Pastebin Service

Interview-Ready Approach

1) Clarify Scope and SLOs

• •Problem statement: Design a Pastebin-like service for sharing text snippets with syntax highlighting and expiration.
• •Design for a peak load target around 100 RPS (including burst headroom).
• •New pastes/day: ~50,000
• •Paste views/day: ~500,000
• •Max paste size: 512 KB
• •View latency: < 200 ms
• •Total stored pastes: ~10 million

2) Capacity Planning Method

• •Convert traffic and growth constraints into request rate, storage growth, and concurrency budgets.
• •Keep at least 2-3x safety margin per tier (ingress, compute, storage, async workers).
• •Reserve explicit latency budgets per hop so p95 can be defended in review.

3) Architecture Decisions

• •Databases: Define a clear system-of-record and design read/write paths separately before adding optimizations.
• •Storage: Use object storage for large blobs and keep metadata/authorization separate in the API tier.
• •API Design: Standardize API boundaries, idempotency keys, pagination, and error contracts first.

4) Reliability and Failure Strategy

• •Use strong write constraints (transactions or conditional writes) and explicit backup/restore strategy.
• •Enforce lifecycle policies, retention tiers, and checksum validation.
• •Apply strict input validation and backward-compatible versioning.

5) Validation Plan

• •Run one peak-load test, one dependency-degradation test, and one failover test.
• •Verify idempotency for all retried writes and async consumers.
• •Track user-facing SLOs first: p95 latency, error rate, and successful throughput.

6) Trade-offs to Call Out in Interviews

• •Databases: SQL gives stronger transactional guarantees; NoSQL often gives better write scaling and flexibility.
• •Storage: Object storage is cheap and durable, but random low-latency reads are weaker than databases/caches.
• •API Design: Rich APIs improve developer speed but can create long-term compatibility burden.

Practical Notes

• •Store paste content in an object store (S3) keyed by a unique ID; metadata (title, language, expiration) in a database.
• •A cron job runs periodically to delete expired pastes from both the database and object store.
• •CDN caching for popular pastes can reduce read load significantly.

Why This Solution Works

Request path: The solution keeps ingress, service logic, and stateful dependencies separated so each layer can scale independently.

Reference flow: Web Clients -> API Gateway -> API Service -> Primary SQL DB -> Object Storage

Design strengths

• •The architecture keeps synchronous paths short and isolates stateful dependencies behind clear boundaries.

Interview defense

• •This design makes bottlenecks explicit (ingress, core compute, persistence, async workers).
• •It supports progressive scaling without re-architecting the core request path.
• •It keeps correctness-sensitive state changes in durable systems while offloading background work asynchronously.