Scaling Together: Community-Driven Load Testing for Python Apps
Performance bottlenecks can make or break your app, but load testing often gets pushed aside during development. In the open-source world, why aren't we treating performance testing as a shared responsibility? This talk shows how developers, testers, and infrastructure engineers can collaborate to build scalable Python applications.

We'll use a Django case study and Apache JMeter to demonstrate effective stress-testing techniques and common pitfalls to avoid. We'll also explore open-source tools like Locust and k6, and discuss how the community can contribute by sharing test plans, scripts, and best practices. Think of it as open-sourcing your load testing strategy.

Beyond the technical aspects, this session emphasizes collective knowledge. Imagine a world where shared test suites and benchmarking efforts become the norm—where Python apps benefit from communiPython App Load Testing
Performance bottlenecks can make or break your app, but load testing often gets pushed aside during development. In this hands-on workshop, we'll treat performance testing as a shared responsibility, showing how developers, testers, and infrastructure engineers can collaborate to build scalable Python applications.
Through a Django case study and Apache JMeter, you'll learn to conduct effective stress-testing and identify common pitfalls. You'll also explore open-source tools like Locust and k6, and discover how to contribute to community resources by sharing test plans, scripts, and best practices.
This workshop emphasizes collective knowledge. Participants will work together on shared test suites and benchmarking efforts, experiencing firsthand how community-driven testing strengthens Python applications. By the end, you'll have practical experience integrating load testing into your workflow and leveraging community efforts to build faster, more resilient applications.