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Essential Concepts for System Design
Sep 16, 2024
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.
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