Systems | Development | Analytics | API | Testing

January 2022

Señor Performo's week of load testing with k6 - Leandro Melendez (k6 Office Hours #39)

A new croc appears! Leandro Melendez, aka Señor Performo, talks about what it's like to join the team behind the load testing tool k6. Every new k6 croc does a week of load testing with k6-- here's what he had to say about his first impressions of using k6.

How to Add Notes to your Load Test Results

We’ve added the functionality to add notes to your load test results. This functionality applies to Load Tests and JMeter Load Tests. It’s super simple to add/edit/remove notes for any of the test runs of the same test in order to caption various changes of your test runs. You can easily compare any test run with a baseline.

Test Automation With Python

According to IEEE Spectrum Python is the top programming language of 2021, and since April Loadero supports Python as a test script language. Many engineers agree that test automation with Python is an excellent choice, and in this blog post, we’ll show the basics of it. Python tests in Loadero use the Py-TestUI framework. Py-TestUI wraps and implements additional features for Selenium Python binding.

How to Compare Two Load Tests using the Baseline Comparison Feature

The load test comparison feature build-in to LoadFocus Results allows you to compare the results of two different test runs of the same test for the cloud load testing service. You can visually compare the results between the test run set as baseline and the current test run, just by setting a test run as a baseline, and loading the other load tests runs. Baseline comparison is important because it allows to easily find differences in performance for the test runs.

How the new k6 Cloud app plugin makes it easy to correlate QA data and system metrics in Grafana

​ One of the common challenges when doing performance testing is the difficulty of correlating the metrics of your application with your testing results. Having available QA, infrastructure, and application metrics together allows engineering teams to better understand the behavior of their systems during the testing, helping to detect and prevent potential issues in their applications.