APIs are the backbone of modern web apps, but testing them? That’s where many devs, including me, used to burn time.
Recently, I discovered Keploy, an AI-powered API testing tool, and decided to try it out on two API-heavy websites I use often: YouTube and Amazon. Spoiler: I went from zero test coverage to 100% functional coverage of real-world user flows — in minutes.
Here’s how it went, what I learned, and why I think AI might just be the future of API testing.
Why YouTube and Amazon?
Both of these websites are API monsters:
- YouTube: Every search, video load, comment, and recommendation is driven by background API calls.
- Amazon: From product listings to price and shipping info, nearly everything on a product page is dynamically fetched.
Perfect targets to stress test an API testing tool.
Getting Started with Keploy
Setting up was smooth:
- Installed the Keploy API Testing Chrome Extension.
- Browsed YouTube and Amazon like a normal user — searched, clicked, scrolled.
- Keploy silently recorded the API calls in real-time.
Within seconds, I had a test suite auto-generated from real user interactions.
Testing YouTube
Keploy captured calls like:
-
GET /search(video search) -
GET /watch(load video details) -
GET /comments(load comments)
I replayed these through Keploy. It verified responses and flagged mismatches, especially for dynamic values like timestamps or suggestion IDs.
✨ What stood out:
- Keploy caught minor changes I wouldn’t notice manually.
- No Postman. No scripting. Just record and replay.
Testing Amazon
Amazon was even more API-rich. Keploy captured:
- Product list API (
search) - Product detail API (price, availability, ratings)
- Shipping estimate API
Amazon’s APIs return a lot of dynamic data (e.g., offer IDs, tracking info), which occasionally caused false negatives on replays. Still, a few tweaks to filters and I was golden.
Manual vs. Keploy: A Quick Comparison
| Task | Manual Testing | Keploy + AI |
|---|---|---|
| Capture API traffic | DevTools/Charles, manual | Automatic |
| Write test scripts | Manually, one by one | Auto-generated |
| Handle dynamic values | Tedious | Smart comparison engine |
| Replay tests | Postman/cURL | One-click in dashboard |
| Time spent | Hours | ~10 minutes |
Challenges I Faced
- Dynamic tokens & sessions: Amazon's APIs return session-bound data. Replays required small tweaks or tokens.
- Authentication: Some calls are gated. Keploy works best during real authenticated sessions.
- Noise filtering: Sites like Amazon fire tons of tracking APIs — it helps to focus only on the key business logic calls.
Why I’m Excited About AI Testing
Keploy flipped the API testing game for me. Here's what stood out:
✅ Zero test writing — everything came from real user sessions.
✅ Quick feedback loops — replaying tests after changes is painless.
✅ High confidence — I actually trust my coverage now.
As devs, we’re always chasing better velocity without compromising quality. AI tools like Keploy seem to be closing that gap — fast.
Final Thoughts
If you’re a dev or tester who’s still manually writing API tests or maintaining brittle test suites — give Keploy a shot.
✅ Record real traffic
✅ Auto-generate tests
✅ Replay and verify responses
It's not magic. But it kind of feels like it.
Your turn: Have you used AI-based tools for API testing?
Drop your thoughts in the comments — I’d love to compare notes.
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