🚀 From Clueless to Confident: My First Week with Keploy for API Testing

I’ll be honest—I had zero experience with proper API testing until just recently. Sure, I’ve built a few APIs here and there using Go and knew how to check responses in Postman or curl. But writing tests? Especially integration or E2E ones? I always meant to do it... but never really did. Mostly because it felt tedious, confusing, and well, manual.

That changed this week when I stumbled upon Keploy—an AI-powered API testing tool—and I decided to try it out for a workshop project. Here's what happened 👇

🤯 My Usual API Testing (Or Lack of It)

Before Keploy, my “testing strategy” was mostly just:

Run the backend.
Hit endpoints manually using Postman.
Check console logs or database rows to “see if it worked”.

That obviously didn’t scale, and I knew it wasn’t the right way to test things—but setting up full test suites (mocking, database seeding, etc.) felt like a huge barrier. Plus, every time the API changed, I’d have to go update a bunch of test cases by hand. 😵‍💫

💡 First Time Using Keploy

Keploy promised “automated test generation” just by using my app normally. Skeptical but curious, I decided to give it a shot:

I ran my backend app (a simple anime watchlist built in Go).
Installed the Keploy CLI and attached it to my app.
Used the app like a real user—adding, updating, deleting anime records.
Keploy silently recorded all the API calls and generated test cases and mocks from real traffic!

No writing test functions. No crafting request/response payloads. No environment setup nightmares.

⚙️ Running the Tests

I then ran keploy test—and to my surprise, it spun up the same traffic I had recorded, validated the responses and even simulated the same DB behavior.

What blew me away was the coverage: I basically hit a few endpoints, and Keploy had already generated 70–80% test coverage just from that. I wasn’t even trying!

With a few more user interactions, I pushed it to nearly 100%.

😅 What Was Hard

Of course, it wasn’t completely smooth:

Getting Keploy to authenticate with the cloud dashboard took a few tries (pro tip: you need a valid API key from Keploy’s dashboard).
My app uses Docker-based databases, so I had to configure ports and ensure both read/write databases were accessible.
Since I was new to this, understanding what was going on “under the hood” took some reading.

But compared to writing tests manually from scratch? This was 10x easier.

✨ What Excites Me Now

Confidence in my APIs: Every time I make changes, I can rerun the suite and trust that it’ll catch regressions.
Speed: Recording tests while I just use the app is wild. I’m not wasting hours writing repetitive assertions.
Scalability: If I work on a bigger team, everyone benefits from shared test coverage without needing every dev to be a testing expert.

🧠 Final Thoughts (From a Beginner)

I’m still new to API testing, but Keploy made it feel like I wasn’t. It feels more like having a smart assistant watching over your app and creating tests for you, rather than something you need to fight with.

If you’re like me—someone who avoided testing because it felt like a chore—give Keploy a shot. You’ll go from 0 to hero faster than you think.