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Премиум
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    What do we offer?
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    What are Databases?
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    Storage and Retrieval
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    What is a NoSQL database?
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    Types of Databases: Graph, TimeSeries and Object
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    What database should you choose?
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    What is Data Consistency?
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    Linearizable Consistency
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    Eventual Consistency
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    Causal Consistency
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    Quorum
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    Data Consistency Levels Tradeoffs
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    Transaction Isolation Levels - Read Uncommitted Data
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    Read Committed
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    Repeatable Reads
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    Serializable Isolation Level
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    Transaction Level Implementations
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    Conclusion - Transaction Isolation
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    Caching: Basics
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    Caching: Global vs. Local Cache
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    Global Cache Internals
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    Write Policies: Write Back Policy
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    Write Through Policy
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    Write Around Policy
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    Replacement Policies: LRU, LFU and Segmented LRU
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    Breakdown: The physical layer
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    Breakdown: The Routing Layer
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    Breakdown: The behavioral layer
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    Connecting to the internet: ISPs, DNS and everything in between
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    Internal routing: MAC addresses and NAT
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    HTTP, WebSockets, TCP and UDP
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    Communication Standards: REST, GraphQL and GRPC
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    Head of line blocking
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    Video transmission: WebRTC and HTTP-DASH
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    Primary Replica Architectures
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    WAL and Change Data Capture
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    Write Amplification and Split Brain
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    Database Migrations
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    Migrating the Database
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    Migration Across Regions
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    The Oracle and the Timer Wheel
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    Partitioning and Real-life Optimisations
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    Security aspects in distributed systems
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    Token Based Auth
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    SSO and OAuth
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    Access Control Lists and Rule Engines
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    Attack Vectors - Hackers, Developers and Code
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    How videos are protected inside CDNs
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    Design an algorithm for an Audio Search Engine
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    Introduction to design tradeoffs
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    Pull vs. Push Architectures
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    Memory vs. Latency
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    Throughput vs. Latency
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    Consistency vs. Availability
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    Latency vs. Accuracy
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    SQL vs. NoSQL databases
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    Relations Between Tradeoffs
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    The Problem of Distributed Consensus
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    Basic Algorithm
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    Improving the algorithm
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    Termination Conditions
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    Practical Considerations
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    Introduction to Observability
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    Logging - Best Practices
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    Monitoring Metrics
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    Anomaly Detection: Holt-Winters Algorithm
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    Root Cause Analysis
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    Conclusion to Observability
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    Scope and Requirement setting
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    Chapter #1: Service Registration and Proxies
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    Chapter #2: Authentication & Global Caching
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    Chapter #3: API contracts & Versioning
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    Chapter #4: Sending, Tagging & Searching Emails
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    Chapter #5: Contacts & Groups
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    Requirements of a chess website
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    Handling connections at scale
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    Consistent Hashing vs. Sharding
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    Connection related thundering herds
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    Request Batching and Conclusion
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    Live Streaming Requirement Breakdown
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    Video Ingestion and Transformation
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    Transferring processed videos to end users
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    Virtual Advertising for live sports events
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    Google Docs Requirements
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    Document Schema
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    Storing Documents
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    Version History
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    Avoiding Thundering Herds in Crons
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    Compression and Caching
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    Concurrent Writes with Locks
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    Operational Transform Overview
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    Permission Management
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    Requirements of a cab aggregator
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    Static Pricing of Rides
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    Ride Matching
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    Calculating Estimated Time of Arrival
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    Matching Drivers with Live Rides
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    Requirements of a Map application
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    Routing Challenges in Maps
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    Partitioning Algorithm: Splitting the graph into regions
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    Finding the shortest path - A* search
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    GeoHash and other proximity filters
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    Detecting traffic jams and broadcasting updates
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    Calculating an accurate and efficient estimated time of arrival
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    Calling App Design
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    Concept #1: Breaking calls into dialogs
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    Concept #2: The state machine
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    Concept #3: Charging Users
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    Concept #4: Consistent Hashing for caching call state
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    Converting data sources to a lake
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    The Map Reduce Architecture
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    Fault tolerance and engineering optimizations
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    Real time analytics
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    Ranking restaurants in real time and batch
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    Introduction to Low Level Design Series
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    The need for good coding practices
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    Setting Requirements and Objects
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    API and Package Structuring
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    Parent vs. Base class functions
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    Setting the main method
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    Debugging the code
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    Defining responsibilities of AI and Game classes
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    Unit Tests
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    Benefits of Single Responsibility Principle
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    Looking for a Smart AI
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    The need for stateless move exploration
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    Prototype Design Pattern
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    DRY: Dont Repeat Yourself
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    Iterator Design Pattern
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    DRY: Extracting Common Pieces
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    New feature request: Find Forks!
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    Building a Rule Engine
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    Builder Design Pattern
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    Summary: Open-Closed Principle
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    New feature request: Timers!
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    Encapsulating responsibilities in objects
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    Extracting Nested Objects
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    Having Multiple AI personalities
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    Singleton and Null Object Design Pattern
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    Chain of Responsibility Pattern
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    Interface Segregation Principle
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    Dependency Inversion Principle
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    New feature request: Undo Moves with Momento!
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    Proxy and Flyweight Design Pattern
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    The Labyrinth: Five Level Deep For-Loops!
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    State and Strategy Design Pattern
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    Writing Tests for Timed Games
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    Factory Design Pattern
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    Unit Tests and Object Pools
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    Setting Timed Test Cases
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    Fixing bugs in Game Logic and Factories
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    Strategy Design Pattern: Implementation and Benefits
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    New Feature: Email Notifications
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    Inheritance vs. Composition
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    The Publisher Subscriber Model
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    Problem Statement
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    Defining objects states and behaviors
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    Simplified Balances algorithm
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    APIs and coding requirements
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    Low Level Design
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    Coding: Building the service skeleton and defining objects
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    Coding: Algorithm
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    Coding: Test cases
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    Conclusion and Tips
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    #1: Caching: Engineering requirements
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    #2: Read your own writes
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    #3: Defining the core requirements
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    #4: Asynchronous processing: Keeping threads available
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    #5: View Consistency through thread assignment
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    Code #1: Code skeleton for 'Get' and 'Set'
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    Code #2: Setting up fast evictions
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    Code #3: Thread Assignment and updating GET + SET
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    Code #4: Hot loading and Request Collapsing
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    What is an event bus?
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    Breaking down engineering requirements
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    The mechanics of the bus
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    Why use threads?
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    Code Skeleton and using an extensible Retry Algorithm
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    The Keyed Executor
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    Pull and Push Subscribers
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    Defining the data structures in the bus
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    Wrapper Classes
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    Coding the tests
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    Conclusion
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    What will you learn
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    Rate Limiter Overview
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    Implementation Details
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    API Breakdown
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    Models, Controllers, Packages and ThreadPools
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    Reading and Writing Data
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    RateLimiter Client Setup
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    Sliding Window Algorithm Setup
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    Dependency Inversion
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    Sliding Window with Backpressure
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    Clearing Stale Entries in Sliding Window
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    January 2022: Datastores and their Tradeoffs
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    March 2022: Threads and Request Collapsing
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    April 2022: Chess Low Level Design
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    May 2022: Message Queues
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    June - Design a Payment System
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    July - Caching, Paxos and Zookeeper
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    Data Corruption and Alerts Monitoring
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    Caching: Doubts and Clarifications
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    August - Database Doubts
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    Design a subscription manager
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    Rule Engines
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    October - Kafka Internals
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    October 2022 - Implementing a File System
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    Pessimistic and Optimistic Locking
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    Producers and Consumers: November Meet
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    IRCTC Algorithm: December
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    Google Docs and Chess Design Queries
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    Jan 2023: DNS, CDNs, and everything in between
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    Jan 2023: API design and other discussions
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    Feb 2023: Permission Management System
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    March 2023: Eventual Consistency Levels
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    March 2023: Fetch top K hits in a distributed system
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    April 2023: Distributed Consensus and Load Balancing
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    April 2023: Graph Databases with Facebook TAO
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    May 2023: The SideCar Pattern
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    May 2023: Permission Management
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    June 2023: Clients, Comments and APIs
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    July 2023: Design an Event Handler
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    July 2023: Highly Scalable Concurrent Booking Systems
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    August 2023 - Google Calendar Low-Level Design
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    August 2023 - Designing IRCTC
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    September - Design Judge Launch
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    September - Tech in a startup
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    October - Live Watch Party Design
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    November - Memcached Reading
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    November - Memcached Revision
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    December: Memcached Paper Reading - 2
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    Monoliths vs Microservices
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    Horizontal vs Vertical Scaling
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    Load Balancing
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    An introduction to distributed systems
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    Single Point of Failure
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    Sharding
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    Service discovery and Heartbeats
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    Capacity Planning and Estimation: How much data does YouTube store daily?
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    Content Delivery Networks
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    API Design Goals
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    API Design in Practice
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    The Message Queue: Problem Statement
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    Asynchronous processing: benefits
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    Publisher Subscriber Models
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    Event Driven Architectures
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    Event Driven Architectures - Advantages
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    Event Driven Architectures - Disadvantages
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    Distributed data consistency
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    Data Consistency across Continents
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    Leader-follower architectures
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    Tradeoffs - 2 phase commit protocol
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    Difference between SQL and NoSQL
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    Cassandra Internals
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    Quorom
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    Write Heavy DB Design
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    Write Heavy DB Design - Merging Sorted String Tables
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    Write Heavy DB Design - Query optimisations
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    Location Representation
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    Data Structure - Quad Tree
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    Range Queries and Hilbert Curve
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    Motivation
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    Infrastructure Requirements
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    Practical considerations
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    Containers: A friendly Introduction
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    Containers: Usecases
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    System Requirements
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    One to one messaging
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    Last Seen Timestamps
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    Group Messaging
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    Requirements
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    Image Storage: Files vs. Database BLOB
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    Profile Creation and Authentication
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    One to One chat messaging
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    Matching right-swiped users
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    Serving recommendations to users
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    Requirements
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    Designing the Data Schema
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    Following Users
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    User Feed Service
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    Scaling the Instagram news feed
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    Anomaly Detection
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    Video Processing
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    ISP Synergy
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    System Design Tips
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    Dos and Don'ts
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    Online Judge