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Sunil Notebook
Interview Preparation
  • 📒Notebook
    • What is this about ?
  • System Design
    • 💡Key Concepts
      • 🌐Scalability
      • 🌐Latency Vs Throughput
      • 🌐Databases
      • 🌐CAP Theorem
      • 🌐ACID Transactions
      • 🌐Rate limiting
      • 🌐API Design
      • 🌐Strong Vs eventual consistency
      • 🌐Distributed tracing
      • 🌐Synchronous Vs asynchronous Communication
      • 🌐Batch Processing Vs Stream Processing
      • 🌐Fault Tolerance
    • 💎Building Blocks
      • 🔹Message
      • 🔹Cache
      • 🔹Load Balancer Vs API Gateway
    • 🖥️Introduction to system design
    • ⏱️Step By Step Guide
    • ♨️Emerging Technologies in System Design
    • ☑️System design component checklist
      • 🔷Azure
      • 🔶AWS
      • ♦️Google Cloud
    • 🧊LinkedIn feed Design
    • 🏏Scalable Emoji Broadcasting System - Hotstar
    • 💲UPI Payment System Design
    • 📈Stock Broker System Design - Groww
    • 🧑‍🤝‍🧑Designing Instagram's Collaborative Content Creation - Close Friends Only
    • 🌳Vending Machines - Over the air Systems
    • Reference Links
  • DSA
    • Topics
      • Introduction
      • Algorithm analysis
        • Asymptotic Notation
        • Memory
      • Sorting
        • Selection Sort
        • Insertion Sort
        • Merge Sort
        • Quick Sort
        • Quick'3 Sort
        • Shell Sort
        • Shuffle sort
        • Heap Sort
        • Arrays.sort()
        • Key Points
        • Problems
          • Reorder Log files
      • Stacks and Queues
        • Stack Implementations
        • Queue Implementations
        • Priority Queues
        • Problems
          • Dijkstra's two-stack algorithm
      • Binary Search Tree
        • Left Leaning Red Black Tree
          • Java Implementations
        • 2-3 Tree
          • Search Operation - 2-3 Tree
          • Insert Operation - 2-3 Tree
        • Geometric Applications of BST
      • B-Tree
      • Graphs
        • Undirected Graphs
        • Directed Graphs
        • Topological Sort
      • Union Find
        • Dynamic Connectivity
        • Quick Find - Eager Approach
        • Quick Find - Lazy Approach
        • Defects
        • Weighted Quick Union
        • Quick Union + path comparison
        • Amortized Analysis
      • Convex Hull
      • Binary Heaps and Priority Queue
      • Hash Table vs Binary Search Trees
  • Concurrency and Multithreading
    • Introduction
    • Visibility Problem
    • Interview Questions
    • References
      • System design
  • Design Patterns
    • ℹ️Introduction
    • 💠Classification of patterns
    • 1️⃣Structural Design Patterns
      • Adapter Design Pattern
      • Bridge Design Pattern
      • Composite Design Pattern
      • Decorator Design Pattern
      • Facade Design Pattern
      • Flyweight Design Pattern
      • Private Class Data Design Pattern
      • Proxy Design Pattern
    • 2️⃣Behavioral Design Patterns
      • Chain Of Responsibility
      • Command Design Pattern
      • Interpreter Design Pattern
      • Iterator Design Pattern
      • Mediator Design Pattern
      • Memento Design Pattern
      • Null Object Design Pattern
      • Observer Design Pattern
      • State Design Pattern
      • Strategy Design Pattern
      • Template Design Pattern
    • 3️⃣Creational Design Patterns
      • Abstract Factory Design Pattern
      • Builder Design Pattern
      • Factory Method Design Pattern
      • Object Pool Design Pattern
      • Prototype Design Pattern
      • Singleton Design Pattern
    • Java Pass by Value or Pass by Reference
  • Designing Data-Intensive Applications - O'Reilly
    • Read Me
    • 1️⃣Reliable, Scalable, and Maintainable Applications
      • Reliability
      • Scalability
      • Maintainability
      • References
    • 2️⃣Data Models and Query Languages
      • Read me
      • References
    • Miscellaneous
  • Preparation Manual
    • Disclaimer
    • What is it all about?
    • About a bunch of links
    • Before you start preparing
    • Algorithms and Coding
    • Concurrency and Multithreading
    • Programming Language and Fundementals
    • Best Practices and Experience
  • Web Applications
    • Typescript Guidelines
  • Research Papers
    • Research Papers
      • Real-Time Data Infrastructure at Uber
      • Scaling Memcache at Facebook
  • Interview Questions
    • Important links for preparation
    • Google Interview Questions
      • L4
        • Phone Interview Questions
      • L3
        • Interview Questions
      • Phone Screen Questions
  • Miscellaneous
    • 90 Days Preparation Schedule
    • My Preparation for Tech Giants
    • Top Product Based Companies
  • Links
    • Github
    • LinkedIn
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  1. System Design

Introduction to system design

In common words, System design is nothing but creating the blue print for the Software, like how the civil engineer has the blue print for the Entire Building/ corporate society. This is very crucial for the development of the large scale applications, especially those expected to handle high traffic, large amounts of data, and complex operations.

It is often a key topic in technical interviews for software engineering roles, particularly for senior positions, as it demonstrates the candidate's ability to think critically about the structure and functioning of complex systems.

Below are the list of key concepts:

  1. Scalability: Scalability in system design refers to the ability of a system to handle a growing amount of work, or its potential to be enlarged to accommodate that growth. This can involve various dimensions, such as:

    • Horizontal Scalability: Adding more machines or nodes to a system to distribute the load. For example, adding more servers to handle more web traffic.

    • Vertical Scalability: Adding more power (CPU, RAM) to an existing machine to handle more load.

    • Performance Scalability: Maintaining or improving performance levels as the system scales up. This means that the system can handle more requests per second, perform more transactions, or store more data without a decrease in performance.

    • Geographical Scalability: Ensuring the system can operate efficiently across multiple geographic locations. This involves distributing data centers and ensuring low-latency access to users globally.

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Last updated 10 months ago

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