Introduction
Roblox is a user-generated content platform where users can create, publish, and play games and experiences. The platform hosts millions of user-created experiences, supports real-time multiplayer gameplay, provides creator tools (Roblox Studio), and includes social features, monetization, and content moderation. Designing Roblox requires handling massive scale: millions of daily active users, billions of hours of engagement, real-time multiplayer with low latency, and petabytes of user-generated content.
This post provides a detailed walkthrough of designing Roblox, covering key features, scalability challenges, and architectural decisions. This is a common system design interview question that tests your understanding of distributed systems, real-time multiplayer, user-generated content platforms, game engines, social features, and content moderation.
Table of Contents
- Problem Statement
- Requirements
- Capacity Estimation
- Core Entities
- API
- Data Flow
- Database Design
- High-Level Design
- Deep Dive
- Summary
Problem Statement
Design Roblox, a user-generated content platform for games and experiences with the following features:
- User accounts and authentication
- Create and publish games/experiences
- Real-time multiplayer gameplay
- 3D rendering and physics simulation
- Social features (friends, chat, groups)
- Creator tools (Roblox Studio)
- Asset marketplace (models, clothing, accessories)
- Monetization (Robux currency, developer exchange)
- Content discovery and recommendation
- Content moderation and safety
Scale Requirements:
- 200 million+ monthly active users
- 70 million+ daily active users
- 10 million+ concurrent users
- Millions of user-created experiences
- Billions of hours of engagement per month
- Petabytes of user-generated content
- Real-time multiplayer with < 100ms latency
- Must support cross-platform (PC, mobile, console)
Requirements
Functional Requirements
Core Features:
- User Management: Registration, authentication, profiles
- Experience Creation: Create games using Roblox Studio
- Experience Publishing: Publish and host experiences
- Real-Time Multiplayer: Support multiple players in same experience
- 3D Rendering: Render 3D graphics and environments
- Physics Simulation: Real-time physics calculations
- Social Features: Friends, chat, groups, follow creators
- Asset Marketplace: Buy/sell models, clothing, accessories
- Monetization: Robux currency, in-experience purchases, developer exchange
- Discovery: Browse, search, and discover experiences
- Content Moderation: Automated and manual moderation
- Cross-Platform: Support PC, mobile, console
Out of Scope:
- Mobile app development (focus on backend/platform)
- Specific game mechanics (focus on platform)
- Payment processing (assume payment gateway)
- Video streaming (focus on real-time gameplay)
Non-Functional Requirements
- Availability: 99.9% uptime
- Reliability: No data loss, consistent gameplay
- Performance:
- Game server latency: < 100ms
- Experience load time: < 5 seconds
- Asset download: < 2 seconds
- Chat message delivery: < 200ms
- Scalability: Handle 10M+ concurrent users
- Consistency: Strong consistency for transactions, eventual for social
- Security: Protect user data, prevent cheating, content moderation
- Cross-Platform: Support multiple platforms seamlessly
Capacity Estimation
Traffic Estimates
- Monthly Active Users (MAU): 200 million
- Daily Active Users (DAU): 70 million
- Peak Concurrent Users: 10 million
- Experiences: 50 million+
- Daily Experience Launches: 100 million+
- Chat Messages per Day: 1 billion+
- Asset Downloads per Day: 500 million+
- Peak Requests per Second: 500,000+
- Average Session Duration: 2.5 hours
Storage Estimates
User Data:
- 200M users × 5KB = 1GB
- User profiles, preferences, settings
