System Design
Learn System Design
Introduction to System Design
How to Learn System Design?
Key Characteristics of Distributed Systems
Scalability
Availability
Latency and Performance
Concurrency and Coordination
Monitoring and Observability
Resilience and Error Handling
Fault Tolerance vs. High Availability
Flashcards Review
Chapter Assessment
Network Essentials
HTTP vs. HTTPS
TCP vs. UDP
HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0
URL vs. URI vs. URN
What Happens When You Type a URL into the Browser
Flashcards Review
Chapter Assessment
Long-Polling vs. WebSockets vs. Server-Sent Events
Introduction to Real-Time Communication
What is Long-Polling?
What is WebSocket?
What are Server-Sent Events?
Difference Between Long-Polling, WebSockets, and Server-Sent Events
Flashcards Review
Chapter Assessment
Domain Name System (DNS)
Introduction to DNS
DNS Resolution Process
DNS Load Balancing and High Availability
Flashcards Review
Chapter Assessment
Proxies
What is a Proxy Server?
Uses of Proxies
VPN vs. Proxy Server
Flashcards Review
Chapter Assessment
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
Flashcards Review
Chapter Assessment
API Gateway
Introduction to API Gateway
Usage of API gateway
Advantages and disadvantages of using API gateway
Flashcards Review
Chapter Assessment
API Design
What Is an API?
What Are REST APIs?
Resources, Not Actions
HTTP Methods and Their Semantics
URL Design
Request and Response Shapes
Status Codes and Error Design
Pagination from the Consumer's View
Idempotency Keys
Versioning and Backward Compatibility
Concurrency and Conditional Requests
REST vs gRPC vs GraphQL
Flashcards Review
Chapter Assessment
Rate Limiting and Throttling
What Is Rate Limiting
Rate Limiting Algorithms
Distributed Rate Limiting
Rate Limiting in Practice
Flashcards Review
Chapter Assessment
Caching
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
Flashcards Review
Chapter Assessment
CDN
What is CDN?
Origin Server vs. Edge Server
CDN Architecture
Push CDN vs. Pull CDN
Flashcards Review
Chapter Assessment
Data Partitioning
Introduction to Data Partitioning
Partitioning Methods
Data Sharding Techniques
Benefits of Data Partitioning
Common Problems Associated with Data Partitioning
Flashcards Review
Chapter Assessment
Redundancy and Replication
What is Redundancy?
What is Replication?
Replication Methods
Data Backup vs. Disaster Recovery
Flashcards Review
Chapter Assessment
CAP & PACELC Theorems
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
Flashcards Review
Chapter Assessment
Databases (SQL vs. NoSQL)
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
Flashcards Review
Chapter Assessment
Indexes
What are Indexes?
How a B-Tree Index Works
Types of Indexes
B-Tree vs. LSM Tree
Indexes in Distributed Systems
Flashcards Review
Chapter Assessment
Bloom Filters
Introduction to Bloom Filters
Benefits & Limitations of Bloom Filters
Variants and Extensions of Bloom Filters
Applications of Bloom Filters
Flashcards Review
Chapter Assessment
Quorum
Why Quorum?
What is Quorum?
Flashcards Review
Chapter Assessment
Leader and Follower
What is Leader and Follower Pattern?
Flashcards Review
Chapter Assessment
Heartbeat
What is Heartbeat?
Flashcards Review
Chapter Assessment
Checksum
What is Checksum?
Uses of Checksum
Flashcards Review
Chapter Assessment
Distributed Messaging System
Introduction to Messaging System
Introduction to Kafka
Messaging patterns
Popular Messaging Queue Systems
RabbitMQ vs. Kafka vs. ActiveMQ
Scalability and Performance
Flashcards Review
Chapter Assessment
Distributed File Systems
What is a Distributed File System?
Architecture of a Distributed File System
Key Components of a DFS
Flashcards Review
Chapter Assessment
Security
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?
Flashcards Review
Chapter Assessment
Misc Concepts
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
Flashcards Review
Chapter Assessment
Quiz - System Design Fundamentals
Quiz
How to Approach a System Design Interview
System Design Interviews - A step by step guide
Functional vs. Non-functional Requirements
What are Back-of-the-Envelope Estimations?
