LoadForge provides a powerful platform for conducting load testing using the Locust.io framework. Understanding how to efficiently allocate cloud resources ensures accurate and effective test results. This guide will help you optimize your test configurations for the best performance.Documentation Index
Fetch the complete documentation index at: https://docs.loadforge.com/llms.txt
Use this file to discover all available pages before exploring further.
Resource Dependency
LoadForge tests are primarily CPU-bound, meaning they rely heavily on processing power. Additionally, network sockets play a crucial role in handling large numbers of concurrent connections. Optimizing these resources is essential for generating realistic load scenarios.Performance Guidelines
To ensure optimal test performance, we recommend:- Assigning 10,000 to 20,000 virtual users per worker.
- Allocating one additional server as a controller to manage the test.
Example Calculation:
For a test scenario simulating 50,000 virtual users, you would need:- 1 controller to manage the test.
- 5 worker servers to distribute the client load (50,000 / 10,000 = 5).
Scaling Load Tests
For high-scale testing, LoadForge supports:- Deploying up to 20 worker servers per test.
- Running multiple simultaneous tests.
- Simulating millions of active users across distributed servers.
- Deploying 20 servers, each handling 20,000 virtual users, enables testing of up to 400,000 concurrent users.
- This level of scale is sufficient to simulate real-world traffic for high-demand applications.
Virtual Users vs Real Users: In a real-world scenario, only 20-30% of active users are browsing at any given moment. However, virtual users in load tests generate significantly higher concurrent traffic. Keep this in mind when analyzing results.
Seeking Further Assistance
For large-scale test optimizations, LoadForge offers:- Expert Support – Our team can assist with test configuration and infrastructure scaling.
- Managed Testing Service – Let our experts handle everything, from test setup to execution, ensuring optimal load simulation.