Experience Data:
- 50M experiences × 10MB average = 500TB
- Game code, assets, configurations
User-Generated Assets:
- 1B assets × 1MB average = 1PB
- Models, clothing, accessories, decals
Chat Messages:
- 1B messages/day × 200 bytes = 200GB/day
- 30-day retention: ~6TB
- 1-year archive: ~73TB
Gameplay Data:
- 10M concurrent × 1KB/sec × 3600 sec = 36TB/hour
- Real-time state, not persisted
Total Storage: ~1.5PB
Bandwidth Estimates
Normal Traffic:
- 10M concurrent × 50KB/s = 500GB/s = 4Tbps
- Game state updates, asset streaming
Peak Traffic:
- 10M concurrent × 100KB/s = 1TB/s = 8Tbps
Asset Downloads:
- 500M downloads/day × 1MB = 500TB/day = ~5.8GB/s = ~46Gbps
Total Peak: ~8Tbps
Core Entities
User
user_id(UUID)username(VARCHAR, unique)display_name(VARCHAR)email(VARCHAR)password_hash(VARCHAR)robux_balance(INT)avatar_data(JSON)created_at(TIMESTAMP)updated_at(TIMESTAMP)
Experience (Game)
experience_id(UUID)creator_id(user_id)title(VARCHAR)description(TEXT)thumbnail_url(VARCHAR)genre(VARCHAR)max_players(INT)is_public(BOOLEAN)visits(BIGINT)likes(BIGINT)favorites(BIGINT)created_at(TIMESTAMP)updated_at(TIMESTAMP)
Experience Asset
asset_id(UUID)experience_id(UUID)asset_type(model, script, sound, texture, etc.)asset_url(VARCHAR)file_size(BIGINT)version(INT)created_at(TIMESTAMP)
Game Server Instance
server_id(UUID)experience_id(UUID)server_ip(VARCHAR)server_port(INT)current_players(INT)max_players(INT)region(VARCHAR)status(active, full, closing)created_at(TIMESTAMP)
Player Session
session_id(UUID)user_id(UUID)experience_id(UUID)server_id(UUID)joined_at(TIMESTAMP)left_at(TIMESTAMP)play_duration(INT, seconds)
Friend Relationship
friendship_id(UUID)user_id(UUID)friend_id(UUID)status(pending, accepted, blocked)created_at(TIMESTAMP)
Chat Message
message_id(UUID)user_id(UUID)experience_id(UUID)server_id(UUID)message_text(TEXT)message_type(chat, whisper, system)moderation_status(pending, approved, rejected)created_at(TIMESTAMP)
Asset Marketplace Item
item_id(UUID)creator_id(user_id)item_type(model, clothing, accessory, gamepass)title(VARCHAR)description(TEXT)price_robux(INT)sales_count(INT)is_approved(BOOLEAN)created_at(TIMESTAMP)
Transaction
transaction_id(UUID)user_id(UUID)transaction_type(purchase, sale, refund)item_id(UUID)robux_amount(INT)status(pending, completed, failed)created_at(TIMESTAMP)
API
1. Launch Experience
POST /api/v1/experiences/{experience_id}/launch
Request:
{
"user_id": "uuid",
"region": "us-west"
}
Response:
{
"server_id": "uuid",
"server_ip": "192.168.1.100",
"server_port": 53640,
"join_token": "encrypted_token",
"asset_urls": [
"https://cdn.roblox.com/assets/..."
]
}
2. Join Game Server
POST /api/v1/servers/{server_id}/join
Request:
{
"user_id": "uuid",
"join_token": "encrypted_token"
}
Response:
{
"session_id": "uuid",
"server_connection_info": {
"ip": "192.168.1.100",
"port": 53640,
"encryption_key": "..."
},
"current_players": 5,
"max_players": 20
}
3. Send Chat Message
POST /api/v1/chat/messages
Request:
{
"user_id": "uuid",
"experience_id": "uuid",
"server_id": "uuid",
"message_text": "Hello, everyone!",
"message_type": "chat"
}
Response:
{
"message_id": "uuid",
"status": "pending_moderation",
"created_at": "2025-11-14T10:00:00Z"
}
4. Get Experience Details
GET /api/v1/experiences/{experience_id}
Response:
{
"experience_id": "uuid",
"title": "Adopt Me!",
"creator": {
"user_id": "uuid",
"username": "DreamCraft"
},
"description": "...",
"thumbnail_url": "...",
"visits": 50000000,
"likes": 1000000,
"favorites": 500000,
"max_players": 20,
"genre": "simulation",
"created_at": "2020-01-01T00:00:00Z"
}
5. Search Experiences
GET /api/v1/experiences/search?q=adopt&genre=simulation&limit=20&offset=0
Response:
{
"experiences": [
{
"experience_id": "uuid",
"title": "Adopt Me!",
"creator": {...},
"visits": 50000000,
"thumbnail_url": "..."
