Design a Email Service

Question

Design a low-latency email system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Codemia · Accepted Answer

### Functional Requirements
1. **Email Sending and Receiving**: Users must be able to send and receive emails in real-time.
2. **Search Functionality**: Users should be able to search their inboxes efficiently.
3. **Spam Detection**: The system should classify and filter spam emails.
4. **User Management**: Support for user registrations, authentication, and profile management.
5. **Notifications**: Real-time notifications for new emails.

### Non-Functional Requirements
1. **Low Latency**: Email sending/receiving should have a latency of less than 200ms.
2. **High Availability**: The system should guarantee 99.9% uptime.
3. **Scalability**: Must handle at least 1 million active users concurrently.
4. **Data Consistency**: Strong consistency for email delivery (exact once delivery).
5. **Security**: Implement encryption for data in transit and at rest.

Assuming DE Shaw anticipates around 5 million users with an average of 20 emails sent/received per user per day:
- **Total Emails per Day**: 5 million users * 20 emails = 100 million emails per day.
- **Total Emails per Second**: 100 million emails / 86400 seconds = ~1157 emails per second.
- **Storage Requirements**: Assuming an average email size of 75 KB, total storage required = 100 million emails * 75 KB = ~7.5 TB. 
- **Throughput Requirements**: The system must be able to handle spikes; scaling for up to 2000 emails per second during peak times (e.g., mornings).

### Component Diagram
- **Frontend**: React for UI, providing an interactive email interface.
- **API Gateway**: AWS API Gateway, routing requests to microservices.
- **Email Service**: Microservice for sending/receiving emails, implemented in Node.js.
- **Database**: PostgreSQL for structured data (user profiles) and Redis for caching email metadata.
- **Search Service**: Elasticsearch for efficient email search functionality.
- **Spam Filter**: ML-based model service using TensorFlow Serving for real-time spam detection.
- **Notification Service**: WebSocket service for real-time notifications.

### Technology Choices
- Cloud Provider: AWS for hosting and scaling.
- CI/CD: Jenkins for continuous integration and deployment.

### Schema Design
1. **Users Table**: (user_id, email, password_hash, created_at, updated_at)
2. **Emails Table**: (email_id, sender_id, receiver_id, subject, body, timestamp, is_spam)
3. **Spam Reports Table**: (report_id, email_id, user_id, timestamp)
4. **Email Metadata Table**: (email_id, status, priority, retry_count)

### Access Patterns
- Frequent read queries on Emails Table for inbox retrieval.
- Frequent write operations for sending emails and updating metadata.

1. **Consistency vs. Availability**: Choosing a strong consistency model (e.g., using PostgreSQL) may impact availability during network partitions. We need to ensure that email delivery is exactly-once, which may introduce latency during high loads.
2. **Latency vs. Complexity**: Implementing real-time spam detection using an ML model adds complexity. However, pre-fetching and caching results can help reduce latency in delivering emails.
3. **Scalability vs. Cost**: While using managed services (like AWS RDS) provides scalability, it can be more expensive. Deciding between on-premise solutions vs. cloud can impact operational costs significantly, especially with increased user base.

Design a Email Service

DE Shaw

What the Interviewer Expects

Key Topics to Cover

How to Approach This

Possible Follow-up Questions

Practice a Similar Problem on Codemia

Sample Answer

Requirements

Functional Requirements

Capacity Estimation

Submit Your Answer

DE Shaw Software Engineer Interview Guide

Related Questions

Design a high-throughput Inventory Management System

Design a low-latency Rate Limiting System

Design a fault-tolerant Payment System

Design a fault-tolerant Messaging System

Design Walmart Product Search