System Design

Learn System Design

How to Learn System Design?

Functional vs. Non-functional Requirements

What are Back-of-the-Envelope Estimations?

Things to Avoid During System Design Interview

System Design Basics

Load Balancing

Introduction to Load Balancing

Load Balancing Algorithms

Uses of Load Balancing

Load Balancer Types

Stateless vs. Stateful Load Balancing

High Availability and Fault Tolerance

Scalability and Performance

Challenges of Load Balancers

Introduction to API Gateway

Usage of API gateway

Advantages and disadvantages of using API gateway

Scalability

Availability

Latency and Performance

Concurrency and Coordination

Monitoring and Observability

Resilience and Error Handling

Fault Tolerance vs. High Availability

HTTP vs. HTTPS

TCP vs. UDP

HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0

URL vs. URI vs. URN

Introduction to DNS

DNS Resolution Process

DNS Load Balancing and High Availability

Introduction to Caching

Why is Caching Important?

Types of Caching

Cache Replacement Policies

Cache Invalidation

Cache Read Strategies

Cache Coherence and Consistency Models

Caching Challenges

Cache Performance Metrics

What is CDN?

Origin Server vs. Edge Server

CDN Architecture

Push CDN vs. Pull CDN

Introduction to Data Partitioning

Partitioning Methods

Data Sharding Techniques

Benefits of Data Partitioning

Common Problems Associated with Data Partitioning

What is a Proxy Server?

Uses of Proxies

VPN vs. Proxy Server

What is Redundancy?

What is Replication?

Replication Methods

Data Backup vs. Disaster Recovery

Introduction to CAP Theorem

Components of CAP Theorem

Trade-offs in CAP Theorem

Examples of CAP Theorem in Practice

Beyond CAP Theorem

System Design Trade-offs in Interviews

Introduction to Databases

SQL Databases

NoSQL Databases

SQL vs. NoSQL

ACID vs BASE Properties

Real-World Examples and Case Studies

SQL Normalization and Denormalization

In-Memory Database vs. On-Disk Database

Data Replication vs. Data Mirroring

Database Federation

What are Indexes?

Types of Indexes

Introduction to Bloom Filters

Benefits & Limitations of Bloom Filters

Variants and Extensions of Bloom Filters

Applications of Bloom Filters

Difference Between Long-Polling, WebSockets, and Server-Sent Events

Why Quorum?

What is Quorum?

What is Heartbeat?

What is Checksum?

Uses of Checksum

What is Leader and Follower Pattern?

What is Security and Privacy?

What is Authentication?

What is Authorization?

Authentication vs. Authorization

OAuth vs. JWT for Authentication

What is Encryption?

What are DDoS Attacks?

Introduction to Messaging System

Introduction to Kafka

Messaging patterns

Popular Messaging Queue Systems

RabbitMQ vs. Kafka vs. ActiveMQ

Scalability and Performance

What is a Distributed File System?

