Contact Form Service

Interview-Ready Approach

1) Clarify Scope and SLOs

• •Problem statement: Design a form submission backend that receives contact form data, validates it, and sends email notifications.
• •Design for a peak load target around 100 RPS (including burst headroom).
• •Active websites: ~5,000
• •Submissions/day: ~200,000
• •Email notification delay: < 60 seconds
• •Spam block rate: > 95%
• •API response time: < 300 ms

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.
• •API Design: Standardize API boundaries, idempotency keys, pagination, and error contracts first.
• •Rate Limiting: Enforce token/sliding-window limits at ingress and for sensitive internal APIs.

4) Reliability and Failure Strategy

• •Use strong write constraints (transactions or conditional writes) and explicit backup/restore strategy.
• •Apply strict input validation and backward-compatible versioning.
• •Return deterministic 429 behavior with clear retry headers.

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.
• •API Design: Rich APIs improve developer speed but can create long-term compatibility burden.
• •Rate Limiting: Aggressive limits protect the system but can hurt legitimate burst traffic.

Practical Notes

• •Rate limit by IP address and by form ID to prevent spam floods.
• •Use a queue for email delivery - don't send emails synchronously in the API request.
• •A honeypot field (hidden input) catches most bots without annoying real users.

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 -> Rate Limiter -> API Service -> Primary SQL DB

Design strengths

• •Security controls are enforced at ingress to protect downstream capacity.

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.