Your Gateway to Exciting Quality Assurance!

Open source tools for performance testing

load testing
Performance testing is a critical part of any software development and deployment process. By load testing and stress testing your applications, you can identify bottlenecks, errors, and optimization opportunities before you release code into production. While there are many enterprise-level paid solutions for performance testing, open source tools provide a flexible and affordable option for teams with limited budgets.

In this post, we’ll explore some of the best open source tools available in 2023 for load testing, stress testing, and monitoring application performance. We’ll look at their key features, benefits, and limitations to help you choose the right solutions for your needs.

Why Open Source Performance Testing Tools?

Here are some of the main benefits of using open source load and stress testing tools:
  • Cost-effective - Open source software is free to use. This makes it ideal for teams with limited testing budgets. You only need to invest in the infrastructure required to run tests.
  • Customizable - Since the source code is available, you can customize tests and additions to suit your application and requirements.
  • Support growing demand - Your application traffic and loads will grow over time. Open source tools allow you to scale your tests as demand increases.
  • Large community support - Popular open source projects have huge communities of developers contributing fixes, enhancements, documentation and support through forums.
  • Avoid vendor lock-in - With open source solutions, you are not locked into a single vendor. You can easily switch between different open source tools as needed.

However, open source tools also have some limitations:
  • Lack of support - With no vendor support, you need to rely on community forums and documentation for assistance.
  • Internal expertise required - You’ll need developers familiar with the tools to customize, scale and troubleshoot tests.
  • Integration challenges - Integrating open source tools with existing systems may require significant effort.

Keeping the pros and cons in mind, let’s look at some of the top open source performance testing tools available.

Apache JMeter

Apache JMeter is one of the most popular open source solutions for load testing and performance measurement. Here are some key features:
  • Cross-platform (Windows, Linux, Mac OS) application for load and functional testing.
-Allows you to simulate heavy loads on your application via multi-threading.
-Supports testing on multiple protocols including HTTP, HTTPS, SOAP, REST, FTP, JDBC, POP3, and more.
-Easy integration with continuous integration tools like Jenkins.
-Plug-in architecture allows enhancing functionality through custom plugins.
-Strong community support through forums, blogs and the Apache JMeter mailing list.

JMeter provides a GUI for test creation as well as CLI support for integrating tests with CI/CD workflows. You can use JMeter to performance test everything from simple websites to complex transactional systems and API endpoints.
The tool is very extensible through plugins. There are custom JMeter plugins available for added functionalities like application performance monitoring, distributed testing, advanced reporting and more.

A core limitation with JMeter is that scripting tests can involve significant coding efforts. JMeter also consumes resources heavily during tests so you need sufficient infrastructure for large-scale tests.
Overall, Apache JMeter is a great open source solution for teams that need to thoroughly load test web and mobile applications.


Locust is an open source load testing framework written in Python. Here are some of its benefits:
  • Tests are scripted with standard Python code making it simple and familiar for Python devs.
  • Utilizes Python’s asynchronous capabilities for simulating thousands of concurrent users on a single machine.
  • Easy to install through Python Package Index (pip).
  • Built-in web UI for controlling distributed tests and monitoring real-time metrics.
  • Seamlessly scales to multiple machines using a master-slave architecture.
  • Provides metrics like requests per second, response times, status codes, failure rates etc.
  • Very customizable – allows tweaking test cases to simulate different user behaviors.

Locust is extremely easy to set up and run thanks to its Python foundations and simple architecture. The Python-based test scripts are also easier to maintain over time.
Being single-threaded, Locust may face limitations in achieving high user load volumes. Commercial alternatives provide higher concurrency support. But Locust remains one of the best free options for distributed load testing.


k6 is another open source load and performance testing tool popular for its scripting in JavaScript. Some key aspects:
  • Tests are written using ES2015 JavaScript making test creation easy for JS devs.
  • Native support for asynchronous tests to help simulate thousands of concurrent virtual users.
  • CLI as well as GUI options available for running tests.
  • Integrates easily into any CI/CD workflow.
  • Metrics like RPS, response times, and error rates can be monitored in real-time during test execution.
  • Tests can be run across different geographic regions using k6 cloud execution.
  • Supports HTTP/1.1, HTTP/2.0, WebSocket and gRPC protocols.

k6 also provides built-in thresholds, checks and alerts to validate performance metrics during tests. Scripts can be modularized and reused across tests.
The tool is extremely developer-focused and finds broad adoption among dev teams practicing shift-left testing principles. Lack of native IDE support can make test creation slightly challenging.
For teams comfortable with JavaScript, k6 provides a very developer-friendly solution for end-to-end performance testing.


Gatling is an open source load and performance testing framework based on Scala, Akka and Netty. Here are some notable aspects:
  • Provides a DSL (domain-specific language) in Scala to create tests easily.
  • Tests can simulate multiple user journeys and scenarios to mimic real-world traffic.
  • Supports protocols like HTTP, WebSocket, Server-Sent Events and JMS.
  • Integrates with CI tools like Jenkins, Bamboo etc.
  • Real-time monitoring and graphical reporting of test results.
  • Tests can be run distributed across multiple machines.

Gatling tests follow a coding structure that promotes reusable components. Simulation setup and execution are separate promoting modular code. The DSL also provides statistics recording out of the box removing instrumentation effort.
However, you need familiarity with Scala and Akka to script and customize tests which raises the learning curve. Gatling is also resource intensive. However, for medium to large teams needing high-scale load testing it can be an excellent open source choice.


Artillery is a modern open-source load testing toolkit ideal for continuously testing web services and APIs. Key features:
  • Tests written in easy YAML syntax.
  • Integrates seamlessly with continuous testing workflows.
  • Supports HTTP, WebSocket and Socket.IO protocols.
  • Run tests across multiple environments via Artillery Pro cloud service.
  • Real-time logging and reporting during test runs.
  • Helps identify performance issues through metrics analysis.

The declarative YAML-based scripting language enables writing tests with minimal coding. Artillery also makes it easy to replicate real-world user workflows by modeling use cases.
Artillery is extremely easy to set up and run performance tests without great effort. Detailed metrics reporting also simplifies analysis. Lack of protocol support beyond HTTP/WebSocket/Socket.IO is a limitation.

For web service teams focused on continuous testing, Artillery provides a lightweight yet powerful open source performance testing solution.


Vegeta is a versatile HTTP load testing utility written in Go. Here are some key aspects:
  • CLI tool with simple commands for test execution.
  • Targets can be specified through command line, file or stdin.
  • Supports testing HTTP requests serially or in parallel.
  • Detailed metrics reporting including latency histograms.
  • Easy to integrate into any testing workflow since it is just a CLI.
  • Can stress test any HTTP endpoint by simulating concurrent users.

Vegeta is ideal for developers wanting to perform quick load tests and benchmarking of HTTP APIs and microservices. The CLI usage lends itself easily to automation and CI workflows. Lack of a GUI may limit use cases compared to other tools.
For teams adopting distributed architectures, Vegeta is an invaluable open source addition to the testing toolkit.


Yandex.Tank is an open source performance testing tool from Yandex with the following capabilities:
  • Supports load and stress testing of HTTP, HTTPS, WebSocket, Apache JMeter and Yandex.Protobuf protocols.
  • Flexible test configurations through YAML files.
  • Real-time metrics monitoring with advanced reporting.
  • Allows distributed and cloud-based test execution.
  • Integrates with monitoring tools for additional performance insights.

Yandex.Tank enables mimicking heavy workloads across different protocols beyond just HTTP. The YAML configuration gives you greater control to customize test scenarios and parameters. Tests can also be easily automated through the CLI.
While primarily targeted at Russian markets, Yandex.Tank works well for teams worldwide needing to performance test non-HTTP services.
Open source performance and load testing tools have evolved robust capabilities rivalling many commercial offerings. Apache JMeter, Locust, k6, Gatling, Artillery, Vegeta and Yandex.Tank are some leading choices available for free.

The ideal tool for your team depends on the type of application under test, protocols used, integration requirements and expertise available. Services with simple HTTP-based APIs are well served by JMeter, Locust and Artillery. More complex web applications and transactional systems benefit from Gatling or Yandex.Tank. Vegeta provides a simple but powerful HTTP benchmarking utility.

While open source tools require more in-house expertise, the right solution can deliver high-quality performance testing without sizable licensing costs. Evaluate options like the ones covered to choose the most appropriate tooling for your performance testing needs.