As a budding developer constantly searching for ways to make my workflow more efficient, I recently stumbled upon something that fundamentally changed the way I look at API testing — the Keploy Chrome Extension.
Before diving into what made Keploy a game-changer, let me paint a picture of my life before automation and how AI-powered testing helped me achieve in minutes what would usually take hours.
👨💻 Life Before Keploy: The Manual Testing Maze
In the early days of building APIs, testing felt like a side quest — something I knew I had to do but never enjoyed. Here's what manual API testing looked like:
Open Postman or Insomnia.
Manually set up each request: endpoint, headers, body.
Click “Send”, wait for a response.
Save the response (maybe).
Change some values and repeat the process.
And then came the real pain: Writing proper test cases. I had to think through each condition, edge case, and validation manually. Every bug I caught felt more like luck than strategy.
Enter Keploy: API Testing, Reinvented
When I discovered the Keploy Chrome Extension, my curiosity was piqued. It promised automatic test generation from real API calls and instant test coverage — all with a click. I had nothing to lose, so I gave it a shot.
Spoiler alert: I was blown away.
🔧 Getting Started with Keploy Chrome Extension
The process of setting up and using the extension was straightforward:
Installed the Keploy Chrome Extension.
Chose two API-rich websites to test:
https://reqres.in: A mock user data API service.
https://jsonplaceholder.typicode.com: A fake REST API for prototyping.
Opened Chrome DevTools, navigated to the Network tab, and then activated the Keploy extension.
Clicked around the site to trigger API calls — such as:
Fetching users.
Submitting POST requests.
Deleting or updating fake records.
As I interacted with the pages, the extension quietly did its job: capturing every API call and its metadata.
The Magic Moment: Auto-Generated Test Cases
Once I stopped the recording, Keploy presented me with a clean list of API calls it had tracked — and allowed me to export them as test cases with a single click.
It was surreal.
No JSON editing, no formulating requests. Keploy had built a full test suite from my real-world browsing session.
Key Takeaways and Learnings
🔍 1. Shift-Left Testing Made Easy
Keploy supports developers to bring testing earlier into the development process. As I was coding, I could run the app and generate tests on the fly — without ever opening Postman or writing test scripts manually.
⚡ 2. 100% Test Coverage in Minutes
With traditional tools, covering 100% of endpoints is near impossible without deep planning and huge time investment. Keploy captured all the APIs I used during normal browsing, giving me test coverage instantly.
🔄 3. Perfect for Regression Testing
One powerful use case is regression testing. Once tests are generated, I can re-run them whenever the API or backend changes to ensure nothing breaks.
😓 Challenges I Faced
No tool is perfect, and my first run with Keploy wasn’t either:
Initial Confusion: I wasn’t sure how to trigger the recording. A quick tutorial video helped.
Edge Case Coverage: Since Keploy captures based on real interaction, I had to manually simulate edge cases (e.g., missing fields) to get those test cases captured.
Understanding Test Output: It took a few minutes to get familiar with the test format.
But all of these were learning curves, not blockers.
My Thoughts on AI-Driven Testing:
I’m a developer, not a full-time QA engineer. My goal is to build and ship software quickly, without compromising on quality. Keploy feels like it was built exactly for people like me.
Here’s why I believe AI-driven testing is the future:
✅ It reduces the friction of writing tests.
🚀 It fits perfectly into CI/CD pipelines.
🧠 It lets me think about behavior instead of test syntax.
💡 It enables non-testers (like interns or junior devs) to contribute to QA meaningfully.
More...
Before diving into what made Keploy a game-changer, let me paint a picture of my life before automation and how AI-powered testing helped me achieve in minutes what would usually take hours.
👨💻 Life Before Keploy: The Manual Testing Maze
In the early days of building APIs, testing felt like a side quest — something I knew I had to do but never enjoyed. Here's what manual API testing looked like:
Open Postman or Insomnia.
Manually set up each request: endpoint, headers, body.
Click “Send”, wait for a response.
Save the response (maybe).
Change some values and repeat the process.
And then came the real pain: Writing proper test cases. I had to think through each condition, edge case, and validation manually. Every bug I caught felt more like luck than strategy.
Enter Keploy: API Testing, Reinvented
When I discovered the Keploy Chrome Extension, my curiosity was piqued. It promised automatic test generation from real API calls and instant test coverage — all with a click. I had nothing to lose, so I gave it a shot.
Spoiler alert: I was blown away.
🔧 Getting Started with Keploy Chrome Extension
The process of setting up and using the extension was straightforward:
Installed the Keploy Chrome Extension.
Chose two API-rich websites to test:
https://reqres.in: A mock user data API service.
https://jsonplaceholder.typicode.com: A fake REST API for prototyping.
Opened Chrome DevTools, navigated to the Network tab, and then activated the Keploy extension.
Clicked around the site to trigger API calls — such as:
Fetching users.
Submitting POST requests.
Deleting or updating fake records.
As I interacted with the pages, the extension quietly did its job: capturing every API call and its metadata.
The Magic Moment: Auto-Generated Test Cases
Once I stopped the recording, Keploy presented me with a clean list of API calls it had tracked — and allowed me to export them as test cases with a single click.
It was surreal.
No JSON editing, no formulating requests. Keploy had built a full test suite from my real-world browsing session.
Key Takeaways and Learnings
🔍 1. Shift-Left Testing Made Easy
Keploy supports developers to bring testing earlier into the development process. As I was coding, I could run the app and generate tests on the fly — without ever opening Postman or writing test scripts manually.
⚡ 2. 100% Test Coverage in Minutes
With traditional tools, covering 100% of endpoints is near impossible without deep planning and huge time investment. Keploy captured all the APIs I used during normal browsing, giving me test coverage instantly.
🔄 3. Perfect for Regression Testing
One powerful use case is regression testing. Once tests are generated, I can re-run them whenever the API or backend changes to ensure nothing breaks.
😓 Challenges I Faced
No tool is perfect, and my first run with Keploy wasn’t either:
Initial Confusion: I wasn’t sure how to trigger the recording. A quick tutorial video helped.
Edge Case Coverage: Since Keploy captures based on real interaction, I had to manually simulate edge cases (e.g., missing fields) to get those test cases captured.
Understanding Test Output: It took a few minutes to get familiar with the test format.
But all of these were learning curves, not blockers.
My Thoughts on AI-Driven Testing:
I’m a developer, not a full-time QA engineer. My goal is to build and ship software quickly, without compromising on quality. Keploy feels like it was built exactly for people like me.
Here’s why I believe AI-driven testing is the future:
✅ It reduces the friction of writing tests.
🚀 It fits perfectly into CI/CD pipelines.
🧠 It lets me think about behavior instead of test syntax.
💡 It enables non-testers (like interns or junior devs) to contribute to QA meaningfully.
More...