System Design Essentials

Introduction

• Aim to level up from Junior Dev by mastering 20 essential system design concepts.
• Concepts include networking, API patterns, databases, and more.
• Resources available at neetcode.io

Scaling Applications

Vertical Scaling

• Add more resources like RAM or upgrade CPU.
• Easier but very limited.

Horizontal Scaling

• Add server replicas to handle more requests.
• Allows for near-infinite scaling.
• Adds redundancy and fault tolerance.
• More complex than vertical scaling.

Load Balancers

• Ensure even distribution of traffic across servers.
• Reverse proxy server that directs incoming requests.
• Common algorithms: round robin, request ID hashing.
• Can help route requests to nearest server location.

Content Delivery Networks (CDN)

• Used for serving static files.
• Network of servers worldwide that cache data.
• Can use push or pull method for caching.

Caching Techniques

• Important for faster data retrieval.
• Different levels: network request, disk, memory, CPU cache.

Networking Basics

IP Addresses

• Unique identifier for devices on a network.

TCP/IP Protocol Suite

• Reliable protocol for data transmission over the internet.
• Data sent in packets; TCP ensures packets are resent if needed.

Domain Name System (DNS)

• Translates domains to IP addresses.
• DNS queries resolve domain name to IP address, cached for efficiency.

HTTP Protocol

• Client-server model for web communication.
• Requests include headers (metadata) and body (content).
• Response includes headers and body.

API Patterns: REST

• Stateless HTTP APIs.
• Standardized response codes: 200 (success), 400 (client error), 500 (server error).

API Patterns: GraphQL

• Allows fetching multiple resources with a single request.

API Patterns: gRPC

• Framework for server-to-server communication, using Protocol Buffers.
• More storage-efficient than JSON.

WebSockets

• Enables bi-directional communication.
• Useful for real-time applications like chat apps.

Data Storage

SQL Databases

• Use data structures like B-trees for efficient data storage and retrieval.
• ACID compliant (Atomicity, Consistency, Isolation, Durability).

NoSQL Databases

• Drop consistency constraints for scalability.
• Types: key-value stores, document stores, graph databases.

Sharding

• Technique to horizontally scale databases.
• Uses a Shard key to distribute data.

Replication

• Read-only copies of databases for scaling reads.
• Leader-follower and leader-leader replication techniques.

CAP Theorem

• Trade-offs in replicated databases: consistency vs. availability.

Message Queues

• Durable storage with replication/sharding.
• Decouple parts of applications for better data processing.

Conclusion

• Software engineering involves efficient data storage and movement.
• Further learning resources available at neetcode.io.