目录

Principle

Scalability

Availability

Stability

Performance

Intelligence

Architecture

Interview

Organization

Talk

Book


Principle

  • Lessons from Giant-Scale Services - Eric Brewer, UC Berkeley & Google
  • Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google
  • How to Design a Good API & Why it Matters - Joshua Bloch, CMU & Google
  • On Efficiency, Reliability, Scaling - James Hamilton, VP at AWS
  • Things to Keep in Mind When Building a Platform for the Enterprise - Heidi Williams, VP Platform at Box
  • Principles of Chaos Engineering
  • Finding the Order in Chaos
  • The Twelve-Factor App
  • Clean Architecture
  • High Cohesion and Low Coupling
  • Monoliths and Microservices
  • CAP Theorem and Trade-offs
  • CP Databases and AP Databases
  • Stateless vs Stateful Scalability
  • Scale Up vs Scale Out
  • Scale Up vs Scale Out: Hidden Costs
  • ACID and BASE
  • Blocking/Non-Blocking and Sync/Async
  • Performance and Scalability of Databases
  • Database Isolation Levels and Effects on Performance and Scalability
  • The Probability of Data Loss in Large Clusters
  • Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence
  • SQL vs NoSQL
  • SQL vs NoSQL - Lesson Learned at Salesforce
  • NoSQL Databases: Survey and Decision Guidance
  • How Sharding Works
  • Consistent Hashing
  • Consistent Hashing: Algorithmic Tradeoffs
  • Don’t be tricked by the Hashing Trick
  • Uniform Consistent Hashing at Netflix
  • Eventually Consistent - Werner Vogels, CTO at Amazon
  • Cache is King
  • Anti-Caching
  • Understand Latency
  • Latency Numbers Every Programmer Should Know
  • The Calculus of Service Availability
  • Architecture Issues When Scaling Web Applications: Bottlenecks, Database, CPU, IO
  • Common Bottlenecks
  • Life Beyond Distributed Transactions
  • Relying on Software to Redirect Traffic Reliably at Various Layers
  • Breaking Things on Purpose
  • Avoid Over Engineering
  • Scalability Worst Practices
  • Use Solid Technologies - Don’t Re-invent the Wheel - Keep It Simple!
  • Simplicity by Distributing Complexity
  • Why Over-Reusing is Bad
  • Performance is a Feature
  • Make Performance Part of Your Workflow
  • The Benefits of Server Side Rendering over Client Side Rendering
  • Automate and Abstract: Lessons at Facebook
  • AWS Do's and Don'ts
  • (UI) Design Doesn’t Scale - Stanley Wood, Design Director at Spotify
  • Linux Performance
  • Building Fast and Resilient Web Applications - Ilya Grigorik
  • Accept Partial Failures, Minimize Service Loss
  • Design for Resiliency
  • Design for Self-healing
  • Design for Scaling Out
  • Design for Evolution
  • Learn from Mistakes