}
],
"total": 100,
"limit": 20,
"offset": 0
}
6. Purchase Asset
POST /api/v1/marketplace/purchase
Request:
{
"user_id": "uuid",
"item_id": "uuid",
"price_robux": 100
}
Response:
{
"transaction_id": "uuid",
"status": "completed",
"new_robux_balance": 900,
"purchased_item": {...}
}
7. Upload Experience Asset
POST /api/v1/experiences/{experience_id}/assets
Request:
{
"asset_type": "model",
"asset_data": "base64_encoded_data",
"version": 1
}
Response:
{
"asset_id": "uuid",
"asset_url": "https://cdn.roblox.com/assets/...",
"file_size": 1024000,
"status": "uploaded"
}
Data Flow
Experience Launch Flow
- User Launches Experience:
- User clicks “Play” on an experience
- Client sends launch request to API Gateway
- API Gateway routes to Experience Service
- Server Selection:
- Experience Service:
- Gets user’s region preference
- Queries Game Server Manager for available servers
- Selects server with capacity and lowest latency
- Creates player session
- Experience Service:
- Asset Loading:
- Experience Service:
- Gets experience asset list
- Generates CDN URLs for assets
- Returns asset URLs to client
- Experience Service:
- Server Connection:
- Client:
- Downloads assets from CDN
- Connects to game server
- Establishes WebSocket connection
- Starts gameplay
- Client:
- Gameplay:
- Game Server:
- Handles game logic
- Manages player state
- Broadcasts updates to all players
- Handles physics simulation
- Game Server:
Real-Time Multiplayer Flow
- Player Action:
- Player performs action (move, interact)
- Client sends action to Game Server
- Server Processing:
- Game Server:
- Validates action
- Updates game state
- Runs physics simulation
- Determines state changes
- Game Server:
- State Broadcast:
- Game Server:
- Broadcasts state updates to all players
- Uses efficient delta compression
- Prioritizes critical updates
- Game Server:
- Client Update:
- Client receives state update
- Updates local game state
- Renders changes
- Maintains smooth gameplay
Chat Message Flow
- User Sends Message:
- User types message in chat
- Client sends to Chat Service
- Moderation Check:
- Chat Service:
- Checks message against moderation filters
- If flagged, queues for review
- If safe, proceeds to delivery
- Chat Service:
- Message Delivery:
- Chat Service:
- Stores message in database
- Broadcasts to all players in server
- Updates chat history
- Chat Service:
- Real-Time Delivery:
- WebSocket Service:
- Pushes message to connected clients
- Handles delivery failures
- Maintains message order
- WebSocket Service:
Database Design
Schema Design
Users Table:
CREATE TABLE users (
user_id UUID PRIMARY KEY,
username VARCHAR(50) UNIQUE NOT NULL,
display_name VARCHAR(100),
email VARCHAR(100) UNIQUE NOT NULL,
password_hash VARCHAR(255) NOT NULL,
robux_balance INT DEFAULT 0,
avatar_data JSON,
created_at TIMESTAMP DEFAULT NOW(),
updated_at TIMESTAMP DEFAULT NOW(),
INDEX idx_username (username),
INDEX idx_email (email)
);
Experiences Table:
CREATE TABLE experiences (
experience_id UUID PRIMARY KEY,
creator_id UUID NOT NULL,
title VARCHAR(200) NOT NULL,
description TEXT,
thumbnail_url VARCHAR(500),
genre VARCHAR(50),
max_players INT DEFAULT 20,
is_public BOOLEAN DEFAULT TRUE,
visits BIGINT DEFAULT 0,
likes BIGINT DEFAULT 0,
favorites BIGINT DEFAULT 0,
created_at TIMESTAMP DEFAULT NOW(),
updated_at TIMESTAMP DEFAULT NOW(),
INDEX idx_creator_id (creator_id),
INDEX idx_genre (genre),
INDEX idx_visits (visits DESC),
FULLTEXT INDEX idx_title_description (title, description)
);
Game Server Instances Table:
CREATE TABLE game_server_instances (
server_id UUID PRIMARY KEY,
experience_id UUID NOT NULL,
server_ip VARCHAR(50) NOT NULL,
server_port INT NOT NULL,
current_players INT DEFAULT 0,
max_players INT DEFAULT 20,
region VARCHAR(50) NOT NULL,
status VARCHAR(20) DEFAULT 'active',
created_at TIMESTAMP DEFAULT NOW(),
INDEX idx_experience_id (experience_id),
INDEX idx_status (status),
INDEX idx_region (region),
INDEX idx_current_players (current_players)
);
Player Sessions Table (Sharded by user_id):
CREATE TABLE player_sessions_0 (
session_id UUID PRIMARY KEY,
user_id UUID NOT NULL,
experience_id UUID NOT NULL,
server_id UUID NOT NULL,
joined_at TIMESTAMP DEFAULT NOW(),
left_at TIMESTAMP NULL,
play_duration INT DEFAULT 0,
INDEX idx_user_id (user_id),
INDEX idx_experience_id (experience_id),
INDEX idx_server_id (server_id),
INDEX idx_joined_at (joined_at DESC)
);
-- Similar tables: player_sessions_1, ..., player_sessions_N
Chat Messages Table (Sharded by experience_id):
CREATE TABLE chat_messages_0 (
message_id UUID PRIMARY KEY,
user_id UUID NOT NULL,
experience_id UUID NOT NULL,
server_id UUID NOT NULL,
