Loadero API allows managing and running tests just as one would via the Loadero web application. However, sending an HTTP request every time a test needs to be created, updated, or run can become cumbersome. We already had a Java client, which makes the processes easier, and now Loadero team has been hard at work creating a new client and we are proud to present – Loadero-Python.

I’m a big fan of K6, it makes writing performance tests quick and easy. In fact I wrote about it previously on my blog in a post titled Performance testing APIs in pipelines? K6 makes it simple! What I didn’t mention in that post was how to lint K6. Now you might be thinking, K6 tests are written in JavaScript, how hard can it be to lint? The problem is that although we write K6 tests in JavaScript, K6 itself is written in GoLang, an so we run into issues with Linting when importing K6.

This post presents how xk6-disruptor, a k6 extension for fault injection, can be used to improve the reliability of applications by “shifting left” chaos testing.

One of the major factors that come into play when deciding on a load testing tool is whether it can perform as you expect it to. There are many ways to measure how well a load testing tool performs, with the amount of requests per second undoubtedly being one of the main ways. Speedscale creates load tests from recorded traffic, so generating load is at the core of the tool.

You can test the software under normal conditions, and that will tell you a lot about what it can and can’t do. What you need to know, though, is how robust that software is. How can it handle intense conditions? How does it cope with error handling? Essentially, you’re testing the software by pushing it beyond its limits, to see exactly when it breaks. That’s information that you need to have, as you’ll then see just how far you can push the software when using it.

Hi there, Here at k6, we’re constantly shipping new features to help our users get the most out of k6. In case you missed it, here’s a roundup of all the k6 and k6 Cloud news, updates, and improvements you should know about.

Here are some important suggestions on how to improve your search engine optimization (SEO) and advance your website and every page in the ranks of search engine result pages (SERPs) to the top of the page results.

With version 0.41, k6 has changed how it handles, stores, and aggregates the data it collects in the context of a load test. Most users probably won't notice any immediate difference. Yet, we expect these changes will empower us to make k6 more performant and easier to integrate into the larger observability ecosystem.

When building performance tests, we all understand the value of using properties or variables to store static values outside of our tests. This ensures that any changes to these values need only be made in one place rather than having to make these changes in many tests. Sometime though you may have inherited a suite of JMeter tests, or you were ** under pressure to develop these tests** and in order to do so you hardcoded values in your tests.

This tutorial will demonstrate Keptn, a CNCF Incubator Project’s integration with k6. Keptn is a cloud-native application delivery and operations platform. We will use the Job Executor Service to execute k6 performance testing in a Keptn project. We'll start with running a k6 script and how the logs look. And then we'll modify the k6 script to see the behavior when it fails.

At ObservabilityCON, we announced our first step towards launching a native integration between Grafana k6 load testing and Grafana Tempo tracing (k6 x Tempo) in Grafana Cloud. We created k6 x Tempo to help dev, testing, and operation teams analyze their performance test results more effectively and proactively improve the reliability of their business-critical applications.