link1st/go-stress-testing
Go Stress Testing
This project is a performance benchmarking framework and network protocol stress tester designed to evaluate system stability under high-concurrency conditions. It functions as a command-line utility that simulates massive volumes of simultaneous requests to identify infrastructure bottlenecks and verify service reliability.
The tool distinguishes itself through its protocol-agnostic orchestration, which allows for load testing across diverse standards including HTTP, WebSocket, gRPC, and Radius. It supports complex request configurations, enabling users to inject custom headers, binary data, and external payloads to replicate varied client behaviors. To ensure data integrity during stress tests, the framework utilizes pluggable validation middleware that executes custom logic against server responses in real-time.
Beyond basic load generation, the tool provides comprehensive observability by aggregating performance metrics into live streams for monitoring throughput, latency, and error distributions. It generates detailed statistical reports and integrates with external intelligence services to provide automated analysis and scoring of system performance. The software is configured and managed entirely through command-line parameters, facilitating integration into automated testing workflows.
Features
- HTTP Load Testing - Provides a high-concurrency performance testing utility for simulating heavy traffic across HTTP, WebSocket, and gRPC protocols.
- Multi-Protocol Load Testing - Executes load tests across diverse communication standards including HTTP, HTTPS, WebSocket, gRPC, and Radius.
- High-Concurrency Runtimes - Simulates heavy traffic loads using lightweight routines to maximize CPU utilization and evaluate system performance under extreme volumes.
- Real-time Performance Monitoring - Provides live streams of performance metrics including throughput, latency, and error distributions during active stress testing.
- Load Simulation Testing - Simulates massive volumes of simultaneous user requests to identify system bottlenecks and verify infrastructure stability under extreme traffic conditions.
- Network Stress Testers - Offers a performance evaluation suite that supports custom request payloads and binary data to identify bottlenecks in distributed service architectures.
- Framework Performance Test Executions - Functions as a command-line tool for executing stress tests, monitoring real-time throughput metrics, and generating detailed statistical reports.
- Performance Metric Aggregators - Collects real-time performance data from concurrent workers into a centralized stream for live monitoring and statistical analysis.
- Response Integrity Validation - Verifies server responses using pluggable validation logic to ensure data integrity and expected status codes during high-concurrency load tests.
- Protocol-Agnostic Proxies - Employs a modular interface layer to dispatch traffic across diverse communication standards like HTTP, gRPC, and WebSockets.
- Request Payloads - Supports reading request data, headers, and binary content from external files to simulate complex network traffic patterns.
- Performance Analysis - Generates detailed statistical reports and uses intelligent scoring to evaluate system latency, throughput, and error rates during high-load scenarios.
- Goroutine-Per-Connection Models - Uses lightweight execution threads to manage millions of simultaneous network connections with minimal memory overhead per request.
- Performance Visualization - Renders interactive charts to track requests per second, success rates, and latency trends over the duration of a performance test.
- Performance Reporting - Generates detailed statistical reports and performance summaries after load tests to document system health and response time distributions.
- API Request Configurations - Allows defining custom headers, request bodies, and file uploads via command-line configurations to replicate diverse client behaviors.
- Request Validation Middleware - Executes custom validation logic against server responses during high-load scenarios to verify data integrity and service reliability.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
