to test the scalability and performances of IP based client/server applications (supported protocols: HTTP, WebDAV, SOAP, PostgreSQL, MySQL, LDAP, MQTT, AMQP and Jabber/XMPP).
It can simulate a huge number of simultaneous user from a single machine; moreover, you can distribute the users on cluster for machines. When used on cluster, you can generate a really impressive load on a server with a modest cluster, easy to set-up and to maintain. You can also use Tsung on a cloud like EC2.
This is free and open source software.
Features include:
- High Performance: Tsung can simulate a huge number of simultaneous users per physical computer: It can simulates thousands of users on a single CPU (Note: a simulated user is not always active: it can be idle during a thinktime period). Traditional injection tools can hardly go further than a few hundreds (Hint: if all you want to do is requesting a single URL in a loop, use ab; but if you want to build complex scenarios with extended reports, Tsung is for you).
- Distributed: the load can be distributed on a cluster of client machines
- Multi-Protocols using a plug-in system: HTTP (both standard web traffic and SOAP), WebDAV, Jabber/XMPP and PostgreSQL are currently supported. LDAP and MySQL plugins were first included in the 1.3.0 release.
- SSL support
- Several IP addresses can be used on a single machine using the underlying OS IP Aliasing
OS monitoring (CPU, memory and network traffic) using Erlang agents on remote servers or SNMP - XML configuration system: complex user’s scenarios are written in XML. Scenarios can be written with a simple browser using the Tsung recorder (HTTP and PostgreSQL only).
Dynamic scenarios: You can get dynamic data from the server under load (without writing any code) and re-inject it in subsequent requests. You can also loop, restart or stop a session when a string (or regexp) matches the server response. - Mixed behaviours: several sessions can be used to simulate different type of users during the same benchmark. You can define the proportion of the various behaviours in the benchmark scenario.
- Stochastic processes: in order to generate a realistic traffic, user thinktimes and the arrival rate can be randomized using a probability distribution (currently exponential)
Website: github.com/processone/tsung
Support:
Developer: Nicolas Niclausse and contributors
License: GNU General Public License v2.0
Tsung is written in Erlang. Learn Erlang with our recommended free books and free tutorials.
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