Things to Avoid During System Design Interview
System Design Master Template
System Design Master Template
Quiz
Designing a URL Shortening Service like TinyURL
Designing a URL Shortening Service like TinyURL
Quiz - Designing URL Shortner
Designing Pastebin
Designing Pastebin
Quiz - Designing Pastebin
Designing Instagram
Designing Instagram
Quiz - Designing Instagram
Designing Dropbox
Designing Dropbox
Quiz - Designing Dropbox
Designing Facebook Messenger
Designing Facebook Messenger
Quiz - Designing Facebook Messenger
Designing Twitter
Designing Twitter
Quiz - Designing Twitter
Designing Youtube or Netflix
Designing Youtube or Netflix
Quiz - Designing Youtube
Designing Typeahead Suggestion
Designing Typeahead Suggestion
Quiz - Designing Typeahead Suggestion
Designing an API Rate Limiter
Designing an API Rate Limiter
Quiz - Designing an API Rate Limiter
Designing Twitter Search
Designing Twitter Search
Quiz - Designing Twitter Search
Designing a Web Crawler
Designing a Web Crawler
Quiz - Designing a Web Crawler
Designing Facebook’s Newsfeed
Designing Facebook’s Newsfeed
Quiz - Designing Facebook’s Newsfeed
Designing Yelp or Nearby Friends
Designing Yelp or Nearby Friends
Quiz - Designing Yelp or Nearby Friends
Designing Uber backend
Designing Uber backend
Quiz - Designing Uber backend
Designing Ticketmaster
Designing Ticketmaster
Quiz - Designing Ticketmaster
Dynamo: How to design a key value store?
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
Designing YouTube Likes Counter (medium)
YouTube Likes Counter
Quiz
Cassandra: How to Design a Wide-column NoSQL Database?
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
Kafka: How to Design a Distributed Messaging System?
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: How to Design a Distributed Locking Service?
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
HDFS: How to Design File Storage System?
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
GFS: How to Design a Distributed File System Storage?
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: How to Design a Wide Column Storage System?
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
Designing Reddit (medium)
Design Reddit
Quiz
Designing Notification Service (medium)
Designing a Notification System
Quiz
Design Google Calendar (medium)
Design Google calendar (Medium)
Quiz
Design a Recommendation System (medium)
Design a Recommendation System for Netflix
Quiz
Designing Gmail (medium)
Design Gmail
Quiz
Designing Google News (medium)
Design Google News, a Global News Aggregator System (Medium)
Quiz
Designing Unique ID Generator (medium)
Design Unique ID Generator (Easy)
Quiz
Designing Code Judging System (medium)
Design Code Judging System like LeetCode (Medium)
Quiz
Designing Payment System (hard)
Design Payment System
Quiz
Designing Flash Sale System (hard)
Design a Flash Sale for an E-commerce Site (Hard)
Quiz
Designing Reminder Alert System (hard)
Design a Reminder Alert System
Quiz
System Design Patterns
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
Stateful vs Stateless Architecture
stateful architecture
stateless architecture
distributed systems
load balancing
+3
A user logs in, and server 1 handles the request. Their next click lands on server 3. Does server 3 know who they are?
That depends on one design choice. State is the data a system remembers between requests: who is logged in, what is in the cart, a half-written draft. The question this lesson answers is simple. Does that state stay inside one server's memory, or in a shared place every server can reach?
Clear up the common confusion first. Stateless does not mean the state disappears. Almost every application has state. A stateless server keeps no state in its own process. The state still exists. It moves to a database, a shared cache, or the request itself.
One more thing before the options. These are not two equal choices. Stateless is the default for backend systems. Stateful servers are the exception, kept for a few specific jobs. This lesson covers what stateless buys you, and when stateful is genuinely justified.
Stateless Servers: The Default
In a stateless design, the state moves to one of three places.
- A shared store. A database or a Redis cache holds the session, the record of who a logged-in user is. Every server reads it. This is the most common arrangement.
