When it comes to WebRTC testing, there aren’t many feature-rich tools on the market. Loadero is one of those, testRTC is another widely known option, so we get questions about how those two compare frequently. To give a detailed answer to that question, we published this blog post in which we attempted to make a comprehensive comparison of the two tools.

As of k6 version 0.43.0, xk6-browser is now bundled in k6 as an experimental module! 🙌 Since announcing xk6-browser in November 2021 at Grafana ObservabilityCON, the team have been busy adding on new features to include browser automation in k6. The interest from the community has also increased, which shows that browser automation and frontend performance is as important as backend performance.

Load and performance testing remains a vital aspect of any software delivery process. Ensuring that your application supports the anticipated number of concurrent users prevents brand damage, system failures in production, and loss of revenue. There is a saying in engineering that the shape of the solution is dictated by the shape of the problem. Translating this to performance testing solutions, there are several common design elements that all load and performance testing solutions share.

In this article, we will discover the process of sending custom metrics, provided to us through the xk6-browser, in order to gain a better understanding of our performance tests. Through the integration of these metrics, we will be able to create more tailored Slack messages that will help to manage our rule sets.

Grafana Faro and xk6-browser are both new tools within the Grafana Labs open source ecosystem, but the pairing is already showing a lot of potential in terms of frontend monitoring and performance testing. Faro, which was announced last November, includes a highly configurable SDK that instruments web apps to capture observability signals that can then be correlated with backend and infrastructure data.

We are going to look at how performance testing can work hand in hand with Artificial Intelligence and Machine Learning: As there are many Artificial Intelligence solutions to choose from and for the purposes of this post this is the easiest way to discuss the principles of Artificial Intelligence working with performance testing rather than discussing a particular framework.