Image Gallery & Album Service

Interview-Ready Approach

1) Clarify Scope and SLOs

• •Problem statement: Design an image gallery service where users upload photos, organize them into albums, and share galleries.
• •Design for a peak load target around 100 RPS (including burst headroom).
• •Registered users: ~20,000
• •Total photos: ~5,000,000
• •Uploads per day: ~20,000
• •Gallery load time: < 500 ms
• •Thumbnail sizes: 3 (150px, 600px, 1200px)

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

• •Storage: Use object storage for large blobs and keep metadata/authorization separate in the API tier.
• •Databases: Define a clear system-of-record and design read/write paths separately before adding optimizations.
• •CDN: Serve static and cacheable content from edge and keep origin strictly for misses and dynamic requests.
• •API Design: Standardize API boundaries, idempotency keys, pagination, and error contracts first.

4) Reliability and Failure Strategy

• •Enforce lifecycle policies, retention tiers, and checksum validation.
• •Use strong write constraints (transactions or conditional writes) and explicit backup/restore strategy.
• •Define cache keys and purge workflows before launch to avoid stale/global outages.
• •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

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

Practical Notes

• •Store originals in S3; generate thumbnails on upload using an image processing library (Sharp, Pillow) and store alongside.
• •Serve thumbnails from CDN for fast gallery loading - only fetch the full-resolution image when the user clicks to view.
• •Lazy-load images in the gallery grid (Intersection Observer) to reduce initial page load size.

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 -> DNS -> CDN Edge -> 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.