Introduction to System Design
System design refers to the process of defining the architecture, modules, interfaces, and data required to satisfy specified system requirements. In the real world, system design enables scalable, maintainable, and performant software. Whether you’re building a simple CRUD app or a distributed system serving millions of users, understanding design principles is essential.
System design sits at the intersection of software engineering and architecture. It’s what turns code into a coherent system that’s fault-tolerant, scalable, and efficient.
Core Concepts
Monolith vs Microservices
- Monolith: Single codebase, easier to develop and deploy initially.
- Microservices: Independently deployable components, better for scalability and fault isolation.
Scalability
- Vertical Scaling: Increasing the capacity of a single server (CPU, RAM).
- Horizontal Scaling: Adding more servers to distribute the load.
Latency vs Throughput
- Latency: Time taken to complete a single request.
- Throughput: Number of requests served in a given time frame.
CAP Theorem
You can only pick two of the three: Consistency, Availability, and Partition Tolerance.
Load Balancing
Distributes traffic across multiple servers to avoid overload. Examples: Round Robin, Least Connections, IP Hash.
Building Blocks
Databases
- SQL (MySQL, PostgreSQL): ACID compliance, structured schema.
- NoSQL (MongoDB, Cassandra): Flexible schema, eventual consistency.
You can refer to my post on – Decoding ACID in Databases: A Practical Guide for Developers
Caching
- Used to reduce database load and improve response times.
- Tools: Redis, Memcached
You can refer to my Blog on Caching – Beginner’s Guide to Caching: Top Patterns You Need to Know
Messaging Queues
- Used for asynchronous communication.
- Tools: Kafka, RabbitMQ
Object Storage
- Used for storing large files (images, videos).
- Examples: Amazon S3, Google Cloud Storage
Designing Scalable Systems
Read-heavy vs Write-heavy Systems
- Read-heavy: Use caching, replicas.
- Write-heavy: Use sharding, write queues.
Rate Limiting
- Protects APIs from being overwhelmed.
- Enforced at the gateway or service layer.
You can refer to my Blog on – Rate Limiting Explained: How to Prevent System Overload and Ensure Fair Access
Sharding and Partitioning
- Distributes data across multiple databases or tables to improve performance.
5. High Availability and Reliability
Replication
- Master-slave: One primary writer, multiple read replicas.
- Multi-master: Multiple writable nodes, conflict resolution needed.
Failover Mechanisms
- Automatic switchover to standby systems in the event of failure.
Health Checks
- Ensure systems are operating correctly and are responsive.
6. Real-World System Design Examples
URL Shortener
- Input: Long URL
- Output: Unique short code
- Use cases: Redirection, click tracking
Messaging System
- Real-time delivery
- Use WebSockets, queues, and persistent storage
File Sharing Service
- User uploads
- Store in S3, metadata in DB
- Secure downloads with expiring URLs
Video Streaming Platform
- Store videos in chunks
- Use CDN for global delivery
- Transcoding and resolution support
7. Security and Best Practices
Authentication & Authorization
- JWT, OAuth 2.0
- RBAC (Role-Based Access Control)
You can refer to my post on JWT – How JWT Works: A Complete Guide for Developers
Data Encryption
- At rest (disk encryption)
- In transit (HTTPS/TLS)
Secure APIs
- Use rate limiting, validation, HTTPS, and Logging
You can refer to my post on – Simplifying Backend Communication with API Gateways
8. Deployment and Observability
CI/CD Pipelines
- Automate testing and deployments
You can refer to my post – Discover What CI/CD Pipelines Are and Why They Matter
Monitoring and Logging
- Tools: Prometheus, Grafana, ELK Stack
Infrastructure as Code (IaC)
- Use Terraform or Ansible to define environments
9. Interview Preparation Tips
Approach
- Clarify requirements
- Define APIs
- Draw a high-level diagram
- Address scalability, fault tolerance, and consistency
Common Questions
- Design a Rate Limiter
- Design a News Feed
- Design a Ride-Sharing App
10. Summary and Resources
Recap
- Start with requirements
- Pick the right building blocks
- Optimize for performance, scale, and reliability
Recommended Resources
- Books: “Designing Data-Intensive Applications” by Martin Kleppmann
- Courses: Grokking the System Design Interview
- GitHub: Awesome System Design repositories