Scalability

  • Microservices and Orchestration

    • Domain-Oriented Microservice Architecture at Uber
    • Container (8 parts) at Riot Games
    • Containerization at Pinterest
    • Evolution of Container Usage at Netflix
    • Dockerizing MySQL at Uber
    • Testing of Microservices at Spotify
    • Docker in Production at Treehouse
    • Microservice at SoundCloud
    • Operate Kubernetes Reliably at Stripe
    • Cross-Cluster Traffic Mirroring with Istio at Trivago
    • Agrarian-Scale Kubernetes (3 parts) at New York Times
    • Nanoservices at BBC
    • PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg
    • Conductor: Microservices Orchestrator at Netflix
    • Docker Containers that Power Over 100.000 Online Shops at Shopify
    • Microservice Architecture at Medium
    • From bare-metal to Kubernetes at Betabrand
    • Kubernetes at Tinder
    • Kubernetes at Quora
    • Kubernetes Platform at Pinterest
    • Microservices at Nubank
    • GRIT: Protocol for Distributed Transactions across Microservices at eBay
    • Rubix: Kubernetes at Palantir
  • Distributed Caching
    • EVCache: Distributed In-memory Caching at Netflix
    • EVCache Cache Warmer Infrastructure at Netflix
    • Memsniff: Robust Memcache Traffic Analyzer at Box
    • Caching with Consistent Hashing and Cache Smearing at Etsy
    • Analysis of Photo Caching at Facebook
    • Cache Efficiency Exercise at Facebook
    • tCache: Scalable Data-aware Java Caching at Trivago
    • Pycache: In-process Caching at Quora
    • Reduce Memcached Memory Usage by 50% at Trivago
    • Caching Internal Service Calls at Yelp
    • Estimating the Cache Efficiency using Big Data at Allegro
    • Distributed Cache at Zalando
    • Application Data Caching from RAM to SSD at NetFlix
    • Tradeoffs of Replicated Cache at Skyscanner
    • Avoiding Cache Stampede at DoorDash
    • Location Caching with Quadtrees at Yext
    • Video Metadata Caching at Vimeo
    • Scaling Redis at Twitter
    • Scaling Job Queue with Redis at Slack
    • Moving persistent data out of Redis at Github
    • Storing Hundreds of Millions of Simple Key-Value Pairs in Redis at Instagram
    • Redis at Trivago
    • Optimizing Redis Storage at Deliveroo
    • Memory Optimization in Redis at Wattpad
    • Redis Fleet at Heroku
    • Solving Remote Build Cache Misses (2 parts) at SoundCloud
    • Prefetch Caching of Items at eBay
    • HTTP Caching and CDN
      • Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga
      • Google AMP at Condé Nast
      • A/B Tests on Hosting Infrastructure (CDNs) at Deliveroo
      • HAProxy with Kubernetes for User-facing Traffic at SoundCloud
      • Bandaid: Service Proxy at Dropbox
      • CDN in LIVE's Encoder Layer at LINE
      • Service Workers at Slack
      • CDN Services at Spotify
  • Distributed Locking
    • Chubby: Lock Service for Loosely Coupled Distributed Systems at Google
    • Distributed Locking at Uber
    • Distributed Locks using Redis at GoSquared
    • ZooKeeper at Twitter
    • Eliminating Duplicate Queries using Distributed Locking at Chartio
  • Distributed Tracking, Tracing, and Measuring
    • Zipkin: Distributed Systems Tracing at Twitter
    • Improve Zipkin Traces using Kubernetes Pod Metadata at SoundCloud
    • Canopy: Scalable Distributed Tracing & Analysis at Facebook
    • Pintrace: Distributed Tracing at Pinterest
    • XCMetrics: All-in-One Tool for Tracking Xcode Build Metrics at Spotify
    • Real-time Distributed Tracing at LinkedIn
    • Tracking Service Infrastructure at Scale at Shopify
    • Distributed Tracing at HelloFresh
    • Analyzing Distributed Trace Data at Pinterest
    • Distributed Tracing at Uber
    • JVM Profiler: Tracing Distributed JVM Applications at Uber
    • Data Checking at Dropbox
    • Tracing Distributed Systems at Showmax
    • osquery Across the Enterprise at Palantir
    • StatsD at Etsy
    • StatsD at DoorDash
  • Distributed Scheduling
    • Distributed Task Scheduling (3 parts) at PagerDuty
    • Building Cron at Google
    • Distributed Cron Architecture at Quora
    • Chronos: A Replacement for Cron at Airbnb
    • Scheduler at Nextdoor
    • Peloton: Unified Resource Scheduler for Diverse Cluster Workloads at Uber
    • Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix
    • Airflow - Workflow Orchestration
      • Airflow at Airbnb
      • Airflow at Pandora
      • Airflow at Robinhood
      • Airflow at Lyft
      • Airflow at Drivy
      • Airflow at Grab
      • Airflow at Adobe
      • Auditing Airflow Job Runs at Walmart
      • MaaT: DAG-based Distributed Task Scheduler at Alibaba
      • boundary-layer: Declarative Airflow Workflows at Etsy
  • Distributed Monitoring and Alerting
    • Unicorn: Remediation System at eBay
    • M3: Metrics and Monitoring Platform at Uber
    • Athena: Automated Build Health Management System at Dropbox
    • Vortex: Monitoring Server Applications at Dropbox
    • Nuage: Cloud Management Service at LinkedIn
    • Telltale: Application Monitoring at Netflix
    • ThirdEye: Monitoring Platform at LinkedIn
    • Periskop: Exception Monitoring Service at SoundCloud
    • Securitybot: Distributed Alerting Bot at Dropbox
    • Monitoring System at Alibaba
    • Real User Monitoring at Dailymotion
    • Alerting Ecosystem at Uber
    • Alerting Framework at Airbnb
    • Alerting on Service-Level Objectives (SLOs) at SoundCloud
    • Job-based Forecasting Workflow for Observability Anomaly Detection at Uber
    • Monitoring and Alert System using Graphite and Cabot at HackerEarth
    • Observability (2 parts) at Twitter
    • Distributed Security Alerting at Slack
    • Real-Time News Alerting at Bloomberg
    • Data Pipeline Monitoring System at LinkedIn
    • Monitoring and Observability at Picnic
  • Distributed Security
    • Approach to Security at Scale at Dropbox
    • Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix
    • LISA: Distributed Firewall at LinkedIn
    • Secure Infrastructure To Store Bitcoin In The Cloud at Coinbase
    • BinaryAlert: Real-time Serverless Malware Detection at Airbnb
    • Scalable IAM Architecture to Secure Access to 100 AWS Accounts at Segment
    • OAuth Audit Toolbox at Indeed
    • Active Directory Password Blacklisting at Yelp
    • Syscall Auditing at Scale at Slack
    • Athenz: Fine-Grained, Role-Based Access Control at Yahoo
    • WebAuthn Support for Secure Sign In at Dropbox
    • Security Development Lifecycle at Slack
    • Unprivileged Container Builds at Kinvolk
    • Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix
    • Detecting Credential Compromise in AWS at Netflix
    • Scalable User Privacy at Spotify
    • AVA: Audit Web Applications at Indeed
    • TTL as a Service: Automatic Revocation of Stale Privileges at Yelp
    • Enterprise Key Management at Slack
    • Scalability and Authentication at Twitch
    • Edge Authentication and Token-Agnostic Identity Propagation at Netflix
    • Hardening Kubernetes Infrastructure with Cilium at Palantir
  • Distributed Messaging, Queuing, and Event Streaming
    • Cape: Event Stream Processing Framework at Dropbox
    • Brooklin: Distributed Service for Near Real-Time Data Streaming at LinkedIn
    • Samza: Stream Processing System for Latency Insighs at LinkedIn
    • Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo
    • EventHorizon: Tool for Watching Events Streaming at Etsy
    • Qmessage: Distributed, Asynchronous Task Queue at Quora
    • Cherami: Message Queue System for Transporting Async Tasks at Uber
    • Dynein: Distributed Delayed Job Queueing System at Airbnb
    • Messaging Service at Riot Games
    • Debugging Production with Event Logging at Zillow
    • Cross-platform In-app Messaging Orchestration Service at Netflix
    • Video Gatekeeper at Netflix
    • Scaling Push Messaging for Millions of Devices at Netflix
    • Delaying Asynchronous Message Processing with RabbitMQ at Indeed
    • Benchmarking Streaming Computation Engines at Yahoo
    • Improving Stream Data Quality With Protobuf Schema Validation at Deliveroo
    • Scaling Email Infrastructure at Medium
    • Event Stream Database at Nike
    • Event-Driven Messaging
      • Domain-Driven Design at Alibaba
      • Domain-Driven Design at Weebly
      • Domain-Driven Design at Moonpig
      • Scaling Event Sourcing for Netflix Downloads
      • Scaling Event-Sourcing at Jet.com
      • Event Sourcing (2 parts) at eBay
      • Event Sourcing at FREE NOW
      • Scalable content feed using Event Sourcing and CQRS patterns at Brainly
    • Pub-Sub Messaging
      • Pulsar: Pub-Sub Messaging at Scale at Yahoo
      • Wormhole: Pub-Sub System at Facebook
      • Pub-Sub in Chatting Architecture at LINE
      • Pub-Sub in Microservices at Netflix
    • Kafka - Message Broker
      • Kafka at LinkedIn
      • Kafka at Pinterest
      • Kafka at Trello
      • Kafka at Salesforce
      • Kafka at The New York Times
      • Kafka at Yelp
      • Kafka at Criteo
      • Kafka on Kubernetes at Shopify
      • Migrating Kafka's Zookeeper with No Downtime at Yelp
      • Reprocessing and Dead Letter Queues with Kafka at Uber
      • Chaperone: Audit Kafka End-to-End at Uber
      • Finding Kafka throughput limit in infrastructure at Dropbox
      • Cost Orchestration at Walmart
      • InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second at Hulu
    • Stream Data Deduplication
      • Exactly-once Semantics with Kafka
      • Real-time Deduping at Tapjoy
      • Deduplication at Segment
      • Deduplication at Mail.Ru
      • Petabyte Scale Data Deduplication at Mixpanel
  • Distributed Logging
    • Logging at LinkedIn
    • Scalable and Reliable Log Ingestion at Pinterest
    • High-performance Replicated Log Service at Twitter
    • Logging Service with Spark at CERN Accelerator
    • Logging and Aggregation at Quora
    • Collection and Analysis of Daemon Logs at Badoo
    • Log Parsing with Static Code Analysis at Palantir
    • Centralized Application Logging at eBay
    • Enrich VPC Flow Logs at Hyper Scale to provide Network Insight at Netflix
    • BookKeeper: Distributed Log Storage at Yahoo
    • LogDevice: Distributed Data Store for Logs at Facebook
    • LogFeeder: Log Collection System at Yelp
    • DBLog: Generic Change-Data-Capture Framework at Netflix
  • Distributed Searching
    • Search Architecture at Instagram
    • Search Architecture at eBay
    • Search Architecture at Box
    • Search Discovery Indexing Platform at Coupang
    • Universal Search System at Pinterest
    • Improving Search Engine Efficiency by over 25% at eBay
    • Indexing and Querying Telemetry Logs with Lucene at Palantir
    • Query Understanding at TripAdvisor
    • Search Federation Architecture at LinkedIn (2018)
    • Search at Slack
    • Search and Recommendations at DoorDash
    • Search Service at Twitter (2014)
    • Autocomplete Search (2 parts) at Traveloka
    • Data-Driven Autocorrection System at Canva
    • Adapting Search to Indian Phonetics at Flipkart
    • Nautilus: Search Engine at Dropbox
    • Galene: Search Architecture of LinkedIn
    • Manas: High Performing Customized Search System at Pinterest
    • Sherlock: Near Real Time Search Indexing at Flipkart
    • Nebula: Storage Platform to Build Search Backends at Airbnb
    • ELK (Elasticsearch, Logstash, Kibana) Stack
      • Predictions in Real Time with ELK at Uber
      • Building a scalable ELK stack at Envato
      • ELK at Robinhood
      • Scaling Elasticsearch Clusters at Uber
      • Elasticsearch Performance Tuning Practice at eBay
      • Improve Performance using Elasticsearch Plugins (2 parts) at Tinder
      • Elasticsearch at Kickstarter
      • Elasticsearch at Target
      • Log Parsing with Logstash and Google Protocol Buffers at Trivago
      • Fast Order Search using Data Pipeline and Elasticsearch at Yelp
      • Moving Core Business Search to Elasticsearch at Yelp
      • Sharding out Elasticsearch at Vinted
      • Self-Ranking Search with Elasticsearch at Wattpad
      • Vulcanizer: a library for operating Elasticsearch at Github
  • Distributed Storage
    • In-memory Storage

      • MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)
      • Optimizing Memcached Efficiency at Quora
      • Real-Time Data Warehouse with MemSQL on Cisco UCS
      • Moving to MemSQL at Tapjoy
      • MemSQL and Kinesis for Real-time Insights at Disney
      • MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora
    • Object Storage
      • Scaling HDFS at Uber
      • Reasons for Choosing S3 over HDFS at Databricks
      • File System on Amazon S3 at Quantcast
      • Image Recovery at Scale Using S3 Versioning at Trivago
      • Cloud Object Store at Yahoo
      • Ambry: Distributed Immutable Object Store at LinkedIn
      • Dynamometer: Scale Testing HDFS on Minimal Hardware with Maximum Fidelity at LinkedIn
      • Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb
      • MezzFS: Mounting Object Storage in Media Processing Platform at Netflix
      • Magic Pocket: In-house Multi-exabyte Storage System at Dropbox
  • Relational Databases
    • MySQL for Schema-less Data at FriendFeed
    • MySQL at Pinterest
    • PostgreSQL at Twitch
    • Scaling MySQL-based Financial Reporting System at Airbnb
    • Scaling MySQL at Wix
    • MaxScale (MySQL) Database Proxy at Airbnb
    • Switching from Postgres to MySQL at Uber
    • Handling Growth with Postgres at Instagram
    • Scaling the Analytics Database (Postgres) at TransferWise
    • Updating a 50 Terabyte PostgreSQL Database at Adyen
    • Scaling Database Access for 100s of Billions of Queries per Day at PayPal
    • Minimizing Read-Write MySQL Downtime at Yelp
    • Replication
      • MySQL Parallel Replication (4 parts) at Booking.com
      • Mitigating MySQL Replication Lag and Reducing Read Load at Github
      • Read Consistency with Database Replicas at Shopify
      • Black-Box Auditing: Verifying End-to-End Replication Integrity between MySQL and Redshift at Yelp
      • Partitioning Main MySQL Database at Airbnb
      • Herb: Multi-DC Replication Engine for Schemaless Datastore at Uber
    • Sharding
      • Sharding MySQL at Pinterest
      • Sharding MySQL at Twilio
      • Sharding MySQL at Square
      • Sharding MySQL at Quora
      • Sharding Layer of Schemaless Datastore at Uber
      • Sharding & IDs at Instagram
      • Solr: Improving Performance for Batch Indexing at Box
      • Geosharded Recommendations (3 parts) at Tinder
      • Scaling Services with Shard Manager at Facebook
    • Presto the Distributed SQL Query Engine
      • Presto at Pinterest
      • Presto Infrastructure at Lyft
      • Presto at Grab
      • Engineering Data Analytics with Presto and Apache Parquet at Uber
      • Data Wrangling at Slack
      • Presto in Big Data Platform on AWS at Netflix
      • Presto Auto Scaling at Eventbrite
  • NoSQL Databases
    • Key-Value Databases

