System Design was HARD until I Learned these 30 Concepts

Summary

This video covers essential system design concepts for aspiring senior engineers or tech professionals aiming for high-paying roles. It introduces key topics like client-server architecture, DNS, HTTP/HTTPS, APIs, databases (SQL vs NoSQL), scaling (vertical vs horizontal), load balancing, database optimization, caching, and distributed systems. The video also explains microservices, message queues, rate limiting, API gateways, and ensuring idempotency in distributed systems. By mastering these core principles, viewers can build scalable, efficient systems and excel in system design interviews.

Takeaways

• 🚀 System design fundamentals are essential to advance from junior to senior roles and succeed in big tech interviews.
• 🖥️ Most web apps are built on client-server architecture, where clients send requests and servers process and respond.
• 🌐 DNS maps human-friendly domain names to IP addresses so clients can locate servers on the internet.
• 🔒 HTTP enables communication, while HTTPS secures data using encryption via SSL/TLS.
• 🔌 APIs abstract low-level details and enable structured communication, commonly using REST or GraphQL.
• 📦 REST is simple and scalable but can over-fetch data, while GraphQL lets clients request exactly what they need.
• 🗄️ Databases are central to system design, with SQL for strong consistency and NoSQL for scalability and flexible schemas.
• 📈 Vertical scaling upgrades a single machine, while horizontal scaling adds more machines for better reliability and capacity.
• ⚖️ Load balancers distribute traffic across servers to improve performance and handle failures gracefully.
• 🔍 Indexing speeds up reads, replication scales reads, and sharding partitions data to scale writes and storage.
• 🧠 Caching frequently accessed data in memory dramatically reduces latency and database load.
• 🧩 Denormalization improves read performance by reducing joins, at the cost of extra storage and complex updates.
• 🔺 The CAP theorem states that distributed systems must trade off between consistency, availability, and partition tolerance.
• 📁 Blob storage and CDNs enable scalable, fast delivery of large files like images and videos worldwide.
• ⚡ WebSockets enable real-time two-way communication, while webhooks notify systems instantly when events occur.
• 🧱 Microservices decompose monoliths into independent services that scale and deploy independently.
• 📨 Message queues enable asynchronous communication and decouple services for better scalability.
• 🚫 Rate limiting and API gateways protect systems from abuse and centralize cross-cutting concerns.
• 🔁 Idempotency ensures repeated requests (like payments) are processed safely without duplication.

Q & A

What is client-server architecture, and how does it work?

Client-server architecture is the fundamental model for web applications, where the client (such as a web browser or mobile app) sends requests to a server to retrieve, modify, or store data. The server processes the request and responds back with the appropriate data. The client identifies the server using its IP address, which is mapped from the human-readable domain name through DNS (Domain Name System).

What role does DNS play in client-server communication?

DNS (Domain Name System) acts as a translator that maps human-readable domain names (like algo master.io) to their corresponding IP addresses. Without DNS, users would need to remember and input IP addresses to access websites, which is not practical.

How do proxy and reverse proxy servers differ?

A proxy server acts as a middleman between the client and the internet, hiding the client's IP address to maintain privacy. A reverse proxy, on the other hand, forwards client requests to backend servers based on predefined rules, often used to balance load or enhance security.

What is latency, and how can it be reduced?

Latency is the delay between sending a request and receiving a response, often caused by the physical distance between the client and the server. To reduce latency, services can be deployed in multiple data centers around the world so that users can connect to the nearest server.

What is the difference between REST and GraphQL APIs?

REST is a widely used API design that follows a set of rules for communication between clients and servers, using standard HTTP methods (GET, POST, PUT, DELETE). It is simple and stateless but can be inefficient for complex data retrieval. GraphQL, on the other hand, allows clients to specify exactly what data they need, reducing over-fetching, but it requires more server-side processing.

When should you use SQL vs. NoSQL databases?

SQL databases are best for applications that require structured data, strong consistency, and relational relationships (e.g., banking systems). NoSQL databases are better for applications that need high scalability, flexible schemas, and can handle large, unstructured data (e.g., social media platforms). Many modern applications use a combination of both.

What are vertical scaling and horizontal scaling, and which one is more efficient?

Vertical scaling involves upgrading a single server's resources (CPU, RAM, storage) to handle more traffic, but it has limitations in capacity and reliability. Horizontal scaling, or scaling out, involves adding more servers to distribute the load, providing better scalability and fault tolerance.

What is the role of a load balancer in a horizontally scaled system?

A load balancer sits between clients and backend servers, distributing incoming requests to different servers based on various algorithms (e.g., round-robin or least connections). It ensures even traffic distribution and improves reliability by redirecting traffic to healthy servers if one fails.

How does sharding improve database scalability?

Sharding is a technique where a database is divided into smaller, manageable parts (called shards), each handling a subset of the data. This reduces the load on individual servers and improves performance by distributing queries across multiple servers.

What is caching, and how does it optimize system performance?

Caching stores frequently accessed data in memory instead of retrieving it from slower storage systems (like databases). This significantly reduces response times for repeated requests. The Cache Aside pattern involves checking the cache first before fetching data from the database and updating the cache when data is fetched.

What is the CAP theorem, and how does it apply to distributed systems?

The CAP theorem states that in a distributed system, you cannot achieve all three of the following simultaneously: Consistency, Availability, and Partition Tolerance. Given inevitable network failures, systems must choose between consistency and partition tolerance or availability and partition tolerance.

How do WebSockets differ from HTTP for real-time communication?

WebSockets enable continuous, two-way communication between a client and a server over a single persistent connection. Unlike HTTP, where each request requires a new connection, WebSockets allow real-time updates without repeated polling, making them more efficient for applications like live chat or online games.

What are microservices, and how do they improve scalability?

Microservices are a design pattern where applications are broken down into smaller, independent services, each responsible for a specific function. They communicate via APIs or message queues, allowing for independent scaling and deployment. This approach is more manageable and scalable than monolithic architectures.

What is the purpose of an API gateway in a microservices architecture?

An API gateway acts as a single entry point for client requests, routing them to the appropriate microservice. It centralizes functions like authentication, rate limiting, logging, and monitoring, simplifying the management of APIs and improving security and scalability.

What is idempotency, and why is it important in distributed systems?

Idempotency ensures that repeated requests produce the same result, preventing errors from duplicated actions. For example, if a user accidentally submits a payment twice, idempotency guarantees that the system processes the payment only once, ensuring consistency.