- A signed token. The client carries a token that proves who the user is. The server checks the signature and needs no lookup.
- The request itself. Everything needed to answer is inside the request. This is what people mean when they call REST stateless.
An online banking application shows why the distinction confuses people. The bank clearly remembers who you are. But your session sits in a shared store, found by a cookie. So any application server can serve your next request. The system has state. The servers do not.
What stateless buys you.
- Any server can take any request. No server holds anything the others lack, so the servers are interchangeable.
- Scaling is simple. Add a server and it takes traffic at once. Nothing must be copied to it first.
- Failure is cheap. A server dies, and the load balancer sends its requests elsewhere. No sessions are lost. Nobody is logged out.
- Deploys are safe. You can restart servers one at a time, because no server holds anything worth keeping.
There is one more gain. You never need sticky sessions, a load balancer rule that sends each user back to the same machine every time. Sticky sessions exist only to protect state kept inside a server. They make load uneven, and when that machine dies, its users lose whatever it held.
Stateful Servers: The Exception
A stateful server keeps data in its own memory between requests. Only that machine can serve the users whose data it holds.
A few real cases justify this. The pattern behind all of them is the same. State stays in the process when it changes too fast to store outside, or when the connection itself is the state.
- WebSocket and chat gateways. A WebSocket is a long-lived connection between a client and one server, used for live updates. The open connection cannot be moved or shared. A message for a user must reach the exact machine holding that user's socket. Polling vs Long-Polling vs Webhooks covers the delivery options themselves.
- Real-time game servers. A match changes many times per second. A database write for every action would be far too slow. So the match state stays in memory, and players are routed to the machine running their match.
- Legacy session-in-memory applications. Some older systems keep each user's session in the application's own memory, found by a session id in a cookie. These systems need sticky sessions to work at all.
- Stream processors and coordination services. Apache Flink holds running counts in memory as events arrive. ZooKeeper and etcd, which help many machines agree on shared values, hold data and roles on purpose.
What Stateful Costs
Keeping state in the process buys speed, or makes the connection possible. In exchange, you take on three problems.
- Routing. Something must know which machine holds which user's state. That means a registry, or consistent hashing.
- Failure. When the machine dies, its memory is gone. To survive that, you must copy the state to other machines, and that is a project of its own.
- Deploys. You cannot simply restart. You must drain connections, hand the state over, or accept a disruption.
None of these are unsolvable. They are extra work that a stateless design never asks for. That is why stateless is the default.
The Trade-off
| Stateless | Stateful | |
|---|---|---|
| Where state is stored | Shared store, token, or the request | In the server's memory |
| Adding a server | Useful at once | Needs routing, maybe data movement |
| A server dies | Requests go elsewhere, nothing lost | Its state is gone unless copied |
| Load balancing | Any server, any request | Sticky sessions or a registry |
| How common | The default | The exception |
| Used for | Web and API tiers | Games, socket gateways, stream processing, coordination |
Choosing
- Web and API tiers: stateless. Put sessions in a shared cache or a signed token. This should be your starting answer in almost every design.
- Open connections, such as chat or live updates: a stateful gateway. Keep that layer thin, and keep everything behind it stateless.
- State that changes many times per second, such as games: stateful, with routing. Send each user to the machine that holds their state.
- Never keep ordinary web sessions in server memory. That choice forces sticky sessions, and every crash logs users out.
💡 In the interview: say "the application tier is stateless" early, and say where the state went. For example: "App servers are stateless. Sessions are in Redis, so I can add or lose a server without logging anyone out." If your design uses WebSockets, raise the exception yourself. Say that those gateway servers are stateful, because each one holds open connections. Expect the follow-up: how does a message find the right gateway? Answer with a registry that maps each connected user to the machine holding their socket.
Key takeaway: stateless does not mean there is no state. It means no state is kept inside the server process. The state moves to a shared store, a signed token, or the request, and every server becomes interchangeable. That is what makes scaling, failure, and deploys simple, and it is the default for backend systems. Stateful servers are the exception, justified when state changes too fast to store outside, or when the open connection is the state. Choosing stateful means taking on routing, replication, and careful deploys.
Discussion
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