Gatling VS foundation

Gatling: An open-source load and performance testing tool primarily designed for web applications, Gatling utilizes a simple domain-specific language (DSL) for creating and maintaining test scripts. It supports HTTP/2 and allows recording and generation of scenarios directly from a browser. The tool also provides detailed performance reports that are easy to analyze.

Performance and load testing are essential parts of GraphQL API testing. It ensures APIs can handle expected traffic volumes and respond within acceptable timeframes. You can use tools like Apache JMeter or Gatling to generate realistic loads and evaluate the API's performance under different scenarios. Techniques like batched queries and caching can help mitigate this issue.

New to the .NET community and trying to learn! I have used tools such as Apache JMeter (Java), gatling.io (Java) and Locust (Python) that are decent full featured web perf frameworks. Typically these integrate well with your code, and can be run as part of your unit/integration tests and produce offline reports

Gatling , this is what we tested concurrency with. Setting up might take a while depending on your exp. but the tool is solid.

I used SpringBoot 3.0.2, GraalVM 22 (JVM mode), a MacOS 2,6 GHz 6-Core Intel Core i7, running 1000 users for 5 minutes. The idea was to test how memory consumption and CPU usage evolve. Below, I compared the footprint of these three solutions. I collected the total count of requests, throughput, memory consumption, and CPU usage using VisualVM and Gatling.

Load test your code to simulate a production load (you can use tools like k6 or Gatling)

k6 is our preferred javascript based cloud tester for light webservices. gattling if you have (a monolith with) workflows and need more formalized code to prove/audit your testing.

It's read as "Ochikisu" and origin is the machine gun manufacturer Hotchkiss because this tool does not have as much firepower as the Gatling.

GraphQL is a query language and runtime for APIs. It provides a flexible and efficient way for clients to request and retrieve specific data from a server using a single API endpoint.

When you use technologies like GraphQL, it is trivial to derive TypeScript types. A GraphQL API is created by implementing a schema. Generating the TypeScript type definitions from this schema is simple, and you do not have to do any more work than just making the GraphQL API. This is one reason why I like GraphQL so much.

REST and GraphQL have advantages, drawbacks, and use cases for different environments. REST is for simple logic and a more structured architecture, while GraphQL is for a more tailored response and flexible request.

A Gatsby site uses Gatsby, which leverages React and GraphQL to create fast and optimized web experiences. Gatsby is often used for building static websites, progressive web apps (PWAs), and even full-blown dynamic web applications.

In my usual NodeJS tech stack, which includes GraphQL, NestJS, SQL (predominantly PostgreSQL with MikroORM), I encountered these limitations. To overcome them, I've developed a new stack utilizing Rust, which still offers some ease of development:

At Woovi we are GraphQL lovers, hence we develop many helpers around this tool to bring a good developer experience.

A query language for APIs that allows clients to request only the data they need. It provides a more flexible and efficient alternative to RESTful APIs. GraphQL provides a single endpoint for multiple data sources, making it efficient for clients to retrieve only the necessary information forexample if a Node.js microservice uses GraphQL, a client can send a query to request specific data, and the GraphQL service will fetch the required information from the underlying data sources and respond accordingly.

This approach is particularly beneficial for teams looking to enhance their digital presence without the need for extensive coding or software development. By leveraging the GraphQL API endpoint, developers can prepare and execute queries to retrieve the desired content. This makes the Headless Channel a valuable tool 🔨 for content managers and developers, offering ease of use and practicality.

To know about Graphql and why it's being used head over to for more details, Now let's cut to the chase.

GraphQL is an excellent choice for real-time data synchronization in React Native apps. By using GraphQL, you can retrieve precisely the data you need and receive updates in real-time, reducing network usage and providing a seamless user experience.