message_text TEXT NOT NULL,
message_type VARCHAR(20) DEFAULT 'chat',
moderation_status VARCHAR(20) DEFAULT 'pending',
created_at TIMESTAMP DEFAULT NOW(),
INDEX idx_experience_id (experience_id),
INDEX idx_server_id (server_id),
INDEX idx_user_id (user_id),
INDEX idx_created_at (created_at DESC),
INDEX idx_moderation_status (moderation_status)
);
-- Similar tables: chat_messages_1, ..., chat_messages_N
Asset Marketplace Items Table:
CREATE TABLE marketplace_items (
item_id UUID PRIMARY KEY,
creator_id UUID NOT NULL,
item_type VARCHAR(50) NOT NULL,
title VARCHAR(200) NOT NULL,
description TEXT,
price_robux INT NOT NULL,
sales_count INT DEFAULT 0,
is_approved BOOLEAN DEFAULT FALSE,
created_at TIMESTAMP DEFAULT NOW(),
updated_at TIMESTAMP DEFAULT NOW(),
INDEX idx_creator_id (creator_id),
INDEX idx_item_type (item_type),
INDEX idx_price (price_robux),
INDEX idx_sales_count (sales_count DESC),
FULLTEXT INDEX idx_title_description (title, description)
);
Transactions Table (Sharded by user_id):
CREATE TABLE transactions_0 (
transaction_id UUID PRIMARY KEY,
user_id UUID NOT NULL,
transaction_type VARCHAR(50) NOT NULL,
item_id UUID,
robux_amount INT NOT NULL,
status VARCHAR(20) DEFAULT 'pending',
created_at TIMESTAMP DEFAULT NOW(),
INDEX idx_user_id (user_id),
INDEX idx_status (status),
INDEX idx_created_at (created_at DESC)
);
-- Similar tables: transactions_1, ..., transactions_N
Database Sharding Strategy
Player Sessions Table Sharding:
- Shard by user_id using consistent hashing
- 1000 shards:
shard_id = hash(user_id) % 1000 - All sessions for a user in same shard
- Enables efficient user session queries
Chat Messages Table Sharding:
- Shard by experience_id using consistent hashing
- 1000 shards:
shard_id = hash(experience_id) % 1000 - All messages for an experience in same shard
- Enables efficient experience chat queries
Transactions Table Sharding:
- Shard by user_id using consistent hashing
- 1000 shards:
shard_id = hash(user_id) % 1000 - All transactions for a user in same shard
- Enables efficient user transaction queries
Shard Key Selection:
- Ensures related data is co-located
- Enables efficient queries
- Prevents cross-shard queries for single entity
Replication:
- Each shard replicated 3x for high availability
- Master-replica setup for read scaling
- Writes go to master, reads can go to replicas
High-Level Design
┌─────────────┐
│ Client │
│ (PC/Mobile) │
└──────┬──────┘
│
│ HTTP/WebSocket
│
┌──────▼──────────────────────────────────────────────┐
│ API Gateway / Load Balancer │
│ - Rate Limiting │
│ - Request Routing │
└──────┬──────────────────────────────────────────────┘
│
├──────────────┬──────────────┬──────────────┬──────────────┐
│ │ │ │ │
┌──────▼──────┐ ┌─────▼──────┐ ┌─────▼──────┐ ┌─────▼──────┐ ┌─────▼──────┐
│ Experience │ │ Game Server │ │ Chat │ │ Social │ │ Marketplace│
│ Service │ │ Manager │ │ Service │ │ Service │ │ Service │
└──────┬──────┘ └─────┬──────┘ └─────┬──────┘ └─────┬──────┘ └─────┬──────┘
│ │ │ │ │
│ │ │ │ │
┌──────▼──────────────▼──────────────▼──────────────▼──────────────▼──────┐
│ Message Queue (Kafka) │
│ - Chat events │
│ - Game events │
│ - Transaction events │
└──────┬───────────────────────────────────────────────────────────────────┘
│
│
┌──────▼───────────────────────────────────────────────────────────────────┐
│ Game Server Cluster │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Server │ │ Server │ │ Server │ │
│ │ Instance │ │ Instance │ │ Instance │ │
│ │ 1 │ │ 2 │ │ N │ │
│ └──────────┘ └──────────┘ └──────────┘ │
│ - Game logic │
│ - Physics simulation │
│ - State management │
│ - Real-time updates │
└──────┬───────────────────────────────────────────────────────────────────┘
│
│
┌──────▼───────────────────────────────────────────────────────────────────┐
│ Database Cluster (Sharded) │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Users │ │ Experiences│ │ Sessions │ │
│ │ DB │ │ DB │ │ (Sharded) │ │
│ └──────────┘ └──────────┘ └──────────┘ │
│ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Chat │ │ Marketplace│ │ Transactions│ │
│ │ (Sharded)│ │ DB │ │ (Sharded) │ │
│ └──────────┘ └──────────┘ └──────────┘ │
└───────────────────────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────────────────────┐
│ CDN (CloudFront/Cloudflare) │
│ - Experience assets │
│ - User-generated content │
│ - Static assets │
└───────────────────────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────────────────────┐
│ Object Storage (S3) │
│ - Experience assets │
│ - User-generated content │
│ - Backup and archival │
└───────────────────────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────────────────────┐
│ Content Moderation Service │
│ - Automated filtering │
│ - Manual review queue │
│ - Safety and compliance │
└───────────────────────────────────────────────────────────────────────────┘
┌───────────────────────────────────────────────────────────────────────────┐
│ Search & Discovery Service │
│ - Experience search │
│ - Recommendation engine │
│ - Trending and popular │
└───────────────────────────────────────────────────────────────────────────┘
Deep Dive
Component Design
1. Game Server Manager
Responsibilities:
- Manage game server instances
- Allocate servers for experiences
- Monitor server health and capacity
- Handle server scaling
Key Design Decisions:
- Dynamic Server Allocation: Allocate servers on demand
- Regional Distribution: Servers in multiple regions
- Auto-Scaling: Scale servers based on demand
- Health Monitoring: Monitor server health and capacity
Implementation:
class GameServerManager:
def __init__(self):
self.server_pool = ServerPool()
self.region_manager = RegionManager()
self.load_balancer = LoadBalancer()
def allocate_server(self, experience_id, region, max_players):
"""Allocate a game server for an experience"""
# Check available servers in region
available_servers = self.server_pool.get_available_servers(
region=region,
min_capacity=max_players
)
if not available_servers:
# Scale up new server
server = self.scale_up_server(experience_id, region, max_players)
else:
# Select server with lowest load
server = self.select_best_server(available_servers)
# Allocate server to experience
server.allocate(experience_id, max_players)
return server
def select_best_server(self, servers):
"""Select server with lowest load"""
return min(servers, key=lambda s: s.current_load)
def scale_up_server(self, experience_id, region, max_players):
"""Scale up a new game server"""
# Get server configuration
config = self.get_server_config(experience_id)
# Launch server instance
server = self.server_pool.launch_server(
region=region,
config=config,
max_players=max_players
)
# Wait for server to be ready
server.wait_for_ready()
return server
2. Real-Time Game Server
Responsibilities:
- Handle game logic and state
- Manage player connections
- Broadcast state updates
- Run physics simulation
Key Design Decisions:
- State Management: Centralized game state on server
- Delta Compression: Send only state changes
- Update Frequency: 30-60 updates per second
- Client Prediction: Allow client-side prediction
Implementation:
class GameServer:
def __init__(self, experience_id, max_players):
self.experience_id = experience_id
self.max_players = max_players
self.players = {} # user_id -> Player
self.game_state = GameState()
self.physics_engine = PhysicsEngine()
self.update_rate = 60 # updates per second
def handle_player_action(self, user_id, action):
"""Handle player action"""
player = self.players.get(user_id)
if not player:
return
# Validate action
if not self.validate_action(player, action):
return
# Update game state
self.game_state.apply_action(player, action)
# Run physics simulation
self.physics_engine.step(self.game_state)
# Broadcast update to all players
self.broadcast_state_update()
def broadcast_state_update(self):
"""Broadcast state update to all players"""
# Get delta (changes since last update)
delta = self.game_state.get_delta()
# Compress delta
compressed_delta = self.compress_delta(delta)
# Send to all players
for player in self.players.values():
player.send_update(compressed_delta)
def compress_delta(self, delta):
"""Compress state delta"""
# Use delta compression
# Only send changed values
# Use efficient serialization
return json.dumps(delta, separators=(',', ':'))
3. Chat Service
Responsibilities:
- Handle chat messages
- Content moderation
- Real-time message delivery
- Chat history management
Key Design Decisions:
- Moderation Pipeline: Automated + manual review
- Real-Time Delivery: WebSocket for instant delivery
- Message Storage: Store for moderation and history
- Rate Limiting: Prevent spam
Implementation:
class ChatService:
def __init__(self):
self.moderation_service = ModerationService()
self.websocket_manager = WebSocketManager()
self.message_queue = MessageQueue()
def send_message(self, user_id, experience_id, server_id, message_text):
"""Send chat message"""
# Rate limiting
if not self.check_rate_limit(user_id):
raise RateLimitError("Too many messages")
# Content moderation
moderation_result = self.moderation_service.check_message(message_text)
if moderation_result.is_blocked:
# Block message
return {
'status': 'blocked',
'reason': moderation_result.reason
}
# Create message
message = ChatMessage(
user_id=user_id,
experience_id=experience_id,
server_id=server_id,
message_text=message_text,
moderation_status='approved' if moderation_result.is_safe else 'pending'
)
# Store message
message.save()
# If pending moderation, queue for review
if message.moderation_status == 'pending':
self.message_queue.publish('moderation_review', message)
# Broadcast to server players
self.broadcast_message(server_id, message)
return {
'message_id': message.message_id,
'status': message.moderation_status
}
def broadcast_message(self, server_id, message):
"""Broadcast message to all players in server"""
# Get all players in server
players = self.get_server_players(server_id)
# Send via WebSocket
for player in players:
self.websocket_manager.send_message(
player.user_id,
{
'type': 'chat_message',
'message': message.to_dict()
}
)
4. Content Moderation Service
Responsibilities:
- Automated content filtering
- Manual review queue
- Safety and compliance
- Ban management
Key Design Decisions:
- Multi-Layer Filtering: Keyword, ML, manual review
- Real-Time Filtering: Fast automated checks
- Manual Review: Human review for edge cases
- Learning System: Improve filters over time
Implementation:
class ModerationService:
def __init__(self):
self.keyword_filter = KeywordFilter()
self.ml_classifier = MLClassifier()
self.review_queue = ReviewQueue()
def check_message(self, message_text):
"""Check message for moderation"""
# Keyword filtering
keyword_result = self.keyword_filter.check(message_text)
if keyword_result.is_blocked:
return ModerationResult(
is_blocked=True,
reason='keyword_filter',
confidence=1.0
)
# ML classification
ml_result = self.ml_classifier.classify(message_text)
if ml_result.confidence > 0.9:
# High confidence, auto-decision
return ModerationResult(
is_blocked=ml_result.is_toxic,
reason='ml_classifier',
confidence=ml_result.confidence
)
else:
# Low confidence, queue for manual review
return ModerationResult(
is_blocked=False,
reason='pending_review',
confidence=ml_result.confidence,
needs_review=True
)
def check_asset(self, asset_data, asset_type):
"""Check asset for moderation"""
# Image/text analysis
# 3D model analysis
# File content scanning
# Similar to message checking
pass
5. Experience Discovery Service
Responsibilities:
- Search experiences
- Recommend experiences
- Trending and popular
- Personalized recommendations
Key Design Decisions:
- Search Engine: Elasticsearch for full-text search
- Recommendation Engine: ML-based recommendations
- Caching: Cache popular searches
- Personalization: User-based recommendations
Implementation:
class DiscoveryService:
def __init__(self):
self.search_engine = ElasticsearchClient()
self.recommendation_engine = RecommendationEngine()
self.cache = RedisCache()
def search_experiences(self, query, filters, limit=20, offset=0):
"""Search experiences"""
cache_key = f"search:{query}:{filters}:{limit}:{offset}"
# Check cache
cached = self.cache.get(cache_key)
if cached:
return cached
# Search
results = self.search_engine.search(
index='experiences',
query=query,
filters=filters,
limit=limit,
offset=offset
)
# Cache results
self.cache.setex(cache_key, 300, results) # 5 min cache
return results
def get_recommendations(self, user_id, limit=20):
"""Get personalized recommendations"""
# Get user preferences
user_preferences = self.get_user_preferences(user_id)
# Get recommendations
recommendations = self.recommendation_engine.recommend(
user_id=user_id,
preferences=user_preferences,
limit=limit
)
return recommendations
def get_trending(self, limit=20):
"""Get trending experiences"""
# Calculate trending score
# Based on visits, likes, recent activity
trending = self.calculate_trending_score(limit)
return trending
Detailed Design
Real-Time State Synchronization
Challenge: Synchronize game state across multiple clients with low latency
Solution:
- Server Authority: Server is source of truth
- Delta Compression: Send only changes
- Client Prediction: Allow client-side prediction
- Interpolation: Smooth client-side interpolation
Implementation:
class StateSynchronizer:
def __init__(self):
self.server_state = {}
self.client_states = {}
self.update_rate = 60 # Hz
def sync_state(self, server_state, client_id):
"""Synchronize state with client"""
# Get client's last known state
client_last_state = self.client_states.get(client_id, {})
# Calculate delta
delta = self.calculate_delta(server_state, client_last_state)
# Compress delta
compressed_delta = self.compress(delta)
# Send to client
self.send_to_client(client_id, compressed_delta)
# Update client state
self.client_states[client_id] = server_state
def calculate_delta(self, new_state, old_state):
"""Calculate state delta"""
delta = {}
for key, value in new_state.items():
if key not in old_state or old_state[key] != value:
delta[key] = value
return delta
Asset Management and CDN
Challenge: Efficiently serve petabytes of user-generated content
Solution:
- CDN Distribution: Distribute assets globally
- Asset Versioning: Version assets for updates
- Lazy Loading: Load assets on demand
- Compression: Compress assets for faster delivery
Implementation:
class AssetManager:
def __init__(self):
self.s3_storage = S3Client()
self.cdn = CDNClient()
self.asset_cache = RedisCache()
def upload_asset(self, experience_id, asset_data, asset_type):
"""Upload asset"""
# Generate asset ID
asset_id = generate_asset_id()
# Compress asset
compressed_data = self.compress_asset(asset_data, asset_type)
# Upload to S3
s3_key = f"experiences/{experience_id}/assets/{asset_id}"
self.s3_storage.upload(s3_key, compressed_data)
# Invalidate CDN cache
self.cdn.invalidate(f"assets/{asset_id}")
# Store metadata
asset_metadata = AssetMetadata(
asset_id=asset_id,
experience_id=experience_id,
asset_type=asset_type,
s3_key=s3_key,
file_size=len(compressed_data)
)
asset_metadata.save()
return asset_id
def get_asset_url(self, asset_id):
"""Get CDN URL for asset"""
# Check cache
cached_url = self.asset_cache.get(f"asset_url:{asset_id}")
if cached_url:
return cached_url
# Get metadata
metadata = self.get_asset_metadata(asset_id)
# Generate CDN URL
cdn_url = self.cdn.get_url(metadata.s3_key)
# Cache URL
self.asset_cache.setex(f"asset_url:{asset_id}", 3600, cdn_url)
return cdn_url
Monetization System
Challenge: Handle Robux transactions securely and at scale
Solution:
- Transaction Logging: Log all transactions
- Idempotency: Prevent duplicate transactions
- Atomic Operations: Ensure consistency
- Fraud Detection: Detect suspicious transactions
Implementation:
class MonetizationService:
def __init__(self):
self.transaction_log = TransactionLog()
self.fraud_detector = FraudDetector()
def process_purchase(self, user_id, item_id, price_robux):
"""Process purchase transaction"""
# Check user balance
user = self.get_user(user_id)
if user.robux_balance < price_robux:
raise InsufficientFundsError("Not enough Robux")
# Fraud detection
fraud_check = self.fraud_detector.check_transaction(
user_id, item_id, price_robux
)
if fraud_check.is_suspicious:
# Queue for manual review
self.queue_for_review(user_id, item_id, price_robux)
return {'status': 'pending_review'}
# Create transaction
transaction = Transaction(
user_id=user_id,
transaction_type='purchase',
item_id=item_id,
robux_amount=price_robux,
status='pending'
)
transaction.save()
# Process transaction atomically
try:
# Deduct Robux
user.robux_balance -= price_robux
user.save()
# Grant item to user
self.grant_item(user_id, item_id)
# Update transaction status
transaction.status = 'completed'
transaction.save()
# Log transaction
self.transaction_log.log(transaction)
return {
'transaction_id': transaction.transaction_id,
'status': 'completed',
'new_balance': user.robux_balance
}
except Exception as e:
# Rollback
transaction.status = 'failed'
transaction.save()
raise
Scalability Considerations
Horizontal Scaling
Game Servers:
- Stateless game logic, horizontally scalable
- Auto-scaling based on demand
- Regional distribution for low latency
- Load balancing across servers
Backend Services:
- Stateless services, horizontally scalable
- Multiple instances behind load balancer
- Shared database and cache
- Message queue for async processing
Caching Strategy
Redis Cache:
- User Data: TTL 1 hour
- Experience Metadata: TTL 30 minutes
- Server List: TTL 1 minute
- Search Results: TTL 5 minutes
- Asset URLs: TTL 1 hour
CDN Cache:
- Static Assets: Long TTL (1 year)
- Dynamic Content: Short TTL (5 minutes)
- Edge Caching: Cache at edge locations
Security Considerations
Content Moderation
- Automated Filtering: Keyword and ML-based filtering
- Manual Review: Human review for edge cases
- Reporting System: User reporting mechanism
- Ban Management: Temporary and permanent bans
Anti-Cheat
- Server Authority: Server validates all actions
- Rate Limiting: Limit action frequency
- Behavioral Analysis: Detect suspicious patterns
- Client Validation: Validate client inputs
Data Protection
- Encryption: Encrypt sensitive data
- Access Control: Role-based access control
- Audit Logging: Log all sensitive operations
- Privacy: Protect user privacy
Monitoring & Observability
Key Metrics
Platform Metrics:
- Concurrent users
- Experience launches per second
- Game server count
- Average session duration
- Chat messages per second
Performance Metrics:
- Game server latency (p50, p95, p99)
- Asset download latency
- Chat message delivery latency
- API response time
Business Metrics:
- Daily active users
- Experience visits
- Robux transactions
- Marketplace sales
- Creator earnings
Trade-offs and Optimizations
Trade-offs
1. State Synchronization: Full vs Delta
- Full: Simpler, higher bandwidth
- Delta: Complex, lower bandwidth
- Decision: Delta compression for efficiency
2. Server Authority: Strict vs Lenient
- Strict: More secure, higher latency
- Lenient: Lower latency, less secure
- Decision: Strict with client prediction
3. Content Moderation: Automated vs Manual
- Automated: Fast, may have false positives
- Manual: Accurate, slower
- Decision: Hybrid approach
4. Asset Storage: Centralized vs Distributed
- Centralized: Simpler, higher latency
- Distributed: Complex, lower latency
- Decision: CDN distribution
Optimizations
1. Client Prediction
- Predict actions client-side
- Reduce perceived latency
- Improve user experience
2. Delta Compression
- Send only state changes
- Reduce bandwidth
- Improve performance
3. Asset Streaming
- Stream assets on demand
- Reduce initial load time
- Improve experience launch
4. Regional Distribution
- Servers in multiple regions
- Reduce latency
- Improve user experience
What Interviewers Look For
Real-Time Multiplayer Skills
- Game Server Architecture
- Low-latency game servers
- State synchronization
- Delta compression
- Red Flags: High latency, no compression, poor sync
- State Synchronization
- Efficient state updates
- Client prediction
- Red Flags: No prediction, high latency, poor UX
- Connection Management
- Millions of concurrent connections
- Efficient handling
- Red Flags: Connection limits, poor scaling, bottlenecks
Distributed Systems Skills
- Content Delivery
- CDN distribution
- Asset streaming
- Efficient delivery
- Red Flags: No CDN, slow delivery, poor UX
- User-Generated Content
- Petabytes of content
- Efficient storage
- Red Flags: Inefficient storage, high costs, slow access
- Scalability Design
- Horizontal scaling
- Regional distribution
- Red Flags: Vertical scaling, single region, bottlenecks
Problem-Solving Approach
- Cross-Platform Support
- PC, mobile, console
- Platform-specific optimizations
- Red Flags: Single platform, no optimization, poor UX
- Edge Cases
- Network failures
- High latency
- Content moderation
- Red Flags: Ignoring edge cases, no handling
- Trade-off Analysis
- Latency vs quality
- Consistency vs performance
- Red Flags: No trade-offs, dogmatic choices
System Design Skills
- Component Design
- Game server cluster
- Content service
- Social service
- Red Flags: Monolithic, unclear boundaries
- Content Moderation
- Automated moderation
- Manual review
- Red Flags: No moderation, post-processing, slow
- Monetization System
- Robux currency
- Secure transactions
- Red Flags: Insecure, no validation, fraud possible
Communication Skills
- Real-Time Architecture Explanation
- Can explain game server design
- Understands state sync
- Red Flags: No understanding, vague
- Content Delivery Explanation
- Can explain CDN strategy
- Understands streaming
- Red Flags: No understanding, vague
Meta-Specific Focus
- Real-Time Systems Expertise
- Game server knowledge
- Low-latency design
- Key: Show real-time systems knowledge
- Scale Thinking
- Millions of users
- Petabytes of content
- Key: Demonstrate scale expertise
Summary
Designing Roblox requires careful consideration of:
- Real-Time Multiplayer: Low-latency game servers with state synchronization
- User-Generated Content: Petabytes of content with efficient storage and delivery
- Creator Tools: Roblox Studio for experience creation
- Social Features: Friends, chat, groups with real-time delivery
- Monetization: Robux currency with secure transactions
- Content Moderation: Automated and manual moderation at scale
- Discovery: Search and recommendation for experiences
- Scalability: Handle 10M+ concurrent users
- Cross-Platform: Support PC, mobile, console
- Performance: Sub-100ms game server latency
Key architectural decisions:
- Game Server Cluster for real-time multiplayer
- CDN Distribution for asset delivery
- Delta Compression for state synchronization
- Hybrid Moderation for content safety
- Sharded Database for scalability
- Regional Distribution for low latency
- Client Prediction for better UX
- Horizontal Scaling for all services
The system handles 10 million concurrent users, serves petabytes of content, processes billions of chat messages, and maintains sub-100ms game server latency while ensuring content safety and supporting millions of creators.