apiclarity VS swagger-ui

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.

If you go to APIClarity, the first thing you’ll see is the source code (Figure 1), followed by some documentation at the bottom.

This feature is available in the open-source tool APIClarity, as part of the OpenClarity initiative.

Hi, I would also like to add another tool I'm contributing to at work (cisco) called APIClarity [1]. It aims at reconstructing swagger specifications of REST microservices running in K8S, but can also be run locally.

This is a challenging task and we don't support OpenAPI v3 specs yet (we are working on it).

Feel free to have a look, and get ideas from it :)

We'll also be presenting it at next Kubecon 2022.

[1]: https://github.com/openclarity/apiclarity

For example, APIClarity is a tool that observes all of the API traffic within your Kubernetes environment. Based on traffic observation, APIClarity infers an OpenAPI description for those APIs. This is especially helpful if the API creator never defined or provided such a description. It also surfaces potential problems with existing APIs, such as requests made to undocumented, shadow APIs or continued use of deprecated, zombie APIs. If you’re getting started on the path toward OAS compliance, then tools like APIClarity can be a great source of insight and observability.

The fundamental first step to solving this problem is to create an API spec and use it to audit and document the APIs your apps use. Ideally, we would create an API spec simply by observing API traffic in real-world applications. In the past, there was no simple, scalable, and open-source tooling capable of doing this. Now, we have APIClarity—an open-source API traffic visibility tool for Kubernetes (K8s) clusters. It’s purpose-built to address the gap and enable API reconstruction through observation.

Swagger is a fantastic open-source toolset that's perfect for developing and describing RESTful APIs. It offers you a user-friendly interface to understand a service's capabilities without needing to dig into the code. It even provides a way for you to interact directly with the API, which means you get to test its functionality.

The API had an OpenAPI endpoint built with Swagger where I could download a JSON specification file for the API.

Swagger is a widely used tool for documenting and testing APIs.

Swagger is an open-source software framework that implements the OpenAPI Specification—an API description format for REST APIs. The OpenAPI Specification defines a standard, language-agnostic interface to HTTP APIs, enabling both humans and computers to discover and understand the capabilities of the API.

Mocking and Testing: Once the API design is complete, developers create mock APIs to simulate the behavior of the actual services. This early testing phase helps identify any issues or mismatches between design and implementation before substantial development efforts are invested. Tools like Postman or Swagger are invaluable for API testing and validation.

import fp from "fastify-plugin"; import swagger from "@fastify/swagger"; export default fp(async (fastify) => { fastify.register(swagger, { openapi: { info: { tags: [ { name: "drinks", description: "Drink-related endpoints", externalDocs: { description: "Find out more", url: "http://swagger.io", }, }, ], }, }, }); });

A very requested feature for Sharkio was the auto-generation of OpenAPI documentation using the recorded HTTP requests - to create standardized documentation.

Automation QA is a lot of the same duties as manual QA, but instead of writing and executing the test plans manually, we create and update automated tests that can run those validations programmatically, for example by using Selenium to automatically fill out and submit forms for a web application, or using Postman and/or Swagger to generate an API conversation test.