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Taurus

Taurus​

Taurus is an open-source performance testing tool that simplifies the creation, execution, and analysis of performance tests. It supports various testing tools and integrates well with modern CI/CD pipelines. This guide covers installation on Linux, running Taurus with Docker, and provides several example scripts to help you get started.

Taurus install linux​

To install Taurus on a Linux system, follow these steps:

sudo yum install java-1.8.0  
sudo yum remove java-1.7.0-openjdk  
sudo yum install python default-jre-headless python-tk python-pip python-dev \
libxml2-dev libxslt-dev zlib1g-dev net-tools  
sudo yum -y install gcc  
sudo yum install bzt

Running Taurus with Docker​

You can run Taurus using Docker for an isolated environment. Here’s how:

docker run --rm -v C:\ccviews\taurus:/bzt-configs -v C:\ccviews\taurus\artifact:/tmp/artifacts blazemeter/taurus taurus_execution.yml

Replace /path/to/taurus/config with the directory containing your Taurus configuration files, and /path/to/taurus/artifacts with the directory where you want to save the test artifacts.

Example Scripts​

Here are several example Taurus scripts to illustrate different scenarios and configurations.

Demo Script 1​

execution:
- scenario: testlogin
  concurrency: 170
  hold-for: 50s
  duration: 60
scenarios:
  testlogin:
    headers:
      Content-type: application/json
      User-Agent: 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.122 Safari/537.36'
    requests:
    - url: https://
      method: POST
      label: '/signin'
      body:
        'username': 
        'password': 
      assert-jsonpath:
        - jsonpath: "$.ErrorNo" # path to value, validation fails if path not exists
          validate: true # validate against expected value
          expected-value: "0" # the value we are expecting to validate, default: false
          regexp: true  # if the value is regular expression, default: true
          expect-null: false  # expected value is null
          invert: false # invert condition 

reporting:
- module: console
- module: final-stats
  summary: true
  percentiles: true
  failed-labels: false   
  test-duration: true

Description:

  • Simulates 170 users for 50 seconds, then maintains 10 users for 60 seconds.
  • Posts a login request and checks the response for an expected error code.
  • Reports are generated on the console and include final statistics with percentiles.

Demo Script 2​

execution:
- scenario: testlogin
  concurrency: 300
  hold-for: 3000s
  duration: 1000
scenarios:
  testlogin:
    headers:
      Content-type: application/json
      User-Agent: 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36'
    requests:
    - url: https://
      method: POST
      body:
        'username': 
        'password': 
        
reporting:
- final-stats
- console

Description:

  • Simulates 300 users for 3000 seconds, then performs a load test for 1000 seconds.
  • Posts login requests and generates a report with final statistics and console output.

Demo Script 3​

execution:
- scenario: test
  concurrency: 2
  hold-for: 10s
  duration: 2
scenarios:
  test:
    headers:
      Content-type: application/json
    requests:
    - url: https://******/api/
      method: GET
      extract-jsonpath:   
        masterEventIds: $.result.
        eventIds: $.result.
    - url: https://******/api/
      method: GET
      label: bpe
      assert-jsonpath:
        - "$[0].quantity"
    
reporting:
#- module: blazemeter
#  report-name: testbpe
#  test: testbpe
#  project: testbpe
- module: passfail
  criteria:
  - avg-rt of bpe>100ms for 10s, stop as failed
  - rc4?? of bpe>1, stop as failed
  - rc5?? of bpe>1, stop as failed

Description:

  • Runs a scenario with 2 users for 10 seconds, testing API endpoints.
  • Extracts JSON values and checks conditions against response time and status codes.
  • Uses a pass/fail reporting module based on custom criteria.

Monitoring and Integration​

For more advanced monitoring and integration, you can use tools such as Grafana and InfluxDB. Here are some useful resources:

Creating a Lightweight Performance Monitoring Solution with Docker, Grafana, and InfluxDB

Gatling Tests Monitoring with Grafana and InfluxDB

Taurus with Docker​

  • Create folder name taurus
  • Create sub folder name artifact
docker run --rm -v C:\ccviews\taurus:/bzt-configs -v C:\ccviews\taurus\artifact:/tmp/artifacts blazemeter/taurus taurus_execution1.yml