DEV Community: Api Test Lab

Why I Stopped Using Postman After 3 Years By Abubakkar Sajid — Founder, API Test Lab

Api Test Lab — Thu, 09 Jul 2026 06:20:20 +0000

I want to be clear about something before you read this.

Postman is not a bad product. It is actually a very good product.

I used it for three years. I recommended it to every developer I worked with. I built entire workflows around it.

And then I stopped. Completely.

Here is the honest story of why.

Year One: Postman was perfect

When I started using Postman I was building my first real backend API. Node.js, Express, MongoDB. The usual stack for someone learning.

Postman solved a problem I did not even know I had. Before it, I was testing APIs with curl commands in the terminal. One endpoint at a time. Copying and pasting tokens. Forgetting headers. Getting the body format wrong.

Postman gave me a UI. I could save requests. Build collections. Switch between environments with one click. See the response formatted nicely instead of raw JSON in a terminal.

It felt like a superpower.

I told every developer I knew about it. I put it in every project README. I assumed I would use it forever.

Year Two: The cracks started showing

By year two I was working on bigger projects. More APIs. More team members.

This is when Postman starts getting complicated.

Problem 1: Sharing collections

I built a collection for a project. 40 requests across 8 folders. Environments set up for dev, staging, production. Took me a few hours to get it right.

I wanted to share it with a colleague.

The free tier lets you share but with limited collaboration. My colleague could see the collection but the sync was unreliable. He would make a change and it would not show up on my end. I would update an environment variable and his version would be out of date.

We ended up exporting JSON files and sending them over Slack. In 2024. Via Slack messages. Like it was 2015.

Problem 2: The workspace confusion

Postman introduced workspaces. Then team workspaces. Then personal workspaces. Then public workspaces.

I spent more time understanding the workspace system than actually testing APIs. Every new team member needed an explanation. "No, that is your personal workspace. No, this one is the team workspace. No, you need to be invited to this specific workspace."

It became overhead.

Problem 3: Load testing was a completely separate problem

Every project reaches a point where you ask: can this API handle real traffic?

Postman does not answer that question.

So I had k6. Which meant I had two tools. Postman for building and testing requests, k6 for load testing. Different syntax. Different mental model. Different place to look when something breaks.

Fine. Not a dealbreaker. Just friction.

Year Three: The pricing conversation

This is the year that changed everything.

I was building API Test Lab with a small team. Three developers. All using Postman.

We hit the free tier limit.

I went to look at the pricing page.

$14 per user per month for the Basic plan.

For three developers: $42 per month. $504 per year.

For an API testing tool.

I want to be fair here. For a company with 20 engineers, $14 per person is nothing. It disappears into the budget without anyone noticing.

But for a solo developer or a small startup, $504 per year for a testing tool is real money. That is a server. That is a month of runway. That is a decision that actually matters.

I looked at what we were getting for $14 per user:

Unlimited collections ✓
Team collaboration ✓
Version control ✓
More API calls per month ✓

All things that should be free for small teams. All things that used to be free before Postman started its enterprise pivot.

I understand why they did it. Postman is a company. They need revenue. Enterprise contracts pay. Individual developers do not.

But understanding it does not mean accepting it.

The moment I decided to build something

I was debugging an API at 11pm. Load testing had to happen the next morning before a product launch. I had k6 scripts from the last project. I had Postman for the request testing. I had a third tool for monitoring.

Three browser tabs. Three different syntaxes. Three different places where things could be wrong.

I thought: why does this require three tools?

REST testing and load testing are not different problems. They are the same problem at different scales. You want to know if your API works. That is it. Whether you are testing it once or testing it with 500 concurrent users, the question is the same.

So I built API Test Lab.

Not because I was sure it would work. Not because I had a business plan. Because I was frustrated and I wanted one tool that did everything.

What I actually built

Six months later, here is what exists:

REST API testing — collections, folders, environments, variables, 13 auth types including OAuth 2.0, AWS SigV4, JWT, and all the others. Postman-style but without the workspace confusion.

GraphQL testing — schema introspection, query editor, variables, assertions. Point it at any GraphQL endpoint and it shows you the schema automatically.

Load testing — concurrent users, ramp-up time, live WebSocket metrics while the test runs. P50, P95, P99 percentiles. AI analysis of the results. All inside the same tool where you built your requests.

Mock server — create fake API endpoints that return whatever response you configure. Frontend developers can build against them while you finish the real API.

Shared collections — share a full collection via a public link. Recipients can browse every request and run them directly from their browser without creating an account. API keys and auth tokens are automatically hidden from the shared view.

Web scanner — point it at any URL and it detects what API technologies are in use. REST, GraphQL, SOAP. Useful for understanding third-party APIs before you start testing them.

Free tier available. No credit card required.

What I gave up

I should be honest about this.

Postman has things I have not built yet:

Postman Flows — visual workflow builder, genuinely impressive
Pre-request scripts — JavaScript that runs before each request
Test scripts — JavaScript assertions after each request
Monitors — scheduled collection runs with email alerts
API documentation — publish your collection as docs

These are real features that real developers use.

If your workflow depends heavily on JavaScript test scripts or Flows, API Test Lab is not ready for you yet.

I am building toward it. But I would rather tell you what is missing than oversell what exists.

The honest comparison

API Test LabPostman FreePostman BasicREST testing✅✅✅Collections✅ unlimited✅ limited✅ unlimitedEnvironments✅✅✅GraphQL tester✅✅✅Load testing✅ built in❌❌Mock server✅✅ limited✅Shared collections✅ runnable✅ view only✅AI analysis✅ Pro✅ limited✅Pre-request scripts❌ coming✅✅PriceFree / $5 / $20Free (limited)$14/user/month

The number that matters to me: $5 per month for Pro versus $14 per user per month for Postman.

For a team of three, that is $15 versus $42. Per month. Forever.

What happened when I switched

Honestly? The first week was uncomfortable.

Muscle memory is real. I kept reaching for Postman shortcuts. I kept expecting things to be in places they were not.

By week two I stopped noticing.

By month two I could not remember what the friction had been.

The thing that surprised me most: having load testing in the same tool as my API testing changed how I think about APIs. I run quick load tests much more often now because the friction of switching tools is gone. A request I was going to run once, I now run 50 times to see what happens. That habit has caught real performance problems early.

That was not something I planned for when I built it. It is just what happened when the friction disappeared.

Should you switch?

Probably not immediately.

If Postman is working for you and you are not hitting the pricing wall, stay. Switching tools has a real cost and switching for the sake of switching is a waste of time.

Switch if:

You are paying $14/user and questioning whether it is worth it
You want load testing without adding another tool to your stack
You are a solo developer or small team on a tight budget
You want to share testable collections with teammates or external developers without them needing accounts

Do not switch if:

Your workflow depends on Postman's pre-request JavaScript
You use Postman Flows extensively
Your team has deep Postman muscle memory and no real pain with it

Try it

API Test Lab is at apitestlab.org.

Free tier. No card. Sign up in under a minute.

If something is broken or missing, reply to this article or email me at hello@apitestlab.org. I read everything personally. Not a support bot. Not a team. Me.

That is one thing Postman definitely cannot offer.

Abubakkar Sajid is a solo developer and founder of API Test Lab, built in Lahore, Pakistan.

GitHub: github.com/Innocent-Developer

I built a Postman alternative. Here's what I actually learned.

Api Test Lab — Mon, 06 Jul 2026 07:16:09 +0000

I spent the last several months building API Test Lab a full-stack SaaS for API testing, load testing, and web analysis.

Not because I thought the market needed another tool.
Because I was frustrated with Postman's pricing, and I wanted to build something better.

Here's what I learned including the parts I wish someone had told me before I started.

Why I built it

Postman is great until it isn't.

The moment you need to collaborate with a team, the free tier disappears. You're looking at $14/user/month minimum. For a solo developer or a small startup, that adds up fast.

k6 and JMeter handle load testing but they're code-heavy. If you just want to throw 100 concurrent users at an endpoint and see what breaks, you don't want to write a test script first.

BlazeMeter works but costs more than most small teams can justify.

There was a gap: one tool that handles REST testing, GraphQL, load testing, and web analysis together without costing a company budget. So I built it.

What I built

API Test Lab does these things in one place:

REST API testing Postman-style collections, environments, {{variables}}, auth types
GraphQL testing schema introspection, query editor, variables, assertions
Load testing concurrent users, ramp-up, live WebSocket metrics, AI reports
Web scanner detect REST/GraphQL/SOAP endpoints from a URL
Web analysis SEO, performance, security checks
Mock server create fake endpoints for frontend teams to test against
Shared collections share a full collection with a public link, recipients can run requests directly from their browser without an account

The stack: Next.js 16 frontend, FastAPI backend, MongoDB, Google Gemini for AI features.

The technical decisions I got wrong

I over-engineered authentication before anyone asked for it

I built 13 auth types. Basic, Bearer, JWT, OAuth 1.0, OAuth 2.0, Hawk, AWS SigV4, NTLM, Digest, API Key, Akamai EdgeGrid, ASAP Atlassian.

You know what percentage of API developers need Akamai EdgeGrid? Almost none.
You know what percentage need Bearer token? Almost all.

I spent weeks on auth types that maybe 2% of users will ever touch. I should have shipped Bearer, Basic, API Key, and OAuth 2.0 in week one and moved on.

Lesson: Build what 80% of users need first. The exotic 20% can wait until someone actually asks for it.

localhost testing took me too long to figure out

My backend sits on a server. When a user sends a request to localhost:3000, my backend tries to call its own localhost not the user's machine.

This is obvious in hindsight. It took me embarrassingly long to figure out the right solution: detect local/private URLs and run them directly from the user's browser using the Fetch API, bypassing my backend entirely.

The tricky part is CORS. Local dev servers usually don't have CORS headers set. When the request fails, the browser gives you a useless "Failed to fetch" error with zero detail.

My solution: detect the CORS error specifically and show the user exactly what CORS headers to add to their server, with copy-paste code for Express, FastAPI, Django, etc.

javascript// Detect CORS error from browser
if (error instanceof TypeError && error.message.includes('Failed to fetch')) {
// Almost always a CORS error for local URLs
showCorsHelp(url)
}

Shared collections needed careful security thinking

When you share a collection, it contains API endpoints, headers, and sometimes auth tokens in the variable values.

My first approach would have exposed the sender's actual API keys to anyone with the link. Bad.

The fix: strip sensitive header values before serving the public view, replace them with {{variable_name}} placeholders. The recipient sees the structure method, URL, header names but never the actual secret values. They fill in their own values in an environment bar.

pythonSENSITIVE_HEADERS = {"authorization", "x-api-key", "x-auth-token", "cookie"}

def strip_sensitive_headers(headers):
result = []
for h in headers:
if h["key"].lower() in SENSITIVE_HEADERS:
placeholder = h["key"].lower().replace("-", "_")
result.append({**h, "value": f"{{{{{placeholder}}}}}"})
else:
result.append(h)
return result

The shared view is also browser-side execution only. No anonymous user can use my server to fire requests at third-party APIs. That would have been an abuse vector.

AI integration costs are predictable if you design for it

I integrated Google Gemini for AI features: explaining API responses, generating test assertions, load test analysis.

The concern with AI is runaway costs. Here's how I controlled it:

Context window limit: max 9,000 tokens per message (system prompt + request/response + history)
Response syntax highlighting and JSON analysis: client-side only, no AI
Conversation history: kept in browser state, not stored server-side
Free tier cap: 10 AI messages per day, enforced server-side
Rate limit: 20 messages per minute per user

At 1,000 active users each using 5 AI messages per day, cost is roughly $150/month using Gemini 1.5 Flash. Manageable.

The AI features I found most useful in practice: explaining what a 401 error means in context, and suggesting assertions after seeing a response. Not generating entire test suites that's too ambitious and rarely accurate.

The webhook security detail that matters

Freemius (my payment processor) sends a webhook when a user pays. My first implementation logged a warning on signature mismatch but continued processing anyway.

That means anyone could have sent a fake webhook and gotten a Pro account for free.

The fix is one line: reject, not warn.

pythonif not hmac.compare_digest(expected_sig, received_sig):
raise HTTPException(400, "Invalid signature")

Before: just logged a warning and continued

Always use hmac.compare_digest for timing-safe comparison. Regular string comparison is vulnerable to timing attacks.

What I'm still figuring out

Distribution.

The product works. The technical problems are mostly solved. What I don't have yet is users.

Building is the easy part or at least it's the familiar part. Getting developers to switch from a tool they already know is a different problem entirely.

A few things I'm trying:

Writing articles like this one (hi)
Being specific about the Postman pain points I'm solving, not vague "it's better"
Targeting the exact moment someone hits Postman's free tier limit

If you've successfully grown a developer tool, I'm genuinely interested in what worked.

The honest comparison

I'm not going to pretend I've built a Postman killer. Postman has a decade of development, enterprise contracts, and brand recognition.

What I have is:

API Test LabPostman FreePostman TeamBasic API testing✅✅✅Collections✅✅ (limited)✅Load testing✅❌❌GraphQL tester✅✅✅Web scanner✅❌❌Mock server✅✅ (limited)✅AI analysis✅✅ (limited)✅PriceFree / $5 / $20Free (limited)$14/user/month

The honest use case for API Test Lab: solo developers, small teams, startups who want load testing and API testing in one tool without enterprise pricing.

Try it

API Test Lab is live at apitestlab.org.

Free tier exists. No credit card required. 7-day Pro trial on signup.

If you hit a bug, I want to know. If you think a feature is missing, tell me. I'm building this in public and actively improving it.

GitHub: github.com/Innocent-Developer

Built by a solo developer in Lahore, Pakistan. All feedback welcome.