      • DynamoDB at Nike
      • DynamoDB at Segment
      • DynamoDB at Mapbox
      • Manhattan: Distributed Key-Value Database at Twitter
      • Sherpa: Distributed NoSQL Key-Value Store at Yahoo
      • HaloDB: Embedded Key-Value Storage Engine at Yahoo
      • MPH: Fast and Compact Immutable Key-Value Stores at Indeed
      • Venice: Distributed Key-Value Database at Linkedin
    • Columnar Databases
      • Cassandra

        • Cassandra at Instagram
        • Storing Images in Cassandra at Walmart
        • Storing Messages with Cassandra at Discord
        • Scaling Cassandra Cluster at Walmart
        • Scaling Ad Analytics with Cassandra at Yelp
        • Scaling to 100+ Million Reads/Writes using Spark and Cassandra at Dream11
        • Moving Food Feed from Redis to Cassandra at Zomato
        • Benchmarking Cassandra Scalability on AWS at Netflix
        • Service Decomposition at Scale with Cassandra at Intuit QuickBooks
        • Cassandra for Keeping Counts In Sync at SoundCloud
        • cstar: Cassandra Orchestration Tool at Spotify
      • HBase
        • HBase at Salesforce
        • HBase in Facebook Messages
        • HBase in Imgur Notification
        • Improving HBase Backup Efficiency at Pinterest
        • HBase at Xiaomi
      • Redshift
        • Redshift at GIPHY
        • Redshift at Hudl
        • Redshift at Drivy
    • Document Databases
      • eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB
      • MongoDB at Baidu: Multi-Tenant Cluster Storing 200+ Billion Documents across 160 Shards
      • Migrating Mongo Data at Addepar
      • The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)
      • Migrating Mountains of Mongo Data at Addepar
      • Couchbase Ecosystem at LinkedIn
      • SimpleDB at Zendesk
      • Espresso: Distributed Document Store at LinkedIn
    • Graph Databases
      • FlockDB: Distributed Graph Database at Twitter
      • TAO: Distributed Data Store for the Social Graph at Facebook
      • Akutan: Distributed Knowledge Graph Store at eBay
  • Time Series Databases
    • Beringei: High-performance Time Series Storage Engine at Facebook
    • MetricsDB: TimeSeries Database for storing metrics at Twitter
    • Atlas: In-memory Dimensional Time Series Database at Netflix
    • Heroic: Time Series Database at Spotify
    • Roshi: Distributed Storage System for Time-Series Event at SoundCloud
    • Goku: Time Series Database at Pinterest
    • Scaling Time Series Data Storage (2 parts) at Netflix
    • Druid - Real-time Analytics Database
      • Druid at Airbnb
      • Druid at Walmart
      • Druid at eBay
      • Druid at Netflix
  • Distributed Repositories, Dependencies, and Configurations Management
    • DGit: Distributed Git at Github
    • Stemma: Distributed Git Server at Palantir
    • Configuration Management for Distributed Systems at Flickr
    • Git Repository at Microsoft
    • Solve Git Problem with Large Repositories at Microsoft
    • Single Repository at Google
    • Scaling Infrastructure and (Git) Workflow at Adyen
    • Dotfiles Distribution at Booking.com
    • Secret Detector: Preventing Secrets in Source Code at Yelp
    • Managing Software Dependency at Scale at LinkedIn
    • Merging Code in High-velocity Repositories at LinkedIn
    • Dynamic Configuration at Twitter
    • Dynamic Configuration at Mixpanel
    • Dynamic Configuration at GoDaddy
  • Scaling Continuous Integration and Continuous Delivery
    • Continuous Integration Stack at Facebook
    • Continuous Integration with Distributed Repositories and Dependencies at Netflix
    • Continuous Integration and Deployment with Bazel at Dropbox
    • Continuous Deployments at BuzzFeed
    • Screwdriver: Continuous Delivery Build System for Dynamic Infrastructure at Yahoo
    • CI/CD at Betterment
    • CI/CD at Brainly
    • Scaling iOS CI with Anka at Shopify
    • Scaling Jira Server at Yelp
    • Auto-scaling CI/CD cluster at Flexport

