locustio/locust

Features

• Performance Testing - Provides a distributed performance testing framework that simulates concurrent users using Python scripts.
• Load Testing Tools - Simulates millions of concurrent users by executing user scenarios defined as Python code in a distributed environment.
• Load Testing Orchestrators - Manages the lifecycle and coordination of distributed worker nodes to execute large-scale performance simulations.
• Real-Time Monitoring Dashboards - Features a built-in web dashboard for real-time monitoring of throughput, latency, and error rates during load tests.
• Load Shaping - Enables dynamic adjustment of traffic intensity and user spawn rates to simulate realistic system stress patterns.
• Stress Testing Platforms - Orchestrates traffic generation across clusters of worker nodes to measure system stability under heavy, real-world load.
• Protocol-Agnostic Clients - Acts as a traffic simulation engine supporting multiple protocols to validate system responsiveness across diverse network architectures.
• Pacing Strategies - Controls task execution frequency using pacing strategies like constant throughput and randomized delays.
• CI/CD Pipeline Integrations - Automates performance validation by triggering load tests within continuous integration and deployment workflows.
• Distributed Orchestration - Coordinates traffic generation across multiple worker nodes using a central master controller for distributed load testing.
• Web Dashboards - Exposes a web-based dashboard for starting, stopping, and monitoring load tests with support for custom extensions.
• Asynchronous Simulation - Simulates high-concurrency user behavior using asynchronous requests to maintain low resource overhead.
• Programmatic Scenario Definition - Constructs test logic using standard programming patterns to simulate complex user behaviors.
• Infrastructure and Monitoring - Scalable load testing tool with a web-based interface.
• Load Testing - Scalable user load testing tool written in Python.
• Graphical User Interfaces - Listed in the “Graphical User Interfaces” section of the The Book Of Secret Knowledge awesome list.
• Testing Frameworks - Scalable user load testing tool.
• Testing Tools - Listed in the “Testing Tools” section of the Awesome Python awesome list.
• Web and GUI Testing - Scalable user load testing tool.
• Data Throughput Optimizers - Optimizes request throughput by utilizing efficient network clients that minimize memory and CPU consumption.
• Worker Scaling - Scales traffic generation capacity by dynamically coordinating multiple worker nodes across distributed environments.
• Protocol Testing - Supports performance testing for non-HTTP protocols like gRPC and MQTT via specialized client drivers.
• Threshold Monitoring - Configures automated exit conditions based on response metrics to integrate load testing into continuous delivery pipelines.
• User Interaction Simulation - Models concurrent users as classes with lifecycle hooks and weighted tasks to simulate realistic interaction patterns.
• Test Execution Runners - Supports command-line execution of performance tests without a graphical interface for automated environments.
• Test Suites - Aggregates multiple test definitions from local files or remote URLs to build modular simulation suites.
• Auto-Instrumentation - Generates spans and metrics automatically for HTTP traffic to provide visibility into request performance.
• Protocol-Agnostic User Classes - Enables connectivity to diverse protocols like SocketIO and DNS through modular, custom user classes.
• Task Weighting - Provides programmatic control to adjust task weighting and load intensity dynamically during active performance tests.
• Telemetry Collection and Aggregation - Aggregates and streams real-time performance metrics from distributed workers to external monitoring backends.
• AI Service Load Testing - Simulates traffic to AI services by tracking token consumption and response latency.
• Test Execution Management - Allows programmatic control over test execution environments and runners directly from custom scripts.
• Plugin Systems - Supports third-party plugins to extend core functionality with custom user types, protocols, and execution logic.
• Cloud Infrastructure Deployment - Enables execution of load testing scenarios on managed cloud infrastructure to simulate large-scale traffic.
• Containerized Deployments - Packages test scenarios and environments into container images for consistent performance testing across host systems.
• Connection Lifecycle Managers - Manages network connection lifecycles to accurately replicate browser traffic patterns and ensure realistic performance metrics.
• Concurrency Models - Uses lightweight asynchronous coroutines to simulate high concurrency with minimal resource overhead.
• Telemetry Protocols - Streams traces, metrics, and logs from load tests to external observability backends using standard protocols.
• Request Logging - Records granular, per-request data points to files for detailed post-run performance analysis.
• Test Fixture Management - Executes load tests using standard testing syntax and fixtures for easier debugging and reuse.
• Test Lifecycle Hooks - Provides hooks to execute custom logic during test initialization, start, and teardown phases.
• Performance Analysis - Provides diagnostic insights and automated recommendations based on collected test metrics.
• RESTful API Clients - Automates JSON parsing, header configuration, and error handling for REST endpoints during load tests.

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