Understanding System Design: 30 Key Concepts for Scalable Applications

1. Client-Server Architecture

A fundamental model where clients (users) request data or services from a central server. This architecture is commonly used in web applications, where browsers (clients) interact with web servers to fetch and display content. It enables centralized data management and simplifies security enforcement while allowing multiple clients to connect to the same server.

2. IP Address

A unique identifier is assigned to devices on a network, enabling communication between different machines over the internet or local networks. IPv4 and IPv6 are the two main versions, with IPv6 providing a larger address space. IP addresses are crucial for routing data packets between devices across the internet.

3. DNS (Domain Name System)

DNS translates human-readable domain names (e.g., google.com) into machine-readable IP addresses, facilitating seamless web browsing. It works through a hierarchical structure with root servers, TLD (Top-Level Domain) servers, and authoritative name servers, ensuring fast and efficient domain resolution.

4. Proxy & Reverse Proxy

A proxy server acts as an intermediary between clients and servers to enhance security, load balancing, or caching. A reverse proxy sits in front of a server, managing incoming requests to improve performance and security. Reverse proxies also help in SSL termination, compression, and request routing to different backend services.

5. Latency

The time delay between a request and its response in a network, affecting the performance of applications and user experience. Factors influencing latency include network congestion, physical distance, and server processing time. Low latency is essential for real-time applications like gaming and video conferencing.

6. HTTP & HTTPS

HTTP (HyperText Transfer Protocol) defines rules for web communication, while HTTPS (the secure version) encrypts data for safer transmission. HTTPS uses SSL/TLS encryption to protect data from eavesdropping and tampering, making it a standard for secure websites, especially for transactions and sensitive information.

7. APIs (Application Programming Interfaces)

APIs allow applications to communicate with each other by defining standardized request and response formats. They enable interoperability between different systems and platforms, making them essential for microservices, third-party integrations, and cloud computing.

8. REST API

A RESTful API follows REST principles, using HTTP methods like GET, POST, PUT, and DELETE to interact with resources. REST APIs are stateless and use standard HTTP status codes, making them scalable and easy to implement in web applications.

9. GraphQL

A flexible query language for APIs that allows fetching only the required data, reducing over-fetching and under-fetching issues. Unlike REST, GraphQL provides a single endpoint and supports complex queries, making it efficient for frontend applications that need precise data.

10. Databases

Storage systems that manage structured or unstructured data. They are categorized into:

Non-relational (NoSQL) – Flexible, document-based storage, suitable for high scalability and semi-structured data.

Relational (SQL) – Structured schemas and tables, ensuring data integrity and ACID compliance.

11. SQL vs. NoSQL

SQL databases use structured schemas, ensuring consistency and strong relationships between data entities. NoSQL databases offer flexible, scalable storage suitable for distributed applications, making them ideal for handling large volumes of unstructured or semi-structured data.

12. Indexing

An optimization technique that speeds up database queries by organizing data for quick retrieval. Indexes create pointers to data locations, reducing the need for full-table scans, which improves query performance significantly in large datasets.

13. Caching

A technique that temporarily stores frequently accessed data to reduce database load and improve response times. Common caching mechanisms include in-memory caches like Redis and Memcached, which speed up data retrieval in web applications.

14. Load Balancing

Distributes incoming network traffic across multiple servers to enhance performance, reliability, and scalability. Load balancers can use various algorithms like round-robin, least connections, and IP hash to evenly distribute requests and prevent server overload.

15. Microservices Architecture

A design pattern where applications are broken into independent, loosely coupled services that can scale and deploy individually. This architecture enhances maintainability, enables independent development teams, and allows technology heterogeneity.

16. Monolithic vs. Microservices

Monolithic Architecture – A single, tightly integrated codebase, simpler to develop but harder to scale.

Microservices – Decentralized services that communicate through APIs, offering better scalability and fault tolerance, though introducing complexity in service management.

17. Containerization (Docker & Kubernetes)

Containers package applications with dependencies, ensuring consistency across environments. Kubernetes helps orchestrate these containers for scalability and resilience, managing deployment, scaling, and networking efficiently.

18. Message Queues (RabbitMQ, Kafka)

Message queues enable asynchronous communication between distributed components, improving performance and fault tolerance. They help decouple services, enabling event-driven architectures that scale efficiently under high loads.

19. Event-Driven Architecture

A system that reacts to real-time events instead of relying on direct interactions, making it highly responsive and scalable. This architecture is ideal for real-time notifications, financial transactions, and IoT applications.

20. CAP Theorem

States that a distributed system can achieve only two out of three properties:

Partition Tolerance – The system functions despite network failures.
Designing distributed databases involves trade-offs between these three factors.

Consistency – All nodes have the same data at the same time.

Availability – Every request receives a response, even if some nodes fail.

21. Sharding

A database scaling technique that splits large datasets into smaller, manageable partitions across multiple servers. This improves query performance and allows horizontal scaling, reducing bottlenecks in large applications.

22. Replication

A technique where database copies are maintained across multiple servers for redundancy, high availability, and load balancing. Replication can be synchronous or asynchronous, ensuring data reliability and disaster recovery.

23. CDN (Content Delivery Network)

A distributed network of servers that caches and delivers website content closer to users, reducing latency and improving speed. CDNs are widely used for media streaming, e-commerce, and large-scale web applications.

24. WebSockets

A protocol that enables real-time, two-way communication between clients and servers, essential for chat applications and live updates. Unlike HTTP, WebSockets maintain a persistent connection, reducing latency for interactive applications.

25. API Rate Limiting

A strategy to control the number of API requests per user, preventing abuse and system overload. Rate limiting ensures fair usage, improves security, and prevents DDoS attacks.

26. OAuth & Authentication

OAuth is an authorization framework that allows secure third-party access without exposing user credentials. Common authentication methods include:

SAML – Often used for single sign-on (SSO) in enterprise environments.

JWT (JSON Web Tokens) – Stateless and secure token-based authentication.

OAuth 2.0 – Secure API access for third-party applications.

27. Data Consistency Models

• Strong Consistency – Ensures all nodes always have the same data, ideal for banking applications.
• Eventual Consistency – Allows temporary data divergence, resolving it over time, used in large-scale distributed systems like NoSQL databases.

28. Observability (Logging, Monitoring, Tracing)

A set of practices to track system performance:

• Logging – Captures system events and errors.
• Monitoring – Tracks application performance and resource usage.
• Tracing – Analyzes request flows in microservices architectures for debugging.

29. Scalability Strategies

Vertical Scaling – Adding more resources (CPU/RAM) to a single server.

Horizontal Scaling – Adding more servers to distribute the load, enhancing redundancy and failover protection.

30. Fault Tolerance & High Availability

• Fault Tolerance – Ensures the system continues operating even when components fail.
• High Availability – Minimizes downtime by maintaining redundancy, crucial for mission-critical applications like banking and healthcare systems.