Expressive, scalable load testing tool
MZBench helps software developers benchmark and stress test their products. Testing of your product with MZBench before going to production may reduce the risk of outages under real life highload.
MZBench runs test scenarios on many machines simultaneously, maintaining millions of connections, which makes it suitable even for large scale products.
MZBench is:
- Cloud-aware: MZBench can allocates nodes directly from Amazon EC2 or run on a local machine.
- Scalable: tested with 100 nodes and millions of connections.
- Extendable: write your own cloud plugins and workers.
- Open-source: MZBench is released under the BSD license.
Out-of-the-box it supports HTTP, MySQL, PostgreSQL, MongoDB, Cassandra, XMPP, AMQP, TCP, Shell commands execution, Simplified HTTP, and TCPKali.
Implementing addtional protocols is not that hard, but if you want something particular to be implemented — feel free to create an issue.
Available for CentOS 7 and Amazon Linux.
Download MZBench RPM from Github releases page
# Install RPM
sudo yum install -y <rpm_file_downloaded_from_github_releases>
# Install Python package
sudo pip install mzbench_api_client
# Start the server
mzbench start_serverDocker is a container platform, more information is available at its website. If you have Docker up and running, use the following command to start MZBench server:
docker run -d -p 4800:80 --name mzbench_server docker.io/ridrisov/mzbenchAfter that, open http://localhost:4800/ to see the dashboard. Sources for this docker image are available on github.
Instead of download the image from the docker hub, you may want to build it manually:
docker build -t mzbench -f Dockerfile .Helm is a package manager for Kubernetes. We assume that:
- you have Kubernetes cluster with the Helm installed
- kubectl (Kubernetes cli) is configured on the local machine
- helm cli is installed on the local machine
Given that you can install mzbench in k8s with the command
helm install --name mzbench-server deployment/helm/mzbench
To use MZBench, you'll need:
- Erlang R17+
- C++ compiler
- Python 2.6 or 2.7 with pip
Download MZBench from GitHub and install Python requirements:
$ git clone https://github.com/satori-com/mzbench
$ sudo pip install -r mzbench/requirements.txtIf you want to use virtualenv (optional) to isolate Python dependencies:
$ git clone https://github.com/satori-com/mzbench
$ cd mzbench
$ virtualenv venv
$ source venv/bin/activate
$ pip install -r requirements.txtStart the MZBench server on localhost:
$ cd mzbench
$ ./bin/mzbench start_server
Executing make -C /path/to//mzbench/bin/../server generate
Executing /path/to//mzbench/bin/../server/_build/default/rel/mzbench_api/bin/mzbench_api startWhen the server is running, launch an example benchmark:
$ ./bin/mzbench run examples.bdl/ramp.bdl
{
"status": "pending",
"id": 6
}
status: running 00:09Go to localhost:4800 and see the benchmark live status:
