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locust VS JSON Server

Compare locust VS JSON Server and see what are their differences

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locust logo locust

An open source load testing tool written in Python.

JSON Server logo JSON Server

Get a full fake REST API with zero coding in less than 30 seconds. For front-end developers who need a quick back-end for prototyping and mocking
  • locust Landing page
    Landing page //
    2021-10-11
  • JSON Server Landing page
    Landing page //
    2023-08-01

locust features and specs

  • Scalability
    Locust is designed to distribute the load tests across multiple machines, allowing for high scalability and the ability to simulate millions of users.
  • Python-based
    The tool is written in Python, which makes it highly flexible and suitable for those who are familiar with the language. You can write custom test scenarios easily.
  • Web-based UI
    Locust provides a user-friendly web-based interface that makes it easy to monitor and control the test execution in real-time.
  • Real-time monitoring
    During test execution, you get real-time statistics and charts that help in monitoring the performance and load.
  • Open-source
    Being an open-source tool, Locust allows for community contributions and is free to use, which helps in continuous improvement and support from the user base.

Possible disadvantages of locust

  • Setup Complexity
    Initial setup can be somewhat complex, especially for large scale or distributed tests. Requires experience with Python and potentially other infrastructure setups.
  • Resource Intensive
    Locust can be resource-intensive, requiring significant compute resources, particularly when simulating large numbers of users.
  • Steeper Learning Curve
    Despite its flexibility, the requirement to write test scenarios in Python may present a learning curve for users not familiar with programming.
  • Limited Protocol Support
    Primarily designed for HTTP/HTTPS protocols, Locust might not be suitable for load testing applications that use other protocols without additional customization.
  • Dependence on External Libraries
    While the use of Python offers flexibility, it also means that you might need to rely on external libraries and tools, which can introduce dependency management issues.

JSON Server features and specs

  • Ease of Setup
    JSON Server can be set up quickly with minimal configuration, making it ideal for prototyping and rapid development. It allows developers to have a fully functioning REST API within minutes.
  • RESTful API
    It provides a standard RESTful API out of the box, allowing developers to perform all CRUD operations. This is helpful for simulating a real-world server while testing client-side applications.
  • Customization
    JSON Server supports middlewares, routes, and custom rules, allowing developers to customize the behavior and structure of the API to better suit their needs.
  • Fakes Backend Data
    It's great for simulating backend responses without needing a real backend setup, useful in front-end development to test components and interactions.
  • Lightweight
    As a lightweight server, it requires fewer resources and is quite simple compared to setting up a full-fledged backend server.

Possible disadvantages of JSON Server

  • Not for Production
    JSON Server is designed for development and testing. It is not suitable for production use due to performance limits and lack of robust security features.
  • Limited Functionality
    While JSON Server is great for basic CRUD operations, it lacks advanced features like authentication, authorization, and complex querying.
  • Data Persistence
    Data is stored in a JSON file, and while this is convenient for testing, it is not suitable for applications that require persistent and scalable data storage.
  • In-memory Limitations
    Being an in-memory server, it may have issues with handling large datasets or complex data structures efficiently.
  • Manual Data Reset
    Any changes made to the JSON file while the server is running require manual resets or reloads to reflect in the API, which can be cumbersome during continuous development cycles.

Analysis of locust

Overall verdict

  • Locust is a powerful and flexible tool for load testing, particularly advantageous for teams familiar with Python. Its scalability and ease of setup make it a strong choice for both small and large projects.

Why this product is good

  • Locust (locust.io) is considered a good tool for load testing due to its easy-to-use, scalable, and distributed nature. Written in Python, it allows developers to write simple or complex test scenarios in the same language. It enables the simulation of millions of users by distributing tasks across multiple machines, making it highly valuable for performance testing of websites and applications. The web-based user interface is another advantage, allowing real-time monitoring of test progress and results.

Recommended for

  • Development teams looking for a scalable load testing tool.
  • Organizations that prefer open-source solutions.
  • Projects requiring custom test scenarios in Python.
  • Teams needing real-time monitoring and distributed testing capabilities.

locust videos

Locust review - GTA Online guides

More videos:

  • Review - GTA Online: Ocelot Locust Review
  • Review - GTA 5 - DLC Vehicle Customization - Ocelot Locust and Review

JSON Server videos

Angular CRUD with Web API Tutorial Part #3 - Setup Local JSON Server and Mock API Endpoints

Category Popularity

0-100% (relative to locust and JSON Server)
Monitoring Tools
100 100%
0% 0
Development
0 0%
100% 100
Website Testing
100 100%
0% 0
API Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

locust might be a bit more popular than JSON Server. We know about 65 links to it since March 2021 and only 45 links to JSON Server. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

locust mentions (65)

  • 15 Common Kubernetes Pitfalls & Challenges
    Regularly review your cluster's utilization to check whether it's still suitable for your workloads. Test autoscaling rules by using a load-testing tool like Locust to direct excess traffic to your cluster. This lets you spot problems earlier, ensuring your Pods will scale seamlessly when real traffic arrives. - Source: dev.to / 10 months ago
  • Small-Scale Chaos Testing: The Missing Step Before Production
    Locust: While primarily a load testing tool, it can be used to simulate user behavior under stress. - Source: dev.to / 10 months ago
  • Log Spikes? Noย Sweat: How Top DevOps Teams Tame Bursty Workloads
    But you donโ€™t have to operate at Netflixโ€™s scale to benefit from the same mindset. Effective teams simulate log floods during load tests, which push traffic through staging environments while tracking how ingestion, indexing, and alerting respond to the increased load. Tools like Grafanaโ€™s k6 and Locust can simulate thousands of requests per second, while synthetic log generators mimic bursty error scenarios. - Source: dev.to / about 1 year ago
  • Serving 200M requests per day with a CGI-bin
    I mean honestly - the "classic" Apache model of throwing things into the www root is very strong for rapid development. Hot code reloading is sometimes finicky, you can end up with unexpected hidden state and lose sanity over a stupid heisenbug. Trust me. IMO you don't need to compensate for bad configs if you're using a proper staging environment and push-button deployments (which is good practice regardless of... - Source: Hacker News / about 1 year ago
  • 3 Types of Chaos Experiments and How To Run Them
    Use load testing tools like JMeter, Gatling, or Locust to simulate demand spikes and verify that your auto-scaling rules work as expected. This will ensure that your system can handle real-world traffic patterns. - Source: dev.to / over 1 year ago
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JSON Server mentions (45)

  • Building a CRUD app with React Query, TypeScript, and Axios
    We'll be using json-server to create the REST API that we'll fetch data from. In the root of the project, create a db.json file with the contents. - Source: dev.to / about 2 years ago
  • Full Stack To Do list, a step-by-step tutorial
    Our backend will be little more than a two-way translation layer between the database and the user interface (UI). Later in this post we will identify other responsibilities of a backend but our implementation will be kept simple to demonstrate the fundamental machinery and concepts. It is worth noting the backend comes in two parts, web server and application server. Both json-server and Express are able to... - Source: dev.to / about 3 years ago
  • Improve Frontend-Backend development harmony with JSON-Server
    JSON-Server creates fake REST API with a minimum amount of configuration, it provides a simple way to create mock RESTful APIs and easily define the required endpoints, allows easy definition of the data schema in a JSON file and can serve as a reference for each figure in the project. - Source: dev.to / about 3 years ago
  • Dictionary app
    I thought about usingJson Server (hosting the repo with the words on Github to begin with), Googlesheets, or maybe Firestore (i would prefer not to use it ,to avoid extra costs just in case it gets a reasonable amount of users). It isnt a big app so I just want a simple solution for storing the words and fetching them. Source: about 3 years ago
  • Playwright - Not just for Frontend
    First, I didn't create a backend API for this example, but I used a fake API to test. I created it with json-server and json-server-auth. They are two npm packages that use a JSON file as a database and expose the database in an API. You can find more about json-server in its documentation and about json-server-auth here. - Source: dev.to / over 3 years ago
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What are some alternatives?

When comparing locust and JSON Server, you can also consider the following products

Apache JMeter - Apache JMeterโ„ข.

JSON Placeholder - JSON Placeholder is a modern platform that provides you online REST API, which you can instantly use whenever you need any fake data.

Loader.io - Loader.io is a simple cloud-based load testing service

Postman - The Collaboration Platform for API Development

AT Internet - Transform your data into action with our powerful and flexible digital analytics solution.

mocki Fake JSON API - mocki Fake JSON API is an advanced platform that offers you to create API for personal use or testing purposes.