Skip to content

Latest commit

 

History

History
64 lines (42 loc) · 3.01 KB

README.md

File metadata and controls

64 lines (42 loc) · 3.01 KB
Raw

Load Testing and Profiling with K6 and Flamegraph

Overview

This README provides guidance on how to use K6 and Flamegraph for load testing and profiling a Rust server. K6 is a powerful open-source load testing tool that allows you to test the performance of your APIs, while Flamegraph is a visualization tool for profiling software.

Prerequisites

Before proceeding, ensure you have the following prerequisites installed:

  • Rust server application that you want to test and profile.
  • K6 installed on your local machine.
  • Flamegraph installed on your local machine.

Load Testing with K6

  1. Write Test Scripts: Create K6 test scripts to simulate user interactions with your Rust server. These scripts can include scenarios like making GET, POST, PUT, or DELETE requests to various endpoints.

  2. Run Load Tests: Execute the K6 test scripts against your Rust server to simulate various levels of load and traffic.

    k6 run your_test_script.js

  3. Analyze Results: Analyze the test results generated by K6 to identify performance bottlenecks, response times, throughput, and other relevant metrics.

Profiling with Flamegraph

  1. Instrument Your Rust Code: Integrate profiling instrumentation into your Rust server code. This can be done using libraries like perf-event or profiling.

  2. Run Load Tests with Profiling: Execute your load tests using K6 while profiling your Rust server application.

  3. Analyze Flamegraphs: Visualize and analyze the generated Flamegraphs to identify hotspots in your Rust server code. Hotspots represent areas of code that consume a significant amount of CPU time and may need optimization.

Tips for Effective Load Testing and Profiling

  • Start with Small Tests: Begin by running small-scale load tests to ensure everything is set up correctly before ramping up the load.

  • Iterate and Refine: Continuously iterate on your load testing and profiling processes based on the insights gained from analyzing test results and Flamegraphs.

  • Monitor System Resources: Monitor system resource usage (CPU, memory, disk I/O) during load tests to ensure that the performance bottlenecks observed are not caused by resource contention.

  • Optimize Bottlenecks: Use the insights gained from profiling to optimize the performance of your Rust server application by addressing identified bottlenecks.

  • Document Findings: Document your findings, optimizations made, and lessons learned for future reference and knowledge sharing.

Conclusion

By following the steps outlined in this README, you can effectively load test and profile your Rust server application using K6 and Flamegraph. This process enables you to identify performance issues, optimize your codebase, and ensure that your application can handle varying levels of load and traffic.