Automated testing is running the tests and reporting results by tools with scripts. Automated performance testing is designing the performance test scenarios to run them spontaneously by tools and evaluating the result by tools to decide to go or not to go further.
- A subset of the performance test scenarios
- Designed to run spontaneously by tools
- Designed to evaluate the result by tools
- Designed not to break the system
- Having decision metrics, ex: max response time, max-average resp time, …
- Designed to create reports for the concurrent and historical run
What Types of Performance Testing Should be Automated
Automated performance testing can be applied to all types of performance testing. However, each type needs a different level of maturity and sanity.
Automated Performance Testing is
- Easily applied to load testing
- Hard to apply stress test, spike test, but have benefits
- Very hard to apply Soak-Endurance test
Automated Load Tests
Since the load test is aiming to the response of the system under a specific load and it is a success belongs to the pre-defined metrics, load testing is the best-suited performance testing type.
Automated Load Testing is
- Needing a specific load level
- Needing pre-defined metrics
- Needing evaluation of the result
- Needing exactly the same environment — only one thing can be testable
- Needing tools and script knowledge
- Easy to integrate CI/CD pipeline — everything is scripted
- Reporting the performance of the system when something changes
Tools Needed for Automated Performance Testing
Performance testing depends on two main parts. The first part is creating loads and the second part is using these loads for test scenarios. When it comes to doing automated performance testing, we need more tools. The tools needed for automated performance testing can be classified into the following items:
Open-source Performance Testing Tools
- Jmeter — Apache project, v1.0 1998
- Gatling — Enterprise support by Frontline
- K6 — Enterprise support by LoadImpact
- and many others
Commercial Performance Testing Tools
- LoadRunner by Microfocus (previously Mercury — HP)
- Blazemeter — support multiple opensource tools
- LoadUI Pro by Smartbear
- InfluxDB — Opensourced times series database
- MongoDB — Opensourced document-based database
- Docker Compose
- Mesosphere DC/OS
- And others
- Code Ship
- Gitlab CI”
A Way of Implementation of K6 for Automated Performance Testing
K6 is an open-source performance testing tool. It is designed for developers, it gives us many good features to run tests in a safer, faster, easier integrated way. Very easy to integrate it to CI/CD.
Some of the Good Features of K6 are
- Precious in performance, among the top 5 in comparison
- Easy to connect to DB (such as InfluxDB)
- Easy to create reports (Grafana)
K6 has rich libraries that you can use in the script. The request is sending by HTTP from k6/http. Grouping is letting you run the same kind of request in a group. Check the simple test scripts which have to get requests to the three URLs and post requests to register endpoint with dynamic data.
Command-line supports many parameters to run your scripts. For a load test, we have fixed virtual user and fixed test duration so the run script should look like
For a spike test, we should load the system with a nominal load and the load should increase suddenly. Let’s focus on at the — stage option for this.
K6 can be easily integrated with an InfluxDB instance so in the setup we are also running the docker-compose to create an InfluxDB instance with will use for feeding Grafana dashboard to visualize all the data.
The K6 sends the results to the InfluxDB, we can virtualize this data with Grafana. You can use the dashboard created by the LoadImpact
Add these scripts to your CI/CD pipeline to run an automated performance test and see the result in Jenkins. To see all the scripts and data check this repo on Github
Originally published at https://www.testrisk.com on December 31, 2019.