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System Design Interview Volume 1 references

Ch 1

Scale From Zero To Millions Of Users

14 references
  1. [1]
    Hypertext Transfer Protocol
    en.wikipedia.org
  2. [2]
    Should you go Beyond Relational Databases?
    blog.teamtreehouse.com
  3. [3]
    Replication
    en.wikipedia.org
  4. [4]
    Multi-master replication
    en.wikipedia.org
  5. [5]
    NDB Cluster Replication: Multi-Master and Circular Replication
    dev.mysql.com
  6. [6]
    Caching Strategies and How to Choose the Right One
    codeahoy.com
  7. [7]
    Scaling Memcache at Facebook
    usenix.orgPDF
  8. [8]
    Single point of failure
    en.wikipedia.org
  9. [9]
    Amazon CloudFront Dynamic Content Delivery
    aws.amazon.com
  10. [10]
    Configure Sticky Sessions for Your Classic Load Balancer
    docs.aws.amazon.com
  11. [11]
    Active-Active for Multi-Regional Resiliency
    netflixtechblog.com
  12. [12]
    Amazon EC2 High Memory Instances
    aws.amazon.com
  13. [13]
    What it takes to run Stack Overflow
    nickcraver.com
  14. [14]
    What The Heck Are You Actually Using NoSQL For
    highscalability.com
Ch 2

Back-of-the-envelope Estimation

6 references
  1. [1]
    J. Dean: Google Pro Tip: Use Back-Of-The-Envelope Calculations To Choose The Best Design
    highscalability.com
  2. [2]
    System design primer
    github.com
  3. [3]
    Latency Numbers Every Programmer Should Know
    colin-scott.github.io
  4. [4]
    Amazon Compute Service Level Agreement
    aws.amazon.com
  5. [5]
    Compute Engine Service Level Agreement (SLA)
    cloud.google.com
  6. [6]
    SLA summary for Azure services
    azure.microsoft.com
Ch 4

Design A Rate Limiter

16 references
  1. [1]
    Rate-limiting strategies and techniques
    cloud.google.com
  2. [2]
    Twitter rate limits
    developer.twitter.com
  3. [3]
    Google Docs usage limits
    developers.google.com
  4. [4]
    IBM microservices
    ibm.com
  5. [5]
    Throttle API requests for better throughput
    docs.aws.amazon.com
  6. [6]
    Stripe rate limiters
    stripe.com
  7. [7]
    Shopify REST Admin API rate limits
    help.shopify.com
  8. [8]
    Better Rate Limiting With Redis Sorted Sets
    engineering.classdojo.com
  9. [9]
    System Design: Rate limiter and Data modelling
    medium.com
  10. [10]
    How we built rate limiting capable of scaling to millions of domains
    blog.cloudflare.com
  11. [11]
    Redis website
    redis.io
  12. [12]
    Lyft rate limiting
    github.com
  13. [13]
    Scaling your API with rate limiters
    gist.github.com
  14. [14]
    What is edge computing
    cloudflare.com
  15. [15]
    Rate Limit Requests with Iptables
    blog.programster.org
  16. [16]
    OSI model
    en.wikipedia.org
Ch 5

Design Consistent Hashing

7 references
  1. [1]
    Consistent hashing (Wikipedia)
    en.wikipedia.org
  2. [2]
    Consistent Hashing (Tom White)
    tom-e-white.com
  3. [3]
    Dynamo: Amazon's Highly Available Key-value Store
    allthingsdistributed.comPDF
  4. [4]
    Cassandra: A Decentralized Structured Storage System
    cs.cornell.eduPDF
  5. [5]
    How Discord Scaled Elixir to 5,000,000 Concurrent Users
    blog.discord.com
  6. [6]
    CS168 The Modern Algorithmic Toolbox, Lecture #1: Introduction and Consistent Hashing
    theory.stanford.eduPDF
  7. [7]
    Maglev: A Fast and Reliable Software Network Load Balancer
    static.googleusercontent.comPDF
Ch 6

Design A Key-value Store

10 references
  1. [1]
    Amazon DynamoDB
    aws.amazon.com
  2. [2]
    memcached
    memcached.org
  3. [3]
    Redis
    redis.io
  4. [4]
    Dynamo: Amazon's Highly Available Key-value Store
    allthingsdistributed.comPDF
  5. [5]
    Cassandra
    cassandra.apache.org
  6. [6]
    Bigtable: A Distributed Storage System for Structured Data
    static.googleusercontent.comPDF
  7. [7]
    Merkle tree
    en.wikipedia.org
  8. [8]
    Cassandra architecture
    cassandra.apache.org
  9. [9]
    SSTable and Log Structured Storage: LevelDB
    igvita.com
  10. [10]
    Bloom filter
    en.wikipedia.org
Ch 7

Design A Unique ID Generator In Distributed Systems

4 references
  1. [1]
    Universally unique identifier
    en.wikipedia.org
  2. [2]
    Ticket Servers: Distributed Unique Primary Keys on the Cheap
    code.flickr.net
  3. [3]
    Announcing Snowflake
    blog.twitter.com
  4. [4]
    Network Time Protocol
    en.wikipedia.org
Ch 8

Design A URL Shortener

2 references
  1. [1]
    A RESTful Tutorial
    restapitutorial.com
  2. [2]
    Bloom filter
    en.wikipedia.org
Ch 9

Design A Web Crawler

14 references
  1. [1]
    US Library of Congress web archives
    loc.gov
  2. [2]
    EU Web Archive
    data.europa.eu
  3. [3]
    Digimarc
    digimarc.com
  4. [4]
    Mercator: A scalable, extensible web crawler
    courses.cs.washington.eduPDF
  5. [5]
    Web Crawling (Olston & Najork)
    infolab.stanford.eduPDF
  6. [6]
    29% Of Sites Face Duplicate Content Issues
    tinyurl.com
  7. [7]
    Rabin M.O., et al. Fingerprinting by random polynomials. Center for Research in Computing Techn., Aiken Computation Laboratory, Univ. (1981)
    print citation · no link
  8. [8]
    B. H. Bloom. Space/time trade-offs in hash coding with allowable errors. Communications of the ACM, vol. 13, no. 7, pp. 422–426, 1970
    print citation · no link
  9. [9]
    Donald J. Patterson, Web Crawling
    ics.uci.eduPDF
  10. [10]
    L. Page, S. Brin, R. Motwani, T. Winograd. The PageRank citation ranking: Bringing order to the web. Technical Report, Stanford University, 1998
    print citation · no link
  11. [11]
    Burton Bloom. Space/time trade-offs in hash coding with allowable errors. Communications of the ACM, 13(7), pp. 422–426, July 1970
    print citation · no link
  12. [12]
    Google Dynamic Rendering
    developers.google.com
  13. [13]
    T. Urvoy, T. Lavergne, P. Filoche. Tracking web spam with hidden style similarity. 2nd Intl. Workshop on Adversarial Information Retrieval on the Web, 2006
    print citation · no link
  14. [14]
    IRLbot: Scaling to 6 billion pages and beyond
    irl.cs.tamu.eduPDF
Ch 10

Design A Notification System

7 references
  1. [1]
    Twilio SMS
    twilio.com
  2. [2]
    Nexmo SMS
    nexmo.com
  3. [3]
    SendGrid
    sendgrid.com
  4. [4]
    Mailchimp
    mailchimp.com
  5. [5]
    You Cannot Have Exactly-Once Delivery
    bravenewgeek.com
  6. [6]
    App Keys & Secrets: Security
    bit.ly
  7. [7]
    RabbitMQ
    bit.ly
Ch 11

Design A News Feed System

2 references
  1. [1]
    How News Feed Works
    facebook.com
  2. [2]
    Friend of Friend recommendations: Neo4j and SQL Server
    bit.ly
Ch 12

Design A Chat System

10 references
  1. [1]
    Erlang at Facebook
    erlang-factory.comPDF
  2. [2]
    Messenger and WhatsApp process 60 billion messages a day
    theverge.com
  3. [3]
    Long tail
    en.wikipedia.org
  4. [4]
    The Underlying Technology of Messages
    facebook.com
  5. [5]
    How Discord Stores Billions of Messages
    blog.discordapp.com
  6. [6]
    Announcing Snowflake
    blog.twitter.com
  7. [7]
    Apache ZooKeeper
    zookeeper.apache.org
  8. [8]
    From nothing: the evolution of WeChat background system (in Chinese)
    infoq.cn
  9. [9]
    End-to-end encryption (WhatsApp)
    faq.whatsapp.com
  10. [10]
    Flannel: An Application-Level Edge Cache to Make Slack Scale
    slack.engineering
Ch 13

Design A Search Autocomplete System

9 references
  1. [1]
    The Life of a Typeahead Query
    facebook.com
  2. [2]
    How We Built Prefixy: A Scalable Prefix Search Service for Powering Autocomplete
    medium.com
  3. [3]
    Prefix Hash Tree: An Indexing Data Structure over Distributed Hash Tables
    people.eecs.berkeley.eduPDF
  4. [4]
    MongoDB (Wikipedia)
    en.wikipedia.org
  5. [5]
    Unicode frequently asked questions
    unicode.org
  6. [6]
    Apache Hadoop
    hadoop.apache.org
  7. [7]
    Spark Streaming
    spark.apache.org
  8. [8]
    Apache Storm
    storm.apache.org
  9. [9]
    Apache Kafka
    kafka.apache.org
Ch 14

Design YouTube

13 references
  1. [1]
    YouTube by the numbers
    omnicoreagency.com
  2. [2]
    2019 YouTube Demographics
    blog.hubspot.com
  3. [3]
    CloudFront Pricing
    aws.amazon.com
  4. [4]
    Netflix on AWS
    aws.amazon.com
  5. [5]
    Akamai homepage
    akamai.com
  6. [6]
    Binary large object
    en.wikipedia.org
  7. [7]
    Here's What You Need to Know About Streaming Protocols
    dacast.com
  8. [8]
    SVE: Distributed Video Processing at Facebook Scale
    cs.princeton.eduPDF
  9. [9]
    Weibo video processing architecture (in Chinese)
    upyun.com
  10. [10]
    Delegate access with a shared access signature
    docs.microsoft.com
  11. [11]
    YouTube scalability talk by early YouTube employee
    youtube.com
  12. [12]
    Understanding the characteristics of internet short video sharing: A YouTube-based measurement study
    arxiv.orgPDF
  13. [13]
    Content Popularity for Open Connect
    netflixtechblog.com
Ch 15

Design Google Drive

11 references
  1. [1]
    Google Drive
    google.com
  2. [2]
    Upload file data
    developers.google.com
  3. [3]
    Amazon S3
    aws.amazon.com
  4. [4]
    Differential Synchronization
    neil.fraser.name
  5. [5]
    Differential Synchronization (YouTube talk)
    youtube.com
  6. [6]
    How We've Scaled Dropbox
    youtu.be
  7. [7]
    The rsync algorithm
    andrew.cmu.eduPDF
  8. [8]
    librsync
    github.com
  9. [9]
    ACID
    en.wikipedia.org
  10. [10]
    Dropbox security white paper
    dropbox.comPDF
  11. [11]
    Amazon S3 Glacier
    aws.amazon.com
Extra

Real-world Systems

32 references
  1. [1]
    Facebook Timeline: Brought To You By The Power Of Denormalization
    goo.gl
  2. [2]
    Scale at Facebook
    infoq.com
  3. [3]
    Building Timeline: Scaling up to hold your life story
    goo.gl
  4. [4]
    Erlang at Facebook (Facebook chat)
    goo.gl
  5. [5]
    Finding a needle in Haystack: Facebook's photo storage
    goo.gl
  6. [6]
    Serving Facebook Multifeed: Efficiency, performance gains through redesign
    goo.gl
  7. [7]
    Scaling Memcache at Facebook
    goo.gl
  8. [8]
    TAO: Facebook's Distributed Data Store for the Social Graph
    goo.gl
  9. [9]
    Amazon Architecture
    goo.gl
  10. [10]
    Dynamo: Amazon's Highly Available Key-value Store
    goo.gl
  11. [11]
    A 360 Degree View Of The Entire Netflix Stack
    goo.gl
  12. [12]
    It's All A/Bout Testing: The Netflix Experimentation Platform
    goo.gl
  13. [13]
    Netflix Recommendations: Beyond the 5 stars (Part 1)
    goo.gl
  14. [14]
    Netflix Recommendations: Beyond the 5 stars (Part 2)
    goo.gl
  15. [15]
    Google Architecture
    goo.gl
  16. [16]
    The Google File System
    goo.gl
  17. [17]
    Differential Synchronization (Google Docs)
    goo.gl
  18. [18]
    YouTube Architecture
    goo.gl
  19. [19]
    Seattle Conference on Scalability: YouTube Scalability
    goo.gl
  20. [20]
    Bigtable: A Distributed Storage System for Structured Data
    goo.gl
  21. [21]
    Instagram Architecture: 14 Million Users, Terabytes Of Photos
    goo.gl
  22. [22]
    The Architecture Twitter Uses To Deal With 150M Active Users
    goo.gl
  23. [23]
    Scaling Twitter: Making Twitter 10000 Percent Faster
    goo.gl
  24. [24]
    Announcing Snowflake
    goo.gl
  25. [25]
    Timelines at Scale
    goo.gl
  26. [26]
    How Uber Scales Their Real-Time Market Platform
    goo.gl
  27. [27]
    Scaling Pinterest
    goo.gl
  28. [28]
    Pinterest Architecture Update
    goo.gl
  29. [29]
    A Brief History of Scaling LinkedIn
    goo.gl
  30. [30]
    Flickr Architecture
    goo.gl
  31. [31]
    How We've Scaled Dropbox
    goo.gl
  32. [32]
    The WhatsApp Architecture Facebook Bought For $19 Billion
    bit.ly
Extra

Company Engineering Blogs

37 blogs
AirbnbAmazonAsanaAtlassianBitTorrentClouderaDockerDropboxeBayFacebookGitHubGoogleGrouponHigh ScalabilityInstacartInstagramLinkedInMixpanelNetflixNextdoorPayPalPinterestQuoraRedditSalesforceShopifySlackSoundCloudSpotifyStripeSystem design primerTwitterThumbtackUberYahooYelpZoom

System Design Interview Volume 2 references

Ch 1

Proximity Service

32 references
  1. [1]
    Yelp
    yelp.com
  2. [2]
    Map tiles by Stamen Design
    maps.stamen.com
  3. [3]
    OpenStreetMap
    openstreetmap.org
  4. [4]
    GDPR
    en.wikipedia.org
  5. [5]
    CCPA
    en.wikipedia.org
  6. [6]
    Pagination in the REST API
    developer.atlassian.com
  7. [7]
    Google Places API
    developers.google.com
  8. [8]
    Yelp business endpoints
    yelp.com
  9. [9]
    Regions and Zones
    docs.aws.amazon.com
  10. [10]
    Redis GEOHASH
    redis.io
  11. [11]
    PostGIS
    postgis.net
  12. [12]
    Cartesian tiers
    nsshutdown.com
  13. [13]
    R-tree
    en.wikipedia.org
  14. [14]
    Global map in a Geographic Coordinate Reference System
    bit.ly
  15. [15]
    Base32
    en.wikipedia.org
  16. [16]
    Geohash grid aggregation
    bit.ly
  17. [17]
    Geohash
    movable-type.co.uk
  18. [18]
    Quadtree
    en.wikipedia.org
  19. [19]
    How many leaves has a quadtree
    stackoverflow.com
  20. [20]
    Blue green deployment
    martinfowler.com
  21. [21]
    Improved Location Caching with Quadtrees
    engblog.yext.com
  22. [22]
    S2
    s2geometry.io
  23. [23]
    Hilbert curve
    en.wikipedia.org
  24. [24]
    Hilbert mapping
    bit-player.org
  25. [25]
    Geo-fence
    en.wikipedia.org
  26. [26]
    Region cover
    s2.sidewalklabs.com
  27. [27]
    Bing Maps
    bit.ly
  28. [28]
    MongoDB: Build a 2d index
    docs.mongodb.com
  29. [29]
    Geospatial Indexing: The 10 Million QPS Redis Architecture Powering Lyft
    youtube.com
  30. [30]
    Geo Shape Type
    elastic.co
  31. [31]
    Geosharded Recommendations Part 1: Sharding Approach
    medium.com
  32. [32]
    Get the last known location
    developer.android.com
Ch 2

Nearby Friends

10 references
  1. [1]
    Facebook Launches "Nearby Friends"
    techcrunch.com
  2. [2]
    Redis Pub/Sub
    redis.io
  3. [3]
    Redis Pub/Sub under the hood
    making.pusher.com
  4. [4]
    etcd
    etcd.io
  5. [5]
    ZooKeeper
    zookeeper.apache.org
  6. [6]
    Consistent hashing
    toptal.com
  7. [7]
    Erlang
    erlang.org
  8. [8]
    Elixir
    elixir-lang.org
  9. [9]
    A brief introduction to BEAM
    erlang.org
  10. [10]
    OTP
    erlang.org
Ch 3

Google Maps

16 references
  1. [1]
    Google Maps
    developers.google.com
  2. [2]
    Google Maps Platform
    cloud.google.com
  3. [3]
    Prototyping a Smoother Map
    medium.com
  4. [4]
    Mercator projection
    en.wikipedia.org
  5. [5]
    Peirce quincuncial projection
    en.wikipedia.org
  6. [6]
    Gall–Peters projection
    en.wikipedia.org
  7. [7]
    Winkel tripel projection
    en.wikipedia.org
  8. [8]
    Address geocoding
    en.wikipedia.org
  9. [9]
    Geohashing
    kousiknath.medium.com
  10. [10]
    HTTP keep-alive
    en.wikipedia.org
  11. [11]
    Directions API
    developers.google.com
  12. [12]
    Adjacency list
    en.wikipedia.org
  13. [13]
    CAP theorem
    en.wikipedia.org
  14. [14]
    Routing Tiles
    valhalla.readthedocs.io
  15. [15]
    ETAs with GNNs
    deepmind.com
  16. [16]
    Google Maps 101: How AI helps predict traffic and determine routes
    blog.google
Ch 4

Distributed Message Queue

20 references
  1. [1]
    Queue Length Limit
    rabbitmq.com
  2. [2]
    Apache ZooKeeper (Wikipedia)
    en.wikipedia.org
  3. [3]
    etcd
    etcd.io
  4. [4]
    MySQL
    mysql.com
  5. [5]
    Comparison of disk and memory performance
    deliveryimages.acm.org
  6. [6]
    Push vs. pull
    kafka.apache.org
  7. [7]
    Kafka 2.0 Documentation
    kafka.apache.org
  8. [8]
    Kafka No Longer Requires ZooKeeper
    towardsdatascience.com
  9. [9]
    Martin Kleppmann. Replication. In Designing Data-Intensive Applications, pages 151–197. O'Reilly Media, 2017
    print citation · no link
  10. [10]
    ISR in Apache Kafka
    cloudkarafka.com
  11. [11]
    KIP-392: Allow consumers to fetch from closest replica
    cwiki.apache.org
  12. [12]
    Hands-free Kafka Replication
    confluent.io
  13. [13]
    Kafka high watermark
    rongxinblog.wordpress.com
  14. [14]
    Kafka mirroring
    cwiki.apache.org
  15. [15]
    Message filtering in RocketMQ
    partners-intl.aliyun.com
  16. [16]
    Scheduled messages and delayed messages in Apache RocketMQ
    partners-intl.aliyun.com
  17. [17]
    Hashed and hierarchical timing wheels
    cs.columbia.eduPDF
  18. [18]
    Advanced Message Queuing Protocol
    en.wikipedia.org
  19. [19]
    Kafka protocol guide
    kafka.apache.org
  20. [20]
    HDFS
    hadoop.apache.org
Ch 5

Metrics Monitoring And Alerting System

30 references
  1. [1]
    Datadog
    datadoghq.com
  2. [2]
    Splunk
    splunk.com
  3. [3]
    PagerDuty
    pagerduty.com
  4. [4]
    Elastic stack
    elastic.co
  5. [5]
    Dapper, a Large-Scale Distributed Systems Tracing Infrastructure
    research.google
  6. [6]
    Distributed Systems Tracing with Zipkin
    blog.twitter.com
  7. [7]
    Prometheus
    prometheus.io
  8. [8]
    OpenTSDB: A Distributed, Scalable Monitoring System
    opentsdb.net
  9. [9]
    Data model (Prometheus)
    prometheus.io
  10. [10]
    MySQL
    mysql.com
  11. [11]
    Schema design for time-series data (Cloud Bigtable)
    cloud.google.com
  12. [12]
    TimeSeries Database for storing metrics at Twitter
    blog.twitter.com
  13. [13]
    Amazon Timestream
    aws.amazon.com
  14. [14]
    DB-Engines Ranking of time-series DBMS
    db-engines.com
  15. [15]
    InfluxDB
    influxdata.com
  16. [16]
    etcd
    etcd.io
  17. [17]
    Service Discovery with ZooKeeper
    cloud.spring.io
  18. [18]
    Amazon CloudWatch
    aws.amazon.com
  19. [19]
    Graphite
    graphiteapp.org
  20. [20]
    Push vs Pull
    bit.ly
  21. [21]
    Pull doesn't scale, or does it?
    prometheus.io
  22. [22]
    Monitoring Architecture
    developer.lightbend.com
  23. [23]
    Push vs Pull in Monitoring Systems
    giedrius.blog
  24. [24]
    Pushgateway
    github.com
  25. [25]
    Building Applications with Serverless Architectures
    aws.amazon.com
  26. [26]
    Gorilla: A Fast, Scalable, In-Memory Time Series Database
    vldb.orgPDF
  27. [27]
    Why We're Building Flux, a New Data Scripting and Query Language
    influxdata.com
  28. [28]
    InfluxDB storage engine
    docs.influxdata.com
  29. [29]
    YAML
    en.wikipedia.org
  30. [30]
    Grafana Demo
    play.grafana.org
Ch 6

Ad Click Event Aggregation

25 references
  1. [1]
    Clickthrough rate (CTR): Definition
    support.google.com
  2. [2]
    Conversion rate: Definition
    support.google.com
  3. [3]
    OLAP functions
    docs.oracle.com
  4. [4]
    Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting
    arxiv.orgPDF
  5. [5]
    LanguageManual ORC
    cwiki.apache.org
  6. [6]
    Parquet
    databricks.com
  7. [7]
    What is Avro
    ibm.com
  8. [8]
    Big Data
    datakwery.com
  9. [9]
    An Overview of End-to-End Exactly-Once Processing in Apache Flink
    flink.apache.org
  10. [10]
    DAG model
    en.wikipedia.org
  11. [11]
    Understand star schema and the importance for Power BI
    docs.microsoft.com
  12. [12]
    Martin Kleppmann. Designing Data-Intensive Applications. O'Reilly Media, 2017
    print citation · no link
  13. [13]
    Apache Flink
    flink.apache.org
  14. [14]
    Lambda architecture
    databricks.com
  15. [15]
    Kappa architecture
    hazelcast.com
  16. [16]
    Martin Kleppmann. Stream Processing. In Designing Data-Intensive Applications. O'Reilly Media, 2017
    print citation · no link
  17. [17]
    End-to-end Exactly-once Aggregation Over Ad Streams
    youtube.com
  18. [18]
    Ad traffic quality
    google.com
  19. [19]
    Understanding MapReduce in Hadoop
    section.io
  20. [20]
    Flink on Apache YARN
    ci.apache.org
  21. [21]
    How data is distributed across a cluster (using virtual nodes)
    docs.datastax.com
  22. [22]
    Flink performance tuning
    nightlies.apache.org
  23. [23]
    ClickHouse
    clickhouse.com
  24. [24]
    Druid
    druid.apache.org
  25. [25]
    Real-Time Exactly-Once Ad Event Processing with Apache Flink, Kafka, and Pinot
    eng.uber.com
Ch 7

Hotel Reservation System

13 references
  1. [1]
    What Are The Benefits of Microservices Architecture?
    appdynamics.com
  2. [2]
    Microservices
    en.wikipedia.org
  3. [3]
    gRPC
    grpc.io
  4. [4]
    Booking.com iOS app
    print citation · no link
  5. [5]
    Serializability
    en.wikipedia.org
  6. [6]
    Optimistic and pessimistic record locking
    ibm.co
  7. [7]
    Optimistic concurrency control
    en.wikipedia.org
  8. [8]
    Change data capture
    docs.oracle.com
  9. [9]
    Debezium
    debezium.io
  10. [10]
    Redis sink
    bit.ly
  11. [11]
    Monolithic Architecture
    microservices.io
  12. [12]
    Two-phase commit protocol
    en.wikipedia.org
  13. [13]
    Saga
    microservices.io
Ch 8

Distributed Email Service

30 references
  1. [1]
    Number of Active Gmail Users
    financesonline.com
  2. [2]
    Outlook
    en.wikipedia.org
  3. [3]
    How Many Emails Are Sent Per Day in 2021?
    review42.com
  4. [4]
    RFC 1939: Post Office Protocol, Version 3
    faqs.org
  5. [5]
    ActiveSync
    en.wikipedia.org
  6. [6]
    Email attachment
    en.wikipedia.org
  7. [7]
    MIME
    en.wikipedia.org
  8. [8]
    Threading
    en.wikipedia.org
  9. [9]
    IMAP LIST Extension for Special-Use Mailboxes
    datatracker.ietf.org
  10. [10]
    Apache James
    james.apache.org
  11. [11]
    A JSON Meta Application Protocol (JMAP) Subprotocol for WebSocket
    tools.ietf.org
  12. [12]
    Cassandra Limitations
    cwiki.apache.org
  13. [13]
    Inverted index
    en.wikipedia.org
  14. [14]
    Exponential backoff
    en.wikipedia.org
  15. [15]
    QQ Email System Optimization (in Chinese)
    slideshare.net
  16. [16]
    IOPS
    en.wikipedia.org
  17. [17]
    UUID and timeuuid types
    docs.datastax.com
  18. [18]
    Message threading
    jwz.org
  19. [19]
    Global spam volume
    statista.com
  20. [20]
    Warming up dedicated IP addresses
    docs.aws.amazon.com
  21. [21]
    2018 Data Breach Investigations Report
    enterprise.verizon.comPDF
  22. [22]
    Sender Policy Framework
    en.wikipedia.org
  23. [23]
    DomainKeys Identified Mail
    en.wikipedia.org
  24. [24]
    Domain-based Message Authentication, Reporting & Conformance
    dmarc.org
  25. [25]
    DB-Engines Ranking of Search Engines
    db-engines.com
  26. [26]
    Log-structured merge-tree
    en.wikipedia.org
  27. [27]
    Microsoft Exchange Conference 2014: Search in Exchange
    youtube.com
  28. [28]
    General Data Protection Regulation
    en.wikipedia.org
  29. [29]
    Lawful interception
    en.wikipedia.org
  30. [30]
    Email safety
    safety.google
Ch 9

S3-like Object Storage

29 references
  1. [1]
    Fibre Channel
    en.wikipedia.org
  2. [2]
    iSCSI
    en.wikipedia.org
  3. [3]
    Server Message Block
    en.wikipedia.org
  4. [4]
    Network File System
    en.wikipedia.org
  5. [5]
    Amazon S3 Strong Consistency
    aws.amazon.com
  6. [6]
    Serial Attached SCSI
    en.wikipedia.org
  7. [7]
    AWS CLI ls command
    docs.aws.amazon.com
  8. [8]
    Amazon S3 Service Level Agreement
    aws.amazon.com
  9. [9]
    Ambry: LinkedIn's Scalable Geo-Distributed Object Store
    assured-cloud-computing.illinois.eduPDF
  10. [10]
    inode
    en.wikipedia.org
  11. [11]
    Ceph's RADOS Gateway
    docs.ceph.com
  12. [12]
    gRPC
    grpc.io
  13. [13]
    Paxos
    en.wikipedia.org
  14. [14]
    Raft
    raft.github.io
  15. [15]
    Consistent hashing
    toptal.com
  16. [16]
    RocksDB
    github.com
  17. [17]
    SSTable
    igvita.com
  18. [18]
    B+ tree
    en.wikipedia.org
  19. [19]
    SQLite
    sqlite.org
  20. [20]
    Data Durability Calculation
    backblaze.com
  21. [21]
    Rack
    en.wikipedia.org
  22. [22]
    Erasure Coding
    en.wikipedia.org
  23. [23]
    Reed–Solomon error correction
    en.wikipedia.org
  24. [24]
    Erasure Coding Demystified
    youtube.com
  25. [25]
    Checksum
    en.wikipedia.org
  26. [26]
    MD5
    en.wikipedia.org
  27. [27]
    SHA-1
    en.wikipedia.org
  28. [28]
    HMAC
    en.wikipedia.org
  29. [29]
    TIMEUUID
    docs.datastax.com
Ch 10

Real-time Gaming Leaderboard

17 references
  1. [1]
    Man-in-the-middle attack
    en.wikipedia.org
  2. [2]
    Redis Sorted Set source code
    github.com
  3. [3]
    Geekbang
    static001.geekbang.org
  4. [4]
    Building real-time Leaderboard with Redis
    medium.com
  5. [5]
    Build a real-time gaming leaderboard with Amazon ElastiCache for Redis
    aws.amazon.com
  6. [6]
    How we created a real-time Leaderboard for a million Users
    levelup.gitconnected.com
  7. [7]
    Leaderboards
    redislabs.com
  8. [8]
    Lambda
    aws.amazon.com
  9. [9]
    Google Cloud Functions
    cloud.google.com
  10. [10]
    Azure Functions
    azure.microsoft.com
  11. [11]
    Info command
    redis.io
  12. [12]
    Why redis cluster only have 16384 slots
    stackoverflow.com
  13. [13]
    Cyclic redundancy check
    en.wikipedia.org
  14. [14]
    Choosing your node size
    docs.aws.amazon.com
  15. [15]
    How fast is Redis?
    redis.io
  16. [16]
    Using Global Secondary Indexes in DynamoDB
    docs.aws.amazon.com
  17. [17]
    Leaderboard & Write Sharding
    dynamodbguide.com
Ch 11

Payment System

30 references
  1. [1]
    Payment system
    en.wikipedia.org
  2. [2]
    AML/CFT
    en.wikipedia.org
  3. [3]
    Card scheme
    en.wikipedia.org
  4. [4]
    ISO 4217
    en.wikipedia.org
  5. [5]
    Stripe API Reference
    stripe.com
  6. [6]
    Double-entry bookkeeping
    en.wikipedia.org
  7. [7]
    Books, an immutable double-entry accounting database service
    developer.squareup.com
  8. [8]
    Payment Card Industry Data Security Standard
    en.wikipedia.org
  9. [9]
    Tipalti
    tipalti.com
  10. [10]
    Nonce
    en.wikipedia.org
  11. [11]
    Webhooks
    stripe.com
  12. [12]
    Customize your success page
    stripe.com
  13. [13]
    3D Secure
    en.wikipedia.org
  14. [14]
    Kafka Connect Deep Dive: Error Handling and Dead Letter Queues
    confluent.io
  15. [15]
    Reliable Processing in a Streaming Payment System
    youtube.com
  16. [16]
    Chain Services with Exactly-Once Guarantees
    confluent.io
  17. [17]
    Exponential backoff
    en.wikipedia.org
  18. [18]
    Idempotence
    en.wikipedia.org
  19. [19]
    Stripe idempotent requests
    stripe.com
  20. [20]
    Idempotency (PayPal)
    developer.paypal.com
  21. [21]
    Paxos
    en.wikipedia.org
  22. [22]
    Raft
    raft.github.io
  23. [23]
    YugabyteDB
    yugabyte.com
  24. [24]
    CockroachDB
    cockroachlabs.com
  25. [25]
    What is a DDoS attack
    cloudflare.com
  26. [26]
    How Payment Gateways Can Detect and Prevent Online Fraud
    chargebee.com
  27. [27]
    Advanced Technologies for Detecting and Preventing Fraud at Uber
    eng.uber.com
  28. [28]
    Re-Architecting Cash and Digital Wallet Payments for India with Uber Engineering
    eng.uber.com
  29. [29]
    Scaling Airbnb's Payment Platform
    medium.com
  30. [30]
    Payments Integration at Uber: A Case Study (Gergely Orosz)
    youtube.com
Ch 12

Digital Wallet

18 references
  1. [1]
    Transactional guarantees
    docs.oracle.com
  2. [2]
    TPC-E Top Price/Performance Results
    tpc.org
  3. [3]
    ISO 4217 currency codes
    en.wikipedia.org
  4. [4]
    Apache ZooKeeper
    zookeeper.apache.org
  5. [5]
    Martin Kleppmann. Designing Data-Intensive Applications. O'Reilly Media, 2017
    print citation · no link
  6. [6]
    X/Open XA
    en.wikipedia.org
  7. [7]
    Compensating transaction
    en.wikipedia.org
  8. [8]
    Sagas, Hector Garcia-Molina
    cs.cornell.eduPDF
  9. [9]
    Eric Evans. Domain-Driven Design: Tackling Complexity in the Heart of Software. Addison-Wesley Professional, 2003
    print citation · no link
  10. [10]
    Apache Kafka
    kafka.apache.org
  11. [11]
    CQRS
    martinfowler.com
  12. [12]
    Comparing Random and Sequential Access in Disk and Memory
    deliveryimages.acm.org
  13. [13]
    mmap
    man7.org
  14. [14]
    SQLite
    sqlite.org
  15. [15]
    RocksDB
    rocksdb.org
  16. [16]
    Apache Hadoop
    hadoop.apache.org
  17. [17]
    Raft
    raft.github.io
  18. [18]
    Reverse proxy
    en.wikipedia.org
Ch 13

Stock Exchange

30 references
  1. [1]
    LMAX exchange, famous for its open-source Disruptor
    lmax.com
  2. [2]
    IEX attracts investors by "playing fair", also the "Flash Boys Exchange"
    en.wikipedia.org
  3. [3]
    NYSE matched volume
    nyse.com
  4. [4]
    HKEX daily trading volume
    hkex.com.hk
  5. [5]
    All of the World's Stock Exchanges by Size
    money.visualcapitalist.com
  6. [6]
    Denial-of-service attack
    en.wikipedia.org
  7. [7]
    Market impact
    en.wikipedia.org
  8. [8]
    FIX Trading
    fixtrading.org
  9. [9]
    Event Sourcing
    martinfowler.com
  10. [10]
    CME Co-Location and Data Center Services
    cmegroup.com
  11. [11]
    Epoch
    epoch101.com
  12. [12]
    Order book (Investopedia)
    investopedia.com
  13. [13]
    Order book (Wikipedia)
    en.wikipedia.org
  14. [14]
    How to Build a Fast Limit Order Book
    bit.ly
  15. [15]
    Developing with kdb+ and the q language
    code.kx.com
  16. [16]
    Latency Numbers Every Programmer Should Know
    gist.github.com
  17. [17]
    mmap
    en.wikipedia.org
  18. [18]
    Context switch
    bit.ly
  19. [19]
    Reliable User Datagram Protocol
    en.wikipedia.org
  20. [20]
    Aeron
    github.com
  21. [21]
    Chaos engineering
    en.wikipedia.org
  22. [22]
    Raft
    raft.github.io
  23. [23]
    Designing for Understandability: the Raft Consensus Algorithm
    raft.github.ioPDF
  24. [24]
    Supported Matching Algorithms
    bit.ly
  25. [25]
    Dark pool
    investopedia.com
  26. [26]
    HdrHistogram: A High Dynamic Range Histogram
    hdrhistogram.org
  27. [27]
    HotSpot (virtual machine)
    en.wikipedia.org
  28. [28]
    Cache line padding
    bit.ly
  29. [29]
    NACK-Oriented Reliable Multicast
    en.wikipedia.org
  30. [30]
    AWS Coinbase Case Study
    aws.amazon.com