Requirements

Functional Requirements

• Users can create a paste with text content (up to 10MB)
• Each paste gets a unique, shareable URL
• Pastes can be public or private (unlisted)
• Pastes expire after a configurable duration (10 min, 1 hour, 1 day, 1 week, never)
• Support syntax highlighting for code pastes
• Users can set a custom name for the paste (optional)

Non-Functional Requirements

• Latency: Read paste in < 100ms
• Availability: 99.9% uptime
• Durability: Pastes must not be lost before expiration
• Scalability: 10M new pastes/day, 100M reads/day

Back-of-the-Envelope Estimation

API Design

POST /api/v1/pastes
Request:  { "content": "...", "syntax": "python", "visibility": "public", "expires_in": "1h" }
Response: { "paste_id": "abc123", "url": "https://paste.example.com/abc123" }

GET /{paste_id}
Response: { "content": "...", "syntax": "python", "created_at": "...", "expires_at": "..." }

GET /api/v1/pastes/{paste_id}/raw
Response: Plain text content (no JSON wrapping)

DELETE /api/v1/pastes/{paste_id}
Response: { "status": "deleted" }

High-Level Architecture

Detailed Design

Storage Layer

Pastebin has two distinct storage needs:

Expiration Strategy

Pastebin requires automatic deletion of expired pastes:

Option A: Lazy Expiration (Recommended)

• Check expires_at on every read
• Delete if expired; return 404
• Simple, no background processing
• May show stale data in cache

Option B: Active Expiration

• Background worker scans for expired pastes
• Deletes from database and cache periodically
• More consistent, but adds complexity
• Use sorted set in Redis: EXPIRE_AT score=<timestamp>

Content Storage Pattern

Store large paste content in object storage, metadata in the database:

// Metadata record
{
  paste_id: "abc123",
  user_id: "user_456",
  content_path: "s3://pastes/ab/c1/abc123.txt",
  syntax: "python",
  visibility: "public",
  created_at: "2026-06-20T10:00:00Z",
  expires_at: "2026-06-20T11:00:00Z",
  size_bytes: 10240
}

Syntax Highlighting

Support syntax highlighting for code pastes:

1. Client submits paste with syntax parameter (or auto-detect)
2. Server stores raw content in object storage
3. On read, apply syntax highlighting at the CDN edge or application layer
4. Cache highlighted HTML alongside raw content

Scaling Considerations

Database Partitioning

Partition paste metadata by paste ID hash:

shard = hash(paste_id) % NUM_SHARDS

This distributes pastes evenly across shards. For time-based queries (e.g., "recent pastes"), maintain a separate time-indexed table or use a time-series database.

Read Path Optimization

1. Check Redis cache for paste metadata
2. Cache hit: return content from object storage (cached at CDN)
3. Cache miss: query database, populate cache, return content
4. CDN caches public paste content at edge locations

Write Path Optimization

1. Generate unique paste ID (Snowflake or random)
2. Write metadata to database (async if possible)
3. Write content to object storage (S3 multipart upload for large pastes)
4. Populate Redis cache proactively
5. Return paste URL to user

What to Learn Next