Community driven roadmaps, articles and resources for developers

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• Frontend Roadmap / Frontend Beginner Roadmap
• Backend Roadmap / Backend Beginner Roadmap
• DevOps Roadmap / DevOps Beginner Roadmap
• Full Stack Roadmap
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Learn how to design large-scale systems.

Prep for the system design interview.

Learning how to design scalable systems will help you become a better engineer.

System design is a broad topic. There is a vast amount of resources scattered throughout the web on system design principles.

This repo is an organized collection of resources to help you learn how to build systems at scale.

This is a continually updated, open source project.

Contributions are welcome!

In addition…

LinkedIn | YouTube | X | Newsletter

Learn System Design concepts and prepare for interviews using free resources

• Scalability
• Latency vs Throughput
• CAP Theorem
• ACID Transactions
• Consistent Hashing
• Rate Limiting
• API Design
• Strong vs Eventual Consistency
• Synchronous vs. asynchronous communications
• REST vs RPC
• Batch Processing vs Stream Processing
• Fault Tolerance
• Consensus Algorithms
• Gossip Protocol
• Service Discovery
• Disaster Recovery
• Distributed Tracing
• Top 15 Tradeoffs

• Vertical vs Horizontal Scaling
• Databases
• Content Delivery Network (CDN)
• Domain Name System (DNS)
• Caching
• Distributed Caching
• Load Balancing
• SQL vs NoSQL
• Database Index
• Consistency Patterns
• HeartBeats
• Circuit Breaker
• Idempotency
• Database Scaling
• Data Replication
• Data Redundancy
• Database Sharding
• Database Architectures
• Microservices Guidelines
• Failover
• Proxy Server
• Message Queues
• WebSockets
• Bloom Filters
• API Gateway
• Distributed Locking
• Checksum

• Client-Server Architecture
• Microservices Architecture
• Serverless Architecture
• Event-Driven Architecture
• Peer-to-Peer (P2P) Architecture

I complied and collected some of the articles as a part of doing CS654A course at IIT Kanpur for a fantastic course on Advanced Software Architecture taught by Prof.Dr.T.V.Prabbhakar.

Modified from Zach system design repository. Added more links and topics to cover on both PS/DS & System Design Interviews. We will keep updating this posting from time to time. Some more awesome resource

I didn't write the articles myself. I love expanding my understanding of system design complexities and thus read many books, research papers, and articles that enhance my knowledge. I take the opportunity to thank everyone who found this repository useful. I would like to thank all the authors and developers who wrote the articles aggregated in this repository.

How to prepare system design questions for an IT company

System design is a very broad topic. Even a software engineer with many years of working experience at a top IT company may not be an expert on system design. If you want to become an expert, you need to read many books, articles, and solve real large scale system design problems.

This repository only teaches you how to handle the system design interview with a systematic approach in a short time. You can dive into each topic if you have time. Of course, welcome to add your thoughts!

• System Design Interview Tips
• Basic Knowledge about System Design
• Company Engineering Blogs
• Products and Systems
• Hot Questions and Reference
• Good Books
• Object Oriented Design

Clarify the constraints and identify the user cases

Spend a few minutes questioning the interviewer and agreeing on the…

Source: educative

• Scope the problem
  • Don’t make assumptions.
  • Ask clarifying questions to understand the constraints and use cases.
  • Steps
    • Requirements clarifications
    • System interface definition
• Sketch up an abstract design
  • Building blocks of the system
  • Relationships between them
  • Steps
    • Back-of-the-envelope estimation
    • Defining data model
    • High-level design
• Identify and address the bottlenecks
  • Use the fundamental principles of scalable system design
  • Steps
    • Detailed design
    • Identifying and resolving bottlenecks

• Key Characterics
• Load balancing
• Caching
• Sharding
• Indexes
• Proxies
• Queues
• Redundancy
• SQL vs. NoSQL
• CAP Theorem
• Consistent Hashing
• Client Server Communication

• Short URL Service
• Pastebin
• Instagram
• Dropbox
• Twitter
• Youtube
• Twitter Search
• Web Crawler
• Facebook Newsfeed
• Yelp
• Uber Backend
• Ticketmaster

• How to prepare for and answer system design questions

Learning about and implementing large-scale distributed system is not easy. I do not want…

Learn low level design of system at scale prepare for the low level design (LLD) / Machine Coding round interviews.

Learning low level design of scalable systems will help you become better engineer.

This repo is an organized collection of resources to help you learn low level design of systesm's.

• Low level Design Questions
• Low level Design Solutions
• Low Level Design Resources #TODO

Feel free to submit pull requests to help:

• Add new questions
• Improve new questions
• add new solutions
• Fix errors
• Improve sections
• Add new sections

Interested in adding a section or helping complete one in-progress? Contribute!

• how to guide and study material along with various resources.
• add more questions and improve exisiting questions.
• add solutions for the problems along with their detailed explaination (maybe video)

Credits and sources are provided throughout this repo.

Special…

Read this booklet here.

This booklet was my initial attempt to write about machine learning systems design back in 2019. My understanding of the topic has gone through significant iterations since then. My book Designing Machine Learning Systems (O'Reilly, June 2022) is much more comprehensive and up-to-date. The new book's repo contains the full table of contents, chapter summaries, and random thoughts on MLOps tooling.

This booklet covers four main steps of designing a machine learning system:

1. Project setup
2. Data pipeline
3. Modeling: selecting, training, and debugging
4. Serving: testing, deploying, and maintaining

It comes with links to practical resources that explain each aspect in more details. It also suggests case studies written by machine learning engineers at major tech companies who have deployed machine learning systems to solve real-world problems.

At the end, the booklet contains 27 open-ended machine learning systems design questions that might come…

【 👨🏻‍💻 YouTube | 📮 Newsletter 】

Explain complex systems using visuals and simple terms.

Whether you're preparing for a System Design Interview or you simply want to understand how systems work beneath the surface, we hope this repository will help you achieve that.

• Communication protocols
  • REST API vs. GraphQL
  • How does gRPC work?
  • What is a webhook?
  • How to improve API performance?
  • HTTP 1.0 -> HTTP 1.1 -> HTTP 2.0 -> HTTP 3.0 (QUIC)
  • SOAP vs REST vs GraphQL vs RPC
  • Code First vs. API First
  • HTTP status codes
  • What does API gateway do?
  • How do we design effective and safe APIs?
  • TCP/IP encapsulation
  • Why is Nginx called a “reverse” proxy?
  • What are the common load-balancing algorithms?
  • URL, URI, URN - Do you know the differences?
• CI/CD
  • CI/CD Pipeline Explained in Simple Terms
  • Netflix Tech Stack (CI/CD Pipeline)
• Architecture patterns
  • MVC, MVP, MVVM,…

These are the best resources for System Design on the Internet.

• Video Processing
• Cluster and Workflow Management
• Intra-Service Messaging
• Message Queue Antipattern
• Service Mesh
• Practical System Design
• Distributed File System
• Time Series Databases
• Rate Limiting
• In Memory Database - Redis
• Network Protocols
• Chess Engine Design
• Subscription Management System
• Google Docs
• API Design
• NoSQL Database Internals
• NoSQL Database Algorithms
• Database Replication
• Containers and Docker
• Capacity Estimation
• Publisher Subscriber
• Event Driven Architectures
• Software Architectures
• Microservices
• Distributed Transactions consistency Patterns
• Load Balancing
• Alerts and Anomaly Detection
• Distributed Logging
• Metrics and Text Search Engine
• Single Point of Failure
• Location Based Services
• Batch Processing
• Real Time Stream Processing
• Caching
• Distributed Consensus
• Authorization
• Content Delivery Network
• Testing Distributed Systems
• System Design Resources

• Transcoding Videos at Scale
• Facebook Video Broadcasting
• Netflix Video Encoding at Scale
• Netflix Shot based encoding

• Facebook Cluster Management
• Google Autopilot -…