Architecture of a Distributed File System

Key Components of a DFS

Batch Processing vs. Stream Processing

XML vs. JSON

Synchronous vs. Asynchronous Communication

Push vs. Pull Notification Systems

Microservices vs. Serverless Architecture

Message Queues vs. Service Bus

Stateful vs. Stateless Architecture

Event-Driven vs. Polling Architecture

Quiz

Importance of Discussing Trade-offs

Strong vs Eventual Consistency

Latency vs Throughput

ACID vs BASE Properties in Databases

Read-Through vs Write-Through Cache

Batch Processing vs Stream Processing

Load Balancer vs. API Gateway

API Gateway vs Direct Service Exposure

Proxy vs. Reverse Proxy

API Gateway vs. Reverse Proxy

SQL vs. NoSQL

Primary-Replica vs Peer-to-Peer Replication

Data Compression vs Data Deduplication

Server-Side Caching vs Client-Side Caching

REST vs RPC

Polling vs. Long-Polling vs. WebSockets vs. Webhooks

CDN Usage vs Direct Server Serving

Serverless Architecture vs Traditional Server-based

Stateful vs Stateless Architecture

Hybrid Cloud Storage vs All-Cloud Storage

Token Bucket vs Leaky Bucket

Read Heavy vs Write Heavy System

Quiz

System Design Interviews - A step by step guide

System Design Master Template

Designing a URL Shortening Service like TinyURL

Quiz - Designing URL Shortner

Designing Pastebin

Quiz - Designing Pastebin

Designing Instagram

Quiz - Designing Instagram

Designing Dropbox

Quiz - Designing Dropbox

Designing Facebook Messenger

Quiz - Designing Facebook Messenger

Designing Twitter

Quiz - Designing Twitter

Designing Youtube or Netflix

Quiz - Designing Youtube

Designing Typeahead Suggestion

Quiz - Designing Typeahead Suggestion

Designing an API Rate Limiter

Quiz - Designing an API Rate Limiter

Designing Twitter Search

Quiz - Designing Twitter Search

Designing a Web Crawler

Quiz - Designing a Web Crawler

Designing Facebook’s Newsfeed

Quiz - Designing Facebook’s Newsfeed

Designing Yelp or Nearby Friends

Quiz - Designing Yelp or Nearby Friends

Designing Uber backend

Quiz - Designing Uber backend

Designing Ticketmaster

Quiz - Designing Ticketmaster

Dynamo: Introduction

High-Level Architecture

Data Partitioning

Replication

Vector Clocks and Conflicting Data

The Life of Dynamo’s put() & get() Operations

Anti-entropy Through Merkle Trees

Gossip Protocol

Dynamo Characteristics and Criticism

Summary: Dynamo

Quiz: Dynamo

Mock Interview: Dynamo

YouTube Likes Counter

Quiz

Cassandra: Introduction

High-level Architecture

Replication

Cassandra Consistency Levels

Gossiper

Anatomy of Cassandra's Write Operation

Anatomy of Cassandra's Read Operation

Compaction

Tombstones

Summary: Cassandra

Quiz: Cassandra

Mock Interview: Cassandra

Messaging Systems: Introduction

Kafka: Introduction

High-level Architecture

Kafka: Deep Dive

Consumer Groups

Kafka Workflow

Role of ZooKeeper

Controller Broker

Kafka Delivery Semantics

Kafka Characteristics

Summary: Kafka

Quiz: Kafka

Mock Interview: Kafka

Chubby: Introduction

High-level Architecture

Design Rationale

How Chubby Works

File, Directories, and Handles

Locks, Sequencers, and Lock-delays

Sessions and Events

Master Election and Chubby Events

Caching

Database

Scaling Chubby

Summary: Chubby

Quiz: Chubby

Mock Interview: Chubby

Hadoop Distributed File System: Introduction

High-level Architecture

Deep Dive

Anatomy of a Read Operation

Anatomy of a Write Operation

Data Integrity & Caching

Fault Tolerance

HDFS High Availability (HA)

HDFS Characteristics

Summary: HDFS

Quiz: HDFS

Mock Interview: HDFS

Google File System: Introduction

High-level Architecture

Single Master and Large Chunk Size

Metadata

Master Operations

Anatomy of a Read Operation

Anatomy of a Write Operation

Anatomy of an Append Operation

GFS Consistency Model and Snapshotting

Fault Tolerance, High Availability, and Data Integrity

Garbage Collection

Criticism on GFS

Summary: GFS

Quiz: GFS

Mock Interview: GFS

BigTable: Introduction

BigTable Data Model

System APIs

Partitioning and High-level Architecture

SSTable

GFS and Chubby

Bigtable Components

Working with Tablets

The Life of BigTable's Read & Write Operations

Fault Tolerance and Compaction

BigTable Refinements

BigTable Characteristics

Summary: BigTable

Quiz: BigTable

Mock Interview: BigTable

Design Reddit

Quiz

Designing a Notification System

Quiz

Design Google calendar (Medium)

Quiz

Design a Recommendation System for Netflix

Quiz

Design Gmail

Quiz

Design Google News, a Global News Aggregator System (Medium)

Quiz

Design Unique ID Generator (Easy)

Quiz

Design Code Judging System like LeetCode (Medium)

Quiz

Design Payment System

Quiz

Design a Flash Sale for an E-commerce Site (Hard)

Quiz

Design a Reminder Alert System

Quiz

Introduction: System Design Patterns

1. Bloom Filters

2. Consistent Hashing

3. Quorum

4. Leader and Follower

5. Write-ahead Log

6. Segmented Log

7. High-Water Mark

8. Lease

9. Heartbeat

10. Gossip Protocol

11. Phi Accrual Failure Detection

12. Split Brain

13. Fencing

14. Checksum

15. Vector Clocks

16. CAP Theorem

17. PACELC Theorem

18. Hinted Handoff

19. Read Repair

20. Merkle Trees

Quiz

Introduction to Load Balancing

Introduction to Load Balancing

load balancing

high availability

scalability

performance

+1

medium
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5 min
·Updated Jan 2025

Load balancing is a crucial component of System Design, as it helps distribute incoming requests and traffic evenly across multiple servers. The main goal of load balancing is to ensure high availability, reliability, and performance by avoiding overloading a single server and avoiding downtime.

Typically a load balancer sits between the client and the server accepting incoming network and application traffic and distributing the traffic across multiple backend servers using various algorithms. By balancing application requests across multiple servers, a load balancer reduces the load on individual servers and prevents any one server from becoming a single point of failure, thus improving overall application availability and responsiveness.

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To utilize full scalability and redundancy, we can try to balance the load at each layer of the system. We can add LBs at three places:

  • Between the user and the web server
  • Between web servers and an internal platform layer, like application servers or cache servers
  • Between internal platform layer and database.
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Key terminology and concepts

Load Balancer: A device or software that distributes network traffic across multiple servers based on predefined rules or algorithms.

Backend Servers: The servers that receive and process requests forwarded by the load balancer. Also referred to as the server pool or server farm.

Load Balancing Algorithm: The method used by the load balancer to determine how to distribute incoming traffic among the backend servers.

Health Checks: Periodic tests performed by the load balancer to determine the availability and performance of backend servers. Unhealthy servers are removed from the server pool until they recover.

Session Persistence: A technique used to ensure that subsequent requests from the same client are directed to the same backend server, maintaining session state and providing a consistent user experience.

SSL/TLS Termination: The process of decrypting SSL/TLS-encrypted traffic at the load balancer level, offloading the decryption burden from backend servers and allowing for centralized SSL/TLS management.

How Load Balancer works?

Load balancers work by distributing incoming network traffic across multiple servers or resources to ensure efficient utilization of computing resources and prevent overload. Here are the general steps that a load balancer follows to distribute traffic:

  1. The load balancer receives a request from a client or user.
  2. The load balancer evaluates the incoming request and determines which server or resource should handle the request. This is done based on a predefined load-balancing algorithm that takes into account factors such as server capacity, server response time, number of active connections, and geographic location.
  3. The load balancer forwards the incoming traffic to the selected server or resource.
  4. The server or resource processes the request and sends a response back to the load balancer.
  5. The load balancer receives the response from the server or resource and sends it to the client or user who made the request.
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