Put load on your system with an easy to use, scriptable and scalable performance testing tool.
Intro
In the world of software development, it is critical to test the performance of an application before it goes live. Load testing is a type of performance testing that simulates real-world traffic on an application to identify potential bottlenecks and determine if it can handle the expected user load. There are several load testing frameworks available, but one of the most popular is Locust.
Locust is an open-source, Python-based load testing framework that allows developers to write user scenarios in code. It is a distributed load testing tool, which means that it can simulate up to millions of users from different locations and devices at the same time.
Benefits
One of the benefits of Locust is that it is easy to use. The framework uses a simple, intuitive syntax that developers can understand without having to spend a lot of time learning how to use it. Additionally, it has a web-based user interface that makes it easy to monitor the progress of a test in real-time. If that’s not your cup of tea, Locust can also run completely fine in headless mode.
Another advantage of Locust is that it is highly scalable. Because it is a distributed load testing framework, it can simulate a large number of users at the same time. Additionally, it can be run on multiple machines, which means that it can generate even more load.
Capabilities
Locust also has a robust set of features that allow developers to create realistic user scenarios. For example, it can simulate users who log in, perform searches, click on links, and perform other actions that are typical of a real user. It also has support for HTTP, WebSockets, and other protocols, which means that it can be used to test a wide variety of applications.
One of the key features of Locust is its ability to generate detailed reports. After a test has been run, it can generate graphs and charts that show how the application performed under different loads. This information can be used to identify performance bottlenecks and make improvements to the application.
In conclusion, Locust is an excellent choice for developers who need to perform load testing on their applications. It is easy to use, highly scalable, and has a robust set of features that allow developers to create realistic user scenarios. Additionally, its ability to generate detailed reports makes it a valuable tool for identifying performance issues and improving the overall quality of an application.
Warm Tips
If you’ve read this far, I’d like to give you a few tips along the way to make your load testing with Locust even more efficient and better.
First of all, Locust is not only distributed, but also containerized. This allows us to use a Kubernetes cluster as a test source. At the same time, this also gives us all the other benefits of Kubernetes. For example, we could define CronJobs that run our load tests automatically on a daily or multiple daily basis.
On the other hand, there is a Locust Exporter that can send the metrics that Locust provides to Prometheus, for example. This way, we can put our usual application monitoring alongside the load test metrics and observe our performance and resilience live during load phases.
On the other hand, Locust enables out-of-the-box HTML reports that are management-ready. CSV reports are also available on-top for free.
Through event hooks built into Locust, you can build custom logic and even some greenlets. Apart from all the high-level stuff, Locust is also just Python code and you can build a complete ecosystem around it.
Helpful Links
- docs.locust.io
- extremely well written documentation on how to use Locust and avoid common pitfalls
- ContainerSolutions/locust_exporter
- a Prometheus exporter for locust metrics. Comes handy to use with the well-known sidecar pattern.