gatling/gatling

Features

• Performance Testing - Simulates high volumes of concurrent user traffic to identify system bottlenecks and stability limits under heavy load.
• Traffic Generation Engines - A distributed infrastructure for simulating thousands of concurrent users across local and cloud environments.
• Domain Specific Languages - Provides a high-level fluid API that serves as a domain-specific language for defining load simulation execution plans.
• As-Code Testing Libraries - Functions as a framework for writing version-controlled test scenarios in programming languages instead of using graphical interfaces.
• Quality Gates - Integrates performance success criteria into build pipelines as automated gates that block deployments upon failure.
• Distributed Load Generation - Coordinates multiple remote worker nodes to generate and synchronize high-volume request bursts across a global footprint.
• Performance Analysis - Provides tools for analyzing response times and error rates to identify system bottlenecks and stability limits.
• Load Testing Tools - Provides a code-based framework for defining and executing high-volume traffic simulations to analyze system stability.
• Metric-Based Regression Testing - Automates the comparison of quantitative performance metrics against baselines within build pipelines to block regressions.
• Performance Testing Frameworks - Measures response times and error rates under heavy load using scripted network requests to identify bottlenecks.
• Test-as-Code Frameworks - Allows performance test scenarios to be defined as version-controlled code for integration into CI/CD pipelines.
• Test-as-Code Workflows - Defines performance scenarios using programming languages to maintain version-controlled scripts integrated into delivery pipelines.
• Virtual User Simulation - Simulates thousands of concurrent virtual users executing scripted scenarios to measure system performance.
• Performance Metric Aggregators - Collects timing and error data in memory and flushes it to disk for post-simulation report generation.
• Deployment Scaling - Supports scaling traffic generators across local, private, or managed cloud environments to simulate global user loads.
• Asynchronous Event Loops - Utilizes an asynchronous event loop to process request and response cycles efficiently on a small set of threads.
• Actor-Based Concurrency - Implements an actor-based concurrency model to manage thousands of concurrent virtual users without thread-locking.
• Non-blocking I/O - Employs a Netty-based non-blocking I/O engine to handle massive network traffic with minimal resource consumption per connection.
• Performance Trend Analysis - Offers real-time dashboards and service level monitoring to aggregate and analyze performance patterns over time.
• Real-Time Monitoring Dashboards - Provides real-time dashboards to analyze response times and error rates for tracking system health and SLAs.
• Distributed Scalability Analysis - Evaluates how systems handle global user loads at scale by deploying traffic generators across cloud environments.
• Multi-Language Simulations - Supports defining load simulations using multiple programming languages and recorded browser sessions.
• Data Collection Agents - Async stress testing tool with database support.
• Testing Frameworks - Performance testing framework with a developer-friendly DSL.

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