Mocklantis: Modern API Mocking Made Simple

Source: Dev.to

The Hidden Cost of Dependencies: Why Mocking Matters

Working with microservices architecture means living with dependencies. Your service talks to another service, that service talks to three more, and somewhere in this chain, there’s a payment gateway, a notification service, and probably a third‑party API with aggressive rate limits.

When everything is up and running, life is good. But here’s the question nobody likes to ask: what happens when they’re not?

• How do you test a timeout scenario?
• How do you simulate a 503 from the payment service?
• How do you know your retry logic actually works before it matters?

These questions are uncomfortable because the honest answer is often “we don’t” or “we hope for the best.”

The Problems We Don’t Talk About Enough

In microservices development, there are friction points that slow everyone down but rarely get addressed properly.

Dependencies block progress. Your service is ready, but the one you depend on isn’t. Maybe another team is still building it. Maybe it’s a third‑party API with sandbox limitations. Maybe it’s a payment gateway that only behaves correctly in production. Whatever the reason, you’re waiting for something outside your control.

Unit tests create false confidence. Tests pass. Green checkmarks everywhere. But passing unit tests means your code works in isolation—with mocked interfaces that behave exactly as you programmed them. Real services don’t behave that way. They timeout. They return unexpected responses. They fail at 3 AM on a Sunday.

Simulating failure is harder than building features. You need to verify what happens when a downstream service returns a 503, test your circuit breaker, and confirm your fallback logic works. Creating these conditions is where teams give up and hope monitoring will catch problems in production.

Everyone mocks differently. One developer hard‑codes JSON responses. Another writes a small Express server. Someone else uses a CLI tool with YAML configs. The staging environment is shared by four teams and constantly broken. “Works on my machine” becomes the team motto.

These aren’t rare situations. This is Tuesday for most backend teams.

It’s Not Just Microservices

Dependency problems aren’t exclusive to microservices architecture. They exist wherever two systems need to talk to each other.

• Frontend teams waiting for backend APIs to be ready.
• Mobile apps blocked because the server endpoint isn’t deployed yet.
• Integration projects stalled because a third‑party system has rate limits or sandbox restrictions.

The pattern is the same: your work is done, but you can’t verify it because something else isn’t available. You’re blocked not by your own code, but by external factors.

This is where mocking becomes essential—not as a nice‑to‑have, but as a fundamental part of how software gets built and tested.

Why Mocking Has a Bad Reputation

The concept of mocking is simple: create fake services that return predictable responses, test your code against them, and simulate any scenario you need.

On paper, it’s the perfect solution. In practice, most teams avoid it.

Traditional mocking means configuration files (YAML or JSON), CLI commands, and learning another tool’s syntax. Every time you change a response you have to restart servers or reload configs.

“You’ve already written the feature. You’ve already written unit tests. Now you need more setup just to simulate a service that someone else should have finished?”

The friction isn’t worth it, so teams test against unstable staging environments or skip integration testing entirely. Neither is good, but both feel more practical than fighting mock‑server configuration.

Mocklantis changes this.
Mocklantis is a free desktop application for creating mock servers. It runs locally on macOS, Windows, and Linux and supports HTTP/REST endpoints, WebSocket connections, Server‑Sent Events, and webhooks—all in one application.

What makes it different is the experience:

• No configuration files.
• No CLI commands.
• No YAML schemas to learn.

You open the app, create a server, add endpoints, and start testing. Changes apply instantly—no restarts, no rebuilds. Everything is visual and immediate. The distance between “I want to test this scenario” and “I’m testing this scenario” becomes seconds instead of hours.

Mocklantis in Action

The workflow is straightforward:

1. Open the application.

2. Create a server on port 8080.

3. Add an endpoint, e.g.:

   POST /payments/process

4. Type a JSON response and set the status code. Done. The endpoint is live and your service can call it immediately.

Testing timeout handling – add a delay; the change applies instantly.
Testing error scenarios – change the status code to 503 and watch how your service responds.

Dynamic Data

Mocklantis supports template variables—UUIDs that regenerate per request, timestamps, emails, names, and custom patterns. Fourteen different random variable types are built in.

WebSockets

Mocklantis offers three WebSocket modes:

• Conversational – request‑response patterns.
• Streaming – continuous data flow.
• Triggered streaming – a client message triggers a sequence of responses (perfect for AI‑style interactions).

Server‑Sent Events (SSE)

Configure events, set intervals, and define on‑connect messages—ideal for testing token‑by‑token streaming in AI applications.

Webhooks

When an endpoint is called, Mocklantis can fire HTTP requests to other URLs with configurable auth, retry logic, and delays.

Everything is visual, immediate, and requires no custom server code.

Small Features, Big Impact

Some capabilities sound minor until you actually need them. Mocklantis gets these details right.

• Live updates without restart – modify responses, add delays, switch status codes while your service is running.
• Automatic persistence – every change saves immediately (500 ms debounce); close the app and everything is exactly as you left it.
• Real‑time request logs – see every request hitting your mock server, including headers, bodies, and timing.
• Proxy mode – mock some endpoints and forward others to real services, isolating specific dependencies while keeping the rest of your stack intact.
• Import from anywhere – paste a cURL command, import an OpenAPI spec, or load a .mock file.
• Local‑only operation – everything runs on localhost; no cloud accounts, no data leaves your machine, and no concerns about sensitive test data being logged elsewhere.

Individually these features aren’t revolutionary, but together they remove the friction that stops teams from testing properly.

The Friction Problem

Developer tools follow a pattern: more power means more complexity—steeper learning curves, thicker documentation, and more Stack Overflow questions. Mocklantis flips that script by delivering powerful mocking capabilities through a simple, visual interface that requires no code, no config files, and no external services. The result is a tool that lets developers spend less time fighting their tooling and more time building reliable software.