The purpose of this project is to provide a ready and easy-to-use version of locust.io which also contains additional/useful features that are required.
Docker-Locust consist of 3 different roles:
- Master: Instance that will run Locust's web interface where you start and stop the load test and see live statistics.
- Slave: Instance that will simulate users and attack the target url based on user parameters.
- Controller: Instance that will be run for automatic mode and will download the HTML report at the end of load test.
This architecture support following type of deployment:
- single container (standalone mode): If user have only one single machine.
- multiple containers (normal mode): If user have more than one machine and want to create bigger load. This type of deployment might be used in docker-swarm or kubernetes case. An example for deployment in different containers can be seen in docker-compose.
- It allows locust to read load test scenario/script from different resources (any HTTP/HTTPS URL, S3 bucket, and local machine).
- It has the ability to be run in any CI tool e.g. Jenkins (It can start/stop load test automatically) and provides an HTML report at the end of a load test.
- It is also possible to be deployed in AWS to create bigger load.
- docker engine version 1.9.1+
- docker-compose version 1.6.0+ (optional)
docker-locust will be run as standalone version by default. Standalone version is for users who has only 1 single machine.
bash <(curl -s https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/local.sh) deployYou will be prompted for certains inputs required (You can use our example in github as load test script).
Target url: https://targeturl.com
Where load test script is stored: https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/simple.py
Number of slave(s): 4
Run type [automatic/manual]: manual
All of it can be simplify in one line:
bash <(curl -s https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/local.sh) deploy --target=https://targeturl.com --locust-file=https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/simple.py --slaves=4 --mode=manualIt is also possible to run with normal docker command:
docker run -i --rm -v $PWD/reports:/opt/reports -v ~/.aws:/root/.aws -v $PWD/:/opt/script -v $PWD/credentials:/meta/credentials -p 8089:8089 -e ROLE=standalone -e TARGET_HOST=https://targeturl.com -e LOCUST_FILE=https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/simple.py -e SLAVE_MUL=4 -e AUTOMATIC=False registry.opensource.zalan.do/tip/docker-locustdocker-locust can be run in multiple docker-containers. It is useful for users who has more than one machine to create bigger load. In this point we are using docker-compose, but it is also possible to run it in different ways, e.g. Cloudformation in AWS.
Run the application with the command:
DOCKER_COMPOSE=true bash <(curl -s https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/local.sh) deploydocker-locust has the ability to read multiple files from s3 or any http/https, e.g. 1 file is the load test file / python file and 1 other file is json file where payloads are stored. Sample command:
bash <(curl -s https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/local.sh) deploy --target=https://targeturl.com --locust-file=https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/simple_post.py,https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/payloads.json --slaves=4 --mode=manualPlease add following lines to your load test script, like this example.
from locust.web import app
from src import report
app.add_url_rule('/htmlreport', 'htmlreport', report.download_report)
Simply after load test run, append "/htmlreport" to the URL which will download the report of the recent run. Example:
docker-locust can be run automatically by using CI tool like jenkins.
Sample case:
- Number of users [total users that will be simulated]: 100
- Hatch rate [number of user will be added per second]: 5
- Duration [in seconds]: 30
- Target url: https://targeturl.com
- Load test script: simple.py
- Number of slaves: 4
Steps:
-
Put following command in "Execute shell" field:
curl -O https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/local.sh && DOCKER_COMPOSE=true bash local.sh deploy --target=https://targeturl.com --locust-file=https://raw.githubusercontent.com/zalando-incubator/docker-locust/master/example/simple.py --slaves=4 --mode=automatic --users=100 --hatch-rate=5 --duration=30 -
Install html-publisher-plugin in jenkins to display load test result. Example configuration in jenkins job:
All output from containers can be see by running:
docker-compose logs -fA version number is combination between the locust version being supported and patch level, e.g. when a release is 0.7.3-p0, it support locust 0.7.3.
All the data based on load testing against simple hello-world application with the default max_wait and min_wait values (1000ms).
| No. | Group Type | EC2 | vCPU | RAM (GiB) | Clock Speed (GHz) | Enhanced Networking | Max total RPS that can be created per 1 slave machine (rough number) | Price per hour (EU - Frankfurt) | RPS per cent |
|---|---|---|---|---|---|---|---|---|---|
| 1 | General Purpose | t2.nano | 1 | 0.5 | up to 3.3 | - | 200 | $0.0068 | 294.12 |
| 2 | General Purpose | t2.micro | 1 | 1 | up to 3.3 | - | 500 | $0.014 | 357.14 |
| 3 | General Purpose | t2.small | 1 | 2 | up to 3.3 | - | 500 | $0.027 | 185.19 |
| 4 | General Purpose | t2.medium | 2 | 4 | up to 3.3 | - | 1100 | $0.054 | 203.7 |
| 5 | General Purpose | t2.large | 2 | 8 | up to 3.0 | - | 1100 | $0.108 | 101.85 |
| 6 | General Purpose | t2.xlarge | 4 | 16 | up to 3.0 | - | 2200 | $0.216 | 101.85 |
| 7 | General Purpose | t2.2xlarge | 8 | 32 | up to 3.0 | - | 4700 | $0.432 | 108.8 |
| 8 | General Purpose | m4.large | 2 | 8 | 2.4 | Yes | 700 | $0.12 | 58.33 |
| 9 | General Purpose | m4.xlarge | 4 | 16 | 2.4 | Yes | 1500 | $0.24 | 62.5 |
| 10 | General Purpose | m4.2xlarge | 8 | 32 | 2.4 | Yes | 2500 | $0.48 | 52.08 |
| 11 | General Purpose | m4.4xlarge | 16 | 64 | 2.4 | Yes | 6500 | $0.96 | 67.71 |
| 12 | General Purpose | m4.10xlarge | 40 | 160 | 2.4 | Yes | 10000 | $2.4 | 41.67 |
| 13 | General Purpose | m4.16xlarge | 64 | 256 | 2.3 | Yes | 17000 | $3.84 | 44.27 |
| 14 | General Purpose | m3.medium | 1 | 3.75 | 2.5 | - | 250 | $0.079 | 31.65 |
| 15 | General Purpose | m3.large | 2 | 7.5 | 2.5 | - | 600 | $0.158 | 37.97 |
| 16 | General Purpose | m3.xlarge | 4 | 15 | 2.5 | - | 1300 | $0.315 | 41.27 |
| 17 | General Purpose | m3.2xlarge | 8 | 30 | 2.5 | - | 2600 | $0.632 | 41.14 |
| 18 | Compute Optimized | c4.large | 2 | 3.75 | 2.9 | Yes | 800 | $0.114 | 70.18 |
| 19 | Compute Optimized | c4.xlarge | 4 | 7.5 | 2.9 | Yes | 1600 | $0.227 | 70.48 |
| 20 | Compute Optimized | c4.2xlarge | 8 | 15 | 2.9 | Yes | 2500 | $0.454 | 55.07 |
| 21 | Compute Optimized | c4.4xlarge | 16 | 30 | 2.9 | Yes | 6500 | $0.909 | 71.51 |
| 22 | Compute Optimized | c4.8xlarge | 36 | 60 | 2.9 | Yes | 12500 | $1.817 | 68.79 |
| 23 | Compute Optimized | c3.large | 2 | 3.75 | 2.8 | Yes | 650 | $0.129 | 50.39 |
| 24 | Compute Optimized | c3.xlarge | 4 | 7.5 | 2.8 | Yes | 1300 | $0.258 | 50.39 |
| 25 | Compute Optimized | c3.2xlarge | 8 | 15 | 2.8 | Yes | 2500 | $0.516 | 48.45 |
| 26 | Compute Optimized | c3.4xlarge | 16 | 30 | 2.8 | Yes | 5500 | $1.032 | 53.29 |
| 27 | Compute Optimized | c3.8xlarge | 32 | 60 | 2.8 | Yes | 9000 | $2.064 | 43.6 |
NOTE:
- Please check AWS-EC2-Type and AWS-EC2-pricing before use data above, because some of them could be changed time to time.
- Number of total RPS could be different because of n reasons.
Any feedback or contributions are welcome! Please check our guidelines.
Run the unit tests with this command:
local.sh testSee License
See Security