This article demonstrates how to Load Test an application deployed in a Kubernetes cluster, verify that the autoscaling is working, and identify potential performance bottlenecks. When you deploy an application to production on Kubernetes, you'll need to monitor traffic and scale up the application to meet heavy workloads during various times of the day. You'll also need to scale down your application to avoid incurring unnecessary costs.

In this article, I'll explain how to use a Postman collection I have created to load test our instance of our test API. The process is pretty straightforward, as is shown below. You need to feed your exported Postman collection to our postman-to-k6 converter, and use the generated k6 script to load test your own API.

At the end of 2018, Microsoft stated that Visual Studio 2019 is the last version with load testing features. A few months later they formally announced that Azure load testing is closing down on March 31st, 2020. This announcement came as a bomb to the community. But for those who follow this market, the news was not a complete surprise.

In this tutorial, we will look into how to integrate performance testing with k6 in your TeamCity build setup. k6 is a free and open-source performance testing tool for testing the performance of APIs, microservices and websites. TeamCity is a continuous integration and delivery server built by JetBrains.

Throughout the years, there has been many attempts to devise a universal format for defining Web API specifications. The objective was (and still is) to help stakeholders of the system to work with those APIs, without having access to the source code. Each new "universal" format came with the promise of being ubiquitous and all-encompassing, but eventually faded away due to various reasons, like OData and WSDL.

There are two different categories of tools in the load testing ecosystem. The first category is called non-scriptable tools and are usually used for load testing either a single endpoint or a set of endpoints. These tools usually generate load using a constant rate, which is measured in requests per unit of time, usually seconds. These non-scriptable tools don't apply any logic to the load testing process, other than the generation of load.

It has been almost three years since we first published our first comparison & benchmark articles that have become very popular, and we thought an update seemed overdue as some tools have changed a lot in the past couple of years. For this update, we decided to put everything into one huge article - making it more of a guide for those trying to choose a tool.

We’ve set up several initiatives aimed at testing and improving the performance of GitLab, which is why the Quality team built a new tool to test GitLab's performance. Performance testing is an involved process and distinct from other testing disciplines. The strategies and tooling in this space are specialized and require dedicated resources to achieve results.

This is a proud day for all of us here at LoadImpact! Today is the day we're unveiling the new k6 Cloud service. A completely rebuilt frontend to our cloud service including some much requested improvements. Today is also the day when we make public our plan to rebrand the company as "k6", the starting point for the transition away from the "LoadImpact" brand and loadimpact.com to the "k6" brand and k6.io.

At the end of the year, I like to look back at what new discoveries I've made and lessons I've learnt as a QA engineer. 2019 has proved to be a bonanza year, with some startling changes in direction for Test and with new technologies and methodologies making a break into the mainstream.