Practice: Design an AI Image Generator (Midjourney)

AI image generation inspired by Midjourney and DALL·E: prompts accepted as queued jobs, a fleet of GPU workers running diffusion, a fast lane for paid plans and a relaxed lane for free ones, live previews from a progress cache, images in object storage behind a CDN, a cached gallery, prompt moderation and image safety checks. A teaching design.

Build this system yourself on the canvas below. Add components, connect them, and run traffic simulations to see where your design holds up and where it breaks.

Functional requirements

  • Users type a prompt and get generated images.
  • Users see the image forming while it generates.
  • Paid plans are served before free plans.
  • Users can browse their gallery and a public showcase.
  • Disallowed prompts and unsafe images are blocked.

Non-functional requirements

  • Prompt submission and status: p99 < 300ms.
  • Fast-lane images finish in under a minute at peak.
  • Scale: 10M daily users, 3K requests/s at peak, most of it viewing.
  • Generated images are never lost once shown.
  • Availability: 99.9%.
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System Design Interview
Round 1 of 4 · Architecture Design · 60:00 remaining
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Build & Stress Test
Phase 01: Thinking in Systems
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Components

User
CDN
Load Balancer
Server
Cache
Database
Blob Storage
Search Index
Queue
Worker
Rate Limiter
Service
API Gateway
Reverse Proxy
WebSocket Server
Third-party API

Inspector

Notes
Use clear names so your design intent is easy to understand.
Good
Name by business meaning
"Order API", "Restaurant Service"
Avoid
Generic names = zero signal
"Server 1", "API", "Queue"
A short description for each component makes feedback much better.
100%
Start by identifying:
  • Users & entry points
  • APIs & services
  • Databases & storage
  • Traffic flow & scale

Round 1 of 4 Architecture Design

Run a simulation to see results.

Time Remaining
60:00
System Design Interview

What are the core functional requirements?
What are the key non-functional constraints?

Questions

Start Evaluation to unlock questions.

EVALUATE MODE

Test yourself like it's the real thing.

A structured 4-module evaluation that mirrors how top companies assess system design candidates.

Architecture Design
Draw your system on the canvas. Define components, connections, and data flow.
FR & NFR Requirements
Answer functional and non-functional requirement questions about your design.
MCQ Round
Multiple choice questions testing your depth on the chosen system.
Tradeoff Analysis
Justify your design decisions and defend your architectural tradeoffs.
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Round 2 of 4
MCQ Round
Answer multiple-choice questions based on your design.

Exit Interview?

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Your progress will be saved.

Open a saved design

Select a design to load into the canvas.

My Evaluations

Your past evaluation sessions

Here’s a simple request flow that follows the expected layer order.

External User
→
Edge CDN → API Gateway → Load Balancer
→
Compute App Servers / Services
→
DataAccess Cache
→
Storage Database / Search Index
→
Async Queue → Worker

Tip: keep arrows moving forward through layers (Edge → Compute → Storage). Avoid sending storage back to compute.

Evaluation Instructions

Read the rules carefully before starting. The test auto-submits on refresh.

Before you start

  • Build your architecture on the canvas. The timer starts when you click Start Evaluation.
  • Don't forget to answer Functional Requirement and Non Functional Requirements.
  • When satisfied with your design, click Next to lock it and view the questions.
  • Please answer final step questions to complete the evaluation.

Dos

  • Do read each question carefully before answering.
  • Do include required components to maximize component coverage.
  • Do save a copy of your design if you want to keep it before submission.

Don'ts

  • Don't refresh or close the tab during an active evaluation — this will auto-submit your answers.
  • Don't switch app modes or open another tab while the evaluation is running.
  • Don't attempt to edit the design after clicking Next; the workspace will be locked.

All the best!!

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