Application testing is one of the biggest barriers to achieving truly Continuous Deployments because it's use-case specific. Developers often avoid writing test cases because its time consuming, needs to be maintained for every change and metrics like coverage don't necessarily guarantee quality. In this session, we'll talk about how we could capture test cases from traffic data, how all infrastructure can be mocked automatically and how application writes could be safely replayed.

https://github.com/keploy/keploy

Keploy is an open-source no-code API Testing Platform that generates test cases and data mocks from API calls.

We'll walk through examples of how keploy can work alongside existing testing frameworks and capture test cases quickly and mock infrastructure without needing to write Unit API test cases. We'll also cover how these test cases would evolve as the application grows. The core contributors to Keploy will provide an overview of its features and capabilities, and how it is used at scale covering use-cases across microservices across various programming languages.

Outline/Structure of the Demonstration

• Shift-Left Impact of Testing
• Cost and Effort spent on different testing strategies - Manual, Automated, Record-Replay, Keploy
• Problems with Data Mocks
• Problems with Testing Infra
• How to Record API calls as Test Cases (Demo)
• How to auto-record data mocks and other infra calls
• How to Replay Test Suites with the application locally
• Noise filtering of test-cases
• Integration with native unit-test libraries
• Tracking Unit Test Coverage

Learning Outcome

• Record-Replay end-to-end API Test Cases
• Generating data mocks from API calls
• Unifying test coverage of unit tests and API tests and increasing code coverage with the test-suite
• Black-box testing of microservices
• API Chaining Tests