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API Fortress Plug-in for Kong Allows Developers and QA Testers to Record and Mock Live API Calls

Expedite the delivery of new microservices while maintaining quality with API mocking with Kong

API Fortress has been a leader since 2016 in continuous API testing, providing a complete suite of cloud or on-premises tools for agile development and CI/CD workflows. Today, API Fortress announces a new plug-in to capture live API calls and create mocks by leveraging the Kong microservices API management platform.

As a global leader in open source API and microservices management, Kong joins the API Fortress ecosystem that offers targeted solutions to expedite innovation for banking, finance, insurance, digital retail, online marketplaces, online ticket sales, big data, Internet of Things, and more.

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Thousands of enterprises use Kong as their API gateway. While Kong’s enterprise customers have benefited significantly from improved security and control of their APIs, the API Fortress plug-in provides Kong’s customers with the ability to more easily virtualize APIs to allow developers and QAs to work in parallel.

Patrick Poulin, CEO at API Fortress explains:

“By working with Kong, we are leveraging an existing technology that works and is proven, and gives our customers an even easier path to creating virtualized APIs. Using API Fortress for your mocking strategy means you have a single, unified set of mocks for your entire enterprise.”

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Some of the benefits of mocking APIs are:

  • Mock paid APIs such as Google Maps or Salesforce to save money during development
  • Mock APIs as they are being developed, so that test teams can start writing API tests before the APIs are completed
  • Virtualize APIs on unreliable staging environments
  • Isolate microservices to hunt difficult bugs down.

Simone Pezzano, CTO at API Fortress remarks:

“Our plugin allows Kong to send snapshots of payloads to API Fortress which will make them into mocks. Easy and effective. Once your mocks are in, you can create functional tests leveraging stable API responses.”

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