My main use case for SwaggerHub is to design and review API specifications, as I test endpoints with the help of Swagger UI, validate the request and the response schemas, and share the API documentation with other developers for integration. Recently, I used SwaggerHub in our organization mainly because as developers and data engineers, we are designing the API, collaborating with multiple other teams for the review, generating the documentation, and the interactive API documents are automatically created for us. On a day-to-day basis, we use SwaggerHub with the Swagger editor to edit and write API specifications, and because the UI is very interactive, we can also test the API endpoints, generate client SDKs and API documentation, and track version control.
We still use SwaggerHub, but we did not change much in the way we are using it, meaning just limited functionality. For us, SwaggerHub serves as a central place to publish the documentation for our API, and we stick with it because we built infrastructure around it to automatically upload the specification. Because of that small ecosystem we built, it was easy for us to keep it going. If we were to move to a different platform, it would cost us quite an important effort, and we did not want to do that. SwaggerHub is there and working for us, and we did not look for alternatives; I am sure there will be others, but we simply did not want to spend engineering time on it. API documentation is a very simple use case we have, and it is just enough for now. We basically put the APIs there and just use the rendering they have.
I have worked for Arden University, University of Sheffield, and Nanyang Technological University. For those institutions, I used Amazon AppStream for backend validations. When working for Prolifics, I used it for backend validations and data creation. In our testing, we had different sets of environments, such as Test, FT, UAT, and sometimes the Dev instance, where we performed validations. My recent project, DDI (Direct Device Interface), involved a client, Thermo Fisher Scientific, which is a product-based company. In this project, there was a Tune application they had already developed in the desktop version, and they were planning to switch it to the cloud. There, I performed API testing using Swagger and API testing. I have used automated validations and testing features to support API quality control in my projects. Automation, using Swagger validations in CI/CD tools, has helped catch schema mismatches early. In one of my recent projects, the backend team made changes to a response object by adding a new required field without updating the Swagger specification. Because we had Swagger CLI validations integrated into our Jenkins pipeline, it caught the mismatch immediately, thereby preventing breaking changes and facilitating faster feedback with automated Postman.
Director/Enterprise Solutions Architect, Technology Advisor at Kyndryl
Real User
Top 5
Feb 5, 2025
I started using SwaggerHub in its previous version, SmartMiner, with a tool called SoapUI. I used it to create mock web services to test web services and create test scripts and mock APIs. This usage began in 2009 or 2010. Later, I adopted SwaggerHub as the platform evolved into Swagger and now OpenAPI, to create APIs.
When you want to define an API with your customers using SwaggerHub, you first interact with them to understand their requirements. Then, you proceed to build the API definition. This involves creating endpoints, schemas, paths, operations, error codes, and more. Once you've agreed on the API definition, you can generate client code in any desired language or even generate a server-side implementation.
SwaggerHub securely saves API calls, thereby ensuring the confidentiality of secrets. Additionally, it facilitates the validation of APIs, making them safer to use on the server.
The company I work for purchased SwaggerHub with the intent to use it for a certain period of time. I use SwaggerHub in my company for testing purposes, especially testing the APIs.
We are using the software as a service for SwaggerHub. We use it as an entry point for API documentation. It has other features, but we don't use much of it.
We hope to use it for the design of the API and for the entry point of the documentation to help the consumers of the API in understanding the API and specifications.
IT Manager at a insurance company with 10,001+ employees
Real User
Aug 23, 2020
We use SwaggerHub to publish our APIs. We also integrate SmartBear ReadyAPI with Swagger. We use it to manage our APIs. When we develop an API, we then integrate it with SwaggerHub. Centene is a large corporation with plenty of automation so there are various development teams across Centene who use this solution for various use cases. Normally, they publish their APIs on SwaggerHub for seamless integration with SmartBear and ReadyAPI. This allows us to perform detailed end-to-end automation testing.
SwaggerHub streamlines API management with features like centralized management and real-time collaboration, enhancing team efficiency. Its user-friendly interface facilitates API design and testing, offering seamless integration with third-party tools for enhanced teamwork.SwaggerHub provides centralized API definitions enabling easy access and reducing manual errors, which accelerates development. Its role-based access and versioning foster better communication and control among teams....
My main use case for SwaggerHub is to design and review API specifications, as I test endpoints with the help of Swagger UI, validate the request and the response schemas, and share the API documentation with other developers for integration. Recently, I used SwaggerHub in our organization mainly because as developers and data engineers, we are designing the API, collaborating with multiple other teams for the review, generating the documentation, and the interactive API documents are automatically created for us. On a day-to-day basis, we use SwaggerHub with the Swagger editor to edit and write API specifications, and because the UI is very interactive, we can also test the API endpoints, generate client SDKs and API documentation, and track version control.
We still use SwaggerHub, but we did not change much in the way we are using it, meaning just limited functionality. For us, SwaggerHub serves as a central place to publish the documentation for our API, and we stick with it because we built infrastructure around it to automatically upload the specification. Because of that small ecosystem we built, it was easy for us to keep it going. If we were to move to a different platform, it would cost us quite an important effort, and we did not want to do that. SwaggerHub is there and working for us, and we did not look for alternatives; I am sure there will be others, but we simply did not want to spend engineering time on it. API documentation is a very simple use case we have, and it is just enough for now. We basically put the APIs there and just use the rendering they have.
I have worked for Arden University, University of Sheffield, and Nanyang Technological University. For those institutions, I used Amazon AppStream for backend validations. When working for Prolifics, I used it for backend validations and data creation. In our testing, we had different sets of environments, such as Test, FT, UAT, and sometimes the Dev instance, where we performed validations. My recent project, DDI (Direct Device Interface), involved a client, Thermo Fisher Scientific, which is a product-based company. In this project, there was a Tune application they had already developed in the desktop version, and they were planning to switch it to the cloud. There, I performed API testing using Swagger and API testing. I have used automated validations and testing features to support API quality control in my projects. Automation, using Swagger validations in CI/CD tools, has helped catch schema mismatches early. In one of my recent projects, the backend team made changes to a response object by adding a new required field without updating the Swagger specification. Because we had Swagger CLI validations integrated into our Jenkins pipeline, it caught the mismatch immediately, thereby preventing breaking changes and facilitating faster feedback with automated Postman.
I started using SwaggerHub in its previous version, SmartMiner, with a tool called SoapUI. I used it to create mock web services to test web services and create test scripts and mock APIs. This usage began in 2009 or 2010. Later, I adopted SwaggerHub as the platform evolved into Swagger and now OpenAPI, to create APIs.
When you want to define an API with your customers using SwaggerHub, you first interact with them to understand their requirements. Then, you proceed to build the API definition. This involves creating endpoints, schemas, paths, operations, error codes, and more. Once you've agreed on the API definition, you can generate client code in any desired language or even generate a server-side implementation.
SwaggerHub securely saves API calls, thereby ensuring the confidentiality of secrets. Additionally, it facilitates the validation of APIs, making them safer to use on the server.
The company I work for purchased SwaggerHub with the intent to use it for a certain period of time. I use SwaggerHub in my company for testing purposes, especially testing the APIs.
We are using the software as a service for SwaggerHub. We use it as an entry point for API documentation. It has other features, but we don't use much of it.
We use the solution to develop and test the APIs.
We hope to use it for the design of the API and for the entry point of the documentation to help the consumers of the API in understanding the API and specifications.
We use SwaggerHub to publish our APIs. We also integrate SmartBear ReadyAPI with Swagger. We use it to manage our APIs. When we develop an API, we then integrate it with SwaggerHub. Centene is a large corporation with plenty of automation so there are various development teams across Centene who use this solution for various use cases. Normally, they publish their APIs on SwaggerHub for seamless integration with SmartBear and ReadyAPI. This allows us to perform detailed end-to-end automation testing.