Availability

  • Resilience Engineering: Learning to Embrace Failure

    • Resilience Engineering with Project Waterbear at LinkedIn
    • Resiliency against Traffic Oversaturation at iHeartRadio
    • Resiliency in Distributed Systems at GO-JEK
    • Practical NoSQL Resilience Design Pattern for the Enterprise at eBay
    • Ensuring Resilience to Disaster at Quora
    • Site Resiliency at Expedia
    • Resiliency and Disaster Recovery with Kafka at eBay
    • Disaster Recovery for Multi-Region Kafka at Uber
  • Failover
    • The Evolution of Global Traffic Routing and Failover
    • Testing for Disaster Recovery Failover Testing
    • Designing a Microservices Architecture for Failure
    • ELB for Automatic Failover at GoSquared
    • Eliminate the Database for Higher Availability at American Express
    • Failover with Redis Sentinel at Vinted
    • High-availability SaaS Infrastructure at FreeAgent
    • MySQL High Availability at GitHub
    • MySQL High Availability at Eventbrite
    • Business Continuity & Disaster Recovery at Walmart
  • Load Balancing
    • Introduction to Modern Network Load Balancing and Proxying
    • Top Five (Load Balancing) Scalability Patterns
    • Load Balancing infrastructure to support more than 1.3 billion users at Facebook
    • DHCPLB: DHCP Load Balancer at Facebook
    • Katran: Scalable Network Load Balancer at Facebook
    • Deterministic Aperture: A Distributed, Load Balancing Algorithm at Twitter
    • Load Balancing with Eureka at Netflix
    • Edge Load Balancing at Netflix
    • Zuul 2: Cloud Gateway at Netflix
    • Load Balancing at Yelp
    • Load Balancing at Github
    • Consistent Hashing to Improve Load Balancing at Vimeo
    • UDP Load Balancing at 500 pixel
    • QALM: QoS Load Management Framework at Uber
    • Traffic Steering using Rum DNS at LinkedIn
    • Traffic Infrastructure (Edge Network) at Dropbox
    • Intelligent DNS based load balancing at Dropbox
    • Monitor DNS systems at Stripe
    • Multi-DNS Architecture (3 parts) at Monday
  • Rate Limiting
    • Rate Limiting for Scaling to Millions of Domains at Cloudflare
    • Cloud Bouncer: Distributed Rate Limiting at Yahoo
    • Scaling API with Rate Limiters at Stripe
    • Distributed Rate Limiting at Allegro
    • Ratequeue: Core Queueing-And-Rate-Limiting System at Twilio
    • Quotas Service at Grab
  • Autoscaling
    • Autoscaling Pinterest
    • Autoscaling Based on Request Queuing at Square
    • Autoscaling Jenkins at Trivago
    • Autoscaling Pub-Sub Consumers at Spotify
    • Autoscaling Bigtable Clusters based on CPU Load at Spotify
    • Autoscaling AWS Step Functions Activities at Yelp
    • Scryer: Predictive Auto Scaling Engine at Netflix
    • Bouncer: Simple AWS Auto Scaling Rollovers at Palantir
    • Clusterman: Autoscaling Mesos Clusters at Yelp
  • Availability in Globally Distributed Storage Systems at Google
  • NodeJS High Availability at Yahoo
  • Operations (11 parts) at LinkedIn
  • Monitoring Powers High Availability for LinkedIn Feed
  • Supporting Global Events at Facebook
  • High Availability at BlaBlaCar
  • High Availability at Netflix
  • High Availability Cloud Infrastructure at Twilio
  • Automating Datacenter Operations at Dropbox
  • Globalizing Player Accounts at Riot Games

Stability

  • Circuit Breaker

    • Circuit Breaking in Distributed Systems
    • Circuit Breakers for Distributed Services at LINE
    • Applying Circuit Breaker to Channel Gateway at LINE
    • Lessons in Resilience at SoundCloud
    • Circuit Breaker for Scaling Containers
    • Protector: Circuit Breaker for Time Series Databases at Trivago
    • Improved Production Stability with Circuit Breakers at Heroku
    • Circuit Breakers at Zendesk
    • Circuit Breakers at Traveloka
  • Timeouts
    • Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix
    • Enforce Timeout: A Reliability Methodology at DoorDash
    • Troubleshooting a Connection Timeout Issue with tcp_tw_recycle Enabled at eBay
  • Crash-safe Replication for MySQL at Booking.com
  • Bulkheads: Partition and Tolerate Failure in One Part
  • Steady State: Always Put Logs on Separate Disk
  • Throttling: Maintain a Steady Pace
  • Multi-Clustering: Improving Resiliency and Stability of a Large-scale Monolithic API Service at LinkedIn
  • Determinism (4 parts) in League of Legends Server

Performance

  • Performance Optimization on OS, Storage, Database, Network

    • Improving Performance with Background Data Prefetching at Instagram
    • Fixing Linux filesystem performance regressions at LinkedIn
    • Compression Techniques to Solve Network I/O Bottlenecks at eBay
    • Optimizing Web Servers for High Throughput and Low Latency at Dropbox
    • Linux Performance Analysis in 60.000 Milliseconds at Netflix
    • Live Downsizing Google Cloud Persistent Disks (PD-SSD) at Mixpanel
    • Decreasing RAM Usage by 40% Using jemalloc with Python & Celery at Zapier
    • Reducing Memory Footprint at Slack
    • Performance Improvements at Pinterest
    • Server Side Rendering at Wix
    • 30x Performance Improvements on MySQLStreamer at Yelp
    • Optimizing APIs at Netflix
    • Performance Monitoring with Riemann and Clojure at Walmart
    • Performance Tracking Dashboard for Live Games at Zynga
    • Optimizing CAL Report Hadoop MapReduce Jobs at eBay
    • Performance Tuning on Quartz Scheduler at eBay
    • Profiling C++ (Part 1: Optimization, Part 2: Measurement and Analysis) at Riot Games
    • Profiling React Server-Side Rendering at HomeAway
    • Hardware-Assisted Video Transcoding at Dailymotion
    • Cross Shard Transactions at 10 Million RPS at Dropbox
    • API Profiling at Pinterest
    • Pagelets Parallelize Server-side Processing at Yelp
    • Improving key expiration in Redis at Twitter
    • Ad Delivery Network Performance Optimization with Flame Graphs at MindGeek
    • Predictive CPU isolation of containers at Netflix
    • Cloud Jewels: Estimating kWh in the Cloud at Etsy
    • Unthrottled: Fixing CPU Limits in the Cloud (2 parts) at Indeed
  • Performance Optimization by Tuning Garbage Collection
    • Garbage Collection in Java Applications at LinkedIn
    • Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe
    • Garbage Collection in Redux Applications at SoundCloud
    • Garbage Collection in Go Application at Twitch
    • Analyzing V8 Garbage Collection Logs at Alibaba
    • Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram
    • Performance Impact of Removing Out of Band Garbage Collector (OOBGC) at Github
    • Debugging Java Memory Leaks at Allegro
    • Optimizing JVM at Alibaba
    • Tuning JVM Memory for Large-scale Services at Uber
    • Solr Performance Tuning at Walmart
    • Memory Tuning a High Throughput Microservice at Flipkart
  • Performance Optimization on Image, Video, Page Load
    • Optimizing 360 Photos at Scale at Facebook
    • Reducing Image File Size in the Photos Infrastructure at Etsy
    • Improving GIF Performance at Pinterest
    • Optimizing Video Playback Performance at Pinterest
    • Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix
    • Adaptive Video Streaming at YouTube
    • Reducing Video Loading Time at Dailymotion
    • Improving Homepage Performance at Zillow
    • The Process of Optimizing for Client Performance at Expedia
    • Web Performance at BBC
  • Performance Optimization by Brotli Compression
    • Boosting Site Speed Using Brotli Compression at LinkedIn
    • Brotli at Booking.com
    • Brotli at Treebo
    • Deploying Brotli for Static Content at Dropbox
    • Progressive Enhancement with Brotli at Yelp
    • Speeding Up Redis with Compression at Doordash
  • Performance Optimization on Languages and Frameworks
    • Python at Netflix
    • Python at scale (3 parts) at Instagram
    • PHP at Slack
    • Go at Trivago
    • Ruby on Rails at GitLab
    • Choosing a Language Stack at WeWork
    • Switching from Go to Rust at Discord
    • ASP.NET Core Performance Optimization at Agoda

Intelligence

  • Big Data

    • Data Platform at Uber
    • Data Platform at BMW
    • Data Platform at Netflix
    • Data Platform at Flipkart
    • Data Platform at Coupang
    • Data Platform at DoorDash
    • Data Platform at Khan Academy
    • Data Infrastructure at Airbnb
    • Data Infrastructure at LinkedIn
    • Data Infrastructure at GO-JEK
    • Data Ingestion Infrastructure at Pinterest
    • Data Analytics Architecture at Pinterest
    • Big Data Processing (2 parts) at Spotify
    • Big Data Processing at Uber
    • Analytics Pipeline at Lyft
    • Analytics Pipeline at Grammarly
    • Analytics Pipeline at Teads
    • ML Data Pipelines for Real-Time Fraud Prevention at PayPal
    • Big Data Analytics and ML Techniques at LinkedIn
    • Self-Serve Reporting Platform on Hadoop at LinkedIn
    • Privacy-Preserving Analytics and Reporting at LinkedIn
    • Analytics Platform for Tracking Item Availability at Walmart
    • HALO: Hardware Analytics and Lifecycle Optimization at Facebook
    • RBEA: Real-time Analytics Platform at King
    • AresDB: GPU-Powered Real-time Analytics Engine at Uber
    • AthenaX: Streaming Analytics Platform at Uber
    • Delta: Data Synchronization and Enrichment Platform at Netflix
    • Keystone: Real-time Stream Processing Platform at Netflix
    • Databook: Turning Big Data into Knowledge with Metadata at Uber
    • Amundsen: Data Discovery & Metadata Engine at Lyft
    • Maze: Funnel Visualization Platform at Uber
    • Metacat: Making Big Data Discoverable and Meaningful at Netflix
    • SpinalTap: Change Data Capture System at Airbnb
    • Accelerator: Fast Data Processing Framework at eBay
    • Omid: Transaction Processing Platform at Yahoo
    • TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo
    • CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo
    • Spark on Scala: Analytics Reference Architecture at Adobe
    • Experimentation Platform (2 parts) at Spotify
    • Experimentation Platform at Airbnb
    • Smart Product Platform at Zalando
    • Log Analysis Platform at LINE
    • Data Visualisation Platform at Myntra
    • Building and Scaling Data Lineage at Netflix
    • Building a scalable data management system for computer vision tasks at Pinterest
    • Structured Data at Etsy
    • Scaling a Mature Data Pipeline - Managing Overhead at Airbnb
    • Spark Partitioning Strategies at Airbnb
    • Scaling the Hadoop Distributed File System at LinkedIn
  • Distributed Machine Learning
    • Aroma: Using ML for Code Recommendation at Facebook
    • Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft
    • LyftLearn: ML Model Training Infrastructure built on Kubernetes at Lyft
    • Michelangelo: Machine Learning Platform at Uber
    • Scaling Michelangelo
    • Machine Learning Platform at Yelp
    • Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber
    • COTA: Improving Customer Care with NLP & Machine Learning at Uber
    • Manifold: Model-Agnostic Visual Debugging Tool for Machine Learning at Uber
    • Repo-Topix: Topic Extraction Framework at Github
    • Concourse: Generating Personalized Content Notifications in Near-Real-Time at LinkedIn
    • Altus Care: Applying a Chatbot to Platform Engineering at eBay
    • PyKrylov: Accelerating Machine Learning Research at eBay
    • Box Graph: Spontaneous Social Network at Box
    • PricingNet: Pricing Modelling with Neural Networks at Skyscanner
    • PinText: Multitask Text Embedding System at Pinterest
    • Cannes: ML saves $1.7M a year on document previews at Dropbox
    • Scaling Gradient Boosted Trees for Click-Through-Rate Prediction at Yelp
    • Learning with Privacy at Scale at Apple
    • Deep Learning for Image Classification Experiment at Mercari
    • Deep Learning for Frame Detection in Product Images at Allegro
    • Content-based Video Relevance Prediction at Hulu
    • Improving Photo Selection With Deep Learning at TripAdvisor
    • Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor
    • Personalised Recommender Systems at BBC
    • Machine Learning (2 parts) at Condé Nast
    • Natural Language Processing and Content Analysis (2 parts) at Condé Nast
    • Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio
    • Machine Learning to Improve Streaming Quality at Netflix
    • Machine Learning to Match Drivers & Riders at GO-JEK
    • Improving Video Thumbnails with Deep Neural Nets at YouTube
    • Quantile Regression for Delivering On Time at Instacart
    • Cross-Lingual End-to-End Product Search with Deep Learning at Zalando
    • Machine Learning at Jane Street
    • Machine Learning for Ranking Answers End-to-End at Quora
    • Clustering Similar Stories Using LDA at Flipboard
    • Similarity Search at Flickr
    • Large-Scale Machine Learning Pipeline for Job Recommendations at Indeed
    • Deep Learning from Prototype to Production at Taboola
    • Atom Smashing using Machine Learning at CERN
    • Mapping Tags at Medium
    • Clustering with the Dirichlet Process Mixture Model in Scala at Monsanto
    • Map Pins with DBSCAN & Random Forests at Foursquare
    • Detecting and Preventing Fraud at Uber
    • Forecasting at Uber
    • Financial Forecasting at Uber
    • Productionizing ML with Workflows at Twitter
    • GUI Testing Powered by Deep Learning at eBay
    • Scaling Machine Learning to Recommend Driving Routes at Pivotal
    • Real-Time Predictions at DoorDash
    • Machine Intelligence at Dropbox
    • Machine Learning for Indexing Text from Billions of Images at Dropbox
    • Modeling User Journeys via Semantic Embeddings at Etsy
    • Automated Fake Account Detection at LinkedIn
    • Building Knowledge Graph at Airbnb
    • Core Modeling at Instagram
    • Neural Architecture Search (NAS) for Prohibited Item Detection at Mercari
    • Computer Vision at Airbnb
    • 3D Home Backend Algorithms at Zillow
    • Long-term Forecasts at Lyft
    • Discovering Popular Dishes with Deep Learning at Yelp
    • SplitNet Architecture for Ad Candidate Ranking at Twitter
    • Jobs Filter at Indeed
    • Architecting Restaurant Wait Time Predictions at Yelp
    • Music Personalization at Spotify
    • Deep Learning for Domain Name Valuation at GoDaddy
    • Similarity Clustering to Catch Fraud Rings at Stripe
    • Personalized Search at Etsy
    • ML Feature Serving Infrastructure at Lyft
    • Context-Specific Bidding System at Etsy
    • Moderating Promotional Spam and Inappropriate Content in Photos at Scale at Yelp
    • Optimizing Payments with Machine Learning at Dropbox

Architecture

  • Systems We Make
  • Tech Stack (2 parts) at Uber
  • Tech Stack at Medium
  • Tech Stack at Shopify
  • Building Services (4 parts) at Airbnb
  • Architecture of Evernote
  • Architecture of Chat Service (3 parts) at Riot Games
  • Architecture of League of Legends Client Update
  • Architecture of Ad Platform at Twitter
  • Architecture of API Gateway at Uber
  • Basic Architecture of Slack
  • Back-end at LinkedIn
  • Back-end at Flickr
  • Infrastructure (3 parts) at Zendesk
  • Cloud Infrastructure at Grubhub
  • Real-time Presence Platform at LinkedIn
  • Settings Platform at LinkedIn
  • Nearline System for Scale and Performance (2 parts) at Glassdoor
  • Real-time User Action Counting System for Ads at Pinterest
  • API Platform at Riot Games
  • Games Platform at The New York Times
  • Kabootar: Communication Platform at Swiggy
  • Simone: Distributed Simulation Service at Netflix
  • Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp
  • PriceAggregator: Intelligent System for Hotel Price Fetching (3 parts) at Agoda
  • Phoenix: Testing Platform (3 parts) at Tinder
  • Hexagonal Architecture at Netflix
  • Architecture of Play API Service at Netflix
  • Architecture of Sticker Services at LINE
  • Stack Overflow Enterprise at Palantir
  • Architecture of Following Feed, Interest Feed, and Picked For You at Pinterest
  • API Specification Workflow at WeWork
  • Media Database at Netflix
  • Member Transaction History Architecture at Walmart
  • Sync Engine (2 parts) at Dropbox
  • Architectures of Finance and Banking Systems
    • Bank Backend at Monzo
    • Trading Platform for Scale at Wealthsimple
    • Core Banking System at Margo Bank
    • Architecture of Nubank
    • Tech Stack at TransferWise
    • Tech Stack at Addepar
    • Avoiding Double Payments in a Distributed Payments System at Airbnb

Interview

  • Designing Large-Scale Systems

    • My Scaling Hero - Jeff Atwood (a dose of Endorphins before your interview, JK)
    • Software Engineering Advice from Building Large-Scale Distributed Systems - Jeff Dean
    • Introduction to Architecting Systems for Scale
    • Anatomy of a System Design Interview
    • 8 Things You Need to Know Before a System Design Interview
    • Top 10 System Design Interview Questions
    • Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell
    • Cloud Big Data Design Patterns - Lynn Langit
    • How NOT to design Netflix in your 45-minute System Design Interview?
    • API Best Practices: Webhooks, Deprecation, and Design
  • Explaining Low-Level Systems (OS, Network/Protocol, Database, Storage)
    • OSI and TCP/IP Cheat Sheet
    • The Precise Meaning of I/O Wait Time in Linux
    • Paxos Made Live – An Engineering Perspective
    • How to do Distributed Locking
    • SQL Transaction Isolation Levels Explained
  • "What Happens When... and How" Questions
    • Netflix: What Happens When You Press Play?
    • Monzo: How Peer-To-Peer Payments Work
    • Transit and Peering: How Your Requests Reach GitHub
    • How Spotify Streams Music

Organization

  • Engineering Levels at SoundCloud
  • Engineering Roles at Palantir
  • Scaling Engineering Teams at Twitter
  • Scaling Decision-Making Across Teams at LinkedIn
  • Scaling Data Science Team at GOJEK
  • Scaling Agile at Zalando
  • Scaling Agile at bol.com
  • Lessons Learned from Scaling a Product Team at Intercom
  • Hiring, Managing, and Scaling Engineering Teams at Typeform
  • Scaling the Datagram Team at Instagram
  • Scaling the Design Team at Flexport
  • Team Model for Scaling a Design System at Salesforce
  • Building Analytics Team (4 parts) at Wish
  • From 2 Founders to 1000 Employees at Transferwise
  • Lessons Learned Growing a UX Team from 10 to 170 at Adobe
  • Five Lessons from Scaling at Pinterest
  • Approach Engineering at Vinted
  • Using Metrics to Improve the Development Process (and Coach People) at Indeed
  • Mistakes to Avoid while Creating an Internal Product at Skyscanner
  • RACI (Responsible, Accountable, Consulted, Informed) at Etsy
  • Four Pillars of Leading People (Empathy, Inspiration, Trust, Honesty) at Zalando
  • Pair Programming at Shopify
  • Distributed Responsibility at Asana
  • Rotating Engineers at Zalando
  • Experiment Idea Review at Pinterest
  • Tech Migrations at Spotify
  • Improving Code Ownership at Yelp
  • Agile Code Base at eBay
  • Code Review
    • Code Review at Palantir
    • Code Review at LINE
    • Code Reviews at Medium
    • Code Review at LinkedIn
    • Code Review at Disney
    • Code Review at Netlify

Talk

  • Distributed Systems in One Lesson - Tim Berglund, Senior Director of Developer Experience at Confluent
  • Building Real Time Infrastructure at Facebook - Jeff Barber and Shie Erlich, Software Engineer at Facebook
  • Building Reliable Social Infrastructure for Google - Marc Alvidrez, Senior Manager at Google
  • Building a Distributed Build System at Google Scale - Aysylu Greenberg, SDE at Google
  • Site Reliability Engineering at Dropbox - Tammy Butow, Site Reliability Engineering Manager at Dropbox
  • How Google Does Planet-Scale for Planet-Scale Infra - Melissa Binde, SRE Director for Google Cloud Platform
  • Netflix Guide to Microservices - Josh Evans, Director of Operations Engineering at Netflix
  • Achieving Rapid Response Times in Large Online Services - Jeff Dean, Google Senior Fellow
  • Architecture to Handle 80K RPS Celebrity Sales at Shopify - Simon Eskildsen, Engineering Lead at Shopify
  • Lessons of Scale at Facebook - Bobby Johnson, Director of Engineering at Facebook
  • Performance Optimization for the Greater China Region at Salesforce - Jeff Cheng, Enterprise Architect at Salesforce
  • How GIPHY Delivers a GIF to 300 Millions Users - Alex Hoang and Nima Khoshini, Services Engineers at GIPHY
  • High Performance Packet Processing Platform at Alibaba - Haiyong Wang, Senior Director at Alibaba
  • Solving Large-scale Data Center and Cloud Interconnection Problems - Ihab Tarazi, CTO at Equinix
  • Scaling Dropbox - Kevin Modzelewski, Back-end Engineer at Dropbox
  • Scaling Reliability at Dropbox - Sat Kriya Khalsa, SRE at Dropbox
  • Scaling with Performance at Facebook - Bill Jia, VP of Infrastructure at Facebook
  • Scaling Live Videos to a Billion Users at Facebook - Sachin Kulkarni, Director of Engineering at Facebook
  • Scaling Infrastructure at Instagram - Lisa Guo, Instagram Engineering
  • Scaling Infrastructure at Twitter - Yao Yue, Staff Software Engineer at Twitter
  • Scaling Infrastructure at Etsy - Bethany Macri, Engineering Manager at Etsy
  • Scaling Real-time Infrastructure at Alibaba for Global Shopping Holiday - Xiaowei Jiang, Senior Director at Alibaba
  • Scaling Data Infrastructure at Spotify - Matti (Lepistö) Pehrs, Spotify
  • Scaling Pinterest - Marty Weiner, Pinterest’s founding engineer
  • Scaling Slack - Bing Wei, Software Engineer (Infrastructure) at Slack
  • Scaling Backend at Youtube - Sugu Sougoumarane, SDE at