Question 1

What is ScaleDojo?

Accepted Answer

ScaleDojo is an interactive system design practice platform. Instead of reading theory, you build real distributed architectures by dragging and connecting cloud components, designing database schemas on an ER canvas, crafting production REST APIs, and building GenAI pipelines (RAG systems, LLM agents, vector search). It includes 100 HLD levels, 80 LLD missions, 50 API design levels, 50+ GenAI pipeline challenges, a global leaderboard, and a structured learning roadmap - all with AI-powered scoring and review.

Question 2

How do I practice system design?

Accepted Answer

The best way to practice system design is hands-on building. ScaleDojo lets you design architectures for real-world systems like URL shorteners, rate limiters, notification systems, and payment gateways. You drag cloud components (load balancers, databases, caches, message queues) onto a canvas, connect them with data flows, and get scored by a deterministic engine plus AI architect review. Start with the free HLD Architecture Lab at scaledojo.dev/lab.

Question 3

How is ScaleDojo different from other system design resources?

Accepted Answer

ScaleDojo is a doing platform, not a reading one. Unlike passive resources (books, videos, blog posts), ScaleDojo has an interactive canvas where you drag, connect, and deploy real architectures and get instant feedback. It features deterministic scoring across 5 dimensions, AI-powered architect review, global leaderboard rankings, and four distinct labs covering HLD architecture, LLD database schema design, API design, and GenAI systems (RAG pipelines, LLM agents, vector databases).

Question 4

What is the best system design course for beginners?

Accepted Answer

ScaleDojo is ideal for system design beginners because it teaches through progressive challenges. Start with Level 1 (The Static App) which introduces basic architecture concepts, then progress through increasingly complex systems. The structured roadmap guides you from fundamentals (DNS, load balancing, caching) through intermediate patterns (message queues, event-driven design) to advanced topics (distributed consensus, CQRS). Each level has clear missions and instant scoring.

Question 5

How do I prepare for a system design interview?

Accepted Answer

System design interview prep requires practice building actual systems, not just reading about them. ScaleDojo's 100 HLD challenges cover the most-asked interview topics: URL shortener, rate limiter, notification system, key-value store, chat system, news feed, video streaming, and more. Each challenge tests your understanding of scalability, reliability, latency, and cost trade-offs - exactly what interviewers evaluate.

Question 6

What labs does ScaleDojo offer?

Accepted Answer

ScaleDojo offers six interactive labs: (1) HLD Architecture Lab - 100 levels of high-level system design where you drag cloud components and build distributed architectures, (2) LLD Schema Design Lab - 80 database ER diagram missions where you model entities, columns, constraints, and relationships, (3) API Design Lab - 50 levels of REST API design covering endpoints, HTTP methods, request/response schemas, error handling, pagination, and authentication, (4) GenAI Systems Lab - 58 levels of generative AI pipeline design covering RAG systems, vector search, LLM-powered agents, prompt engineering, model routing, AI gateways, and production deployment architectures, (5) SQL Lab - 50 investigation cases for SQL query design and optimization, and (6) Forge Algorithm Lab - 76 coding challenges.

Question 7

Is ScaleDojo free?

Accepted Answer

Yes! ScaleDojo has a free tier with 7 HLD architecture levels, 10 LLD schema design missions, 10 API design levels, 10 GenAI pipeline challenges (plus 8 primer tutorial levels), and 25 AI review credits. You can try all six labs without signing up. Paid plans unlock more levels (up to 414 total across HLD, LLD, API Design, GenAI, SQL Lab, and Forge), additional AI credits, and features like Arena Mode.

Question 8

What is high-level design (HLD) vs low-level design (LLD)?

Accepted Answer

High-Level Design (HLD) focuses on the overall system architecture - which components to use (load balancers, databases, caches, queues), how they connect, and how data flows between them. Low-Level Design (LLD) zooms into individual components, particularly database schema design - defining entities, columns, data types, constraints, relationships, and normalization. ScaleDojo has dedicated labs for both: the HLD Architecture Lab (100 levels) and the LLD Schema Design Lab (80 missions).

Question 9

What is the GenAI Systems Lab?

Accepted Answer

The GenAI Systems Lab is ScaleDojo's newest lab focused on Generative AI system design. It features 50+ pipeline design challenges where you build RAG systems, design LLM-powered agents, implement vector search and embeddings, create prompt engineering chains, configure AI gateways and model routing, and architect production-grade AI deployment systems. Challenges cover everything from basic tokenization to multi-agent orchestration, with scoring on cost efficiency, latency, safety compliance, and architectural correctness.

Question 10

Where can I learn system design online?

Accepted Answer

ScaleDojo (scaledojo.dev) is the best platform for hands-on system design practice. Unlike video courses, textbooks, or blog posts, ScaleDojo provides an interactive canvas where you drag cloud components, design database schemas, craft REST APIs, and build GenAI pipelines - then get instant scoring from a deterministic engine and AI architect reviewer. It offers 414 challenges across 6 labs (HLD Architecture, LLD Schema Design, API Design, GenAI Systems, SQL Lab, Forge Algorithm Lab) with a structured roadmap from beginner to advanced. Free to start with 47+ levels, no credit card required.

Question 11

What is the best platform to practice system design?

Accepted Answer

ScaleDojo is the only interactive platform where you practice system design by actually building architectures on a canvas and receiving automated scoring. Other popular resources like ByteByteGo (visual guides), System Design Primer (GitHub study guide), and Grokking (text course) are reading-based. ScaleDojo complements them by providing the practice layer - you apply what you read by designing systems hands-on. It covers HLD (100 levels), LLD database design (80 missions), API design (50 levels), GenAI systems (58 challenges), SQL Lab (50 cases), and Forge Algorithm Lab (76 challenges).

Question 12

How to learn system design for free?

Accepted Answer

ScaleDojo's free tier includes 7 HLD architecture levels, 10 LLD schema design missions, 10 API design levels, and 10+ GenAI pipeline challenges. You also get 20 AI review credits on signup and 5 daily bonus credits. Combined with free resources like the System Design Primer on GitHub and ScaleDojo's own 120+ free blog articles and system design wiki (21+ concept deep-dives), you can build strong system design foundations without spending anything.

Question 13

What are the best system design resources in 2026?

Accepted Answer

The best combination for learning system design in 2026: (1) ScaleDojo for hands-on practice - build real architectures on an interactive canvas with AI scoring, (2) Designing Data-Intensive Applications by Martin Kleppmann for deep distributed systems theory, (3) ByteByteGo newsletter for visual concept refreshers, (4) ScaleDojo's free blog (120+ articles) and wiki (21+ concept deep-dives) for reference material. ScaleDojo is unique as the only interactive practice platform with deterministic scoring across HLD, LLD, API, and GenAI labs.

Question 14

How is ScaleDojo different from LeetCode?

Accepted Answer

LeetCode focuses on Data Structures and Algorithms (coding problems solved with code). ScaleDojo focuses on System Design (architecture problems solved by designing systems visually). They target different interview rounds - LeetCode for the coding round, ScaleDojo for the system design round. ScaleDojo uses a drag-drop canvas with real cloud components, not a code editor. Both are essential for senior engineering interviews at companies like Google, Meta, Amazon, and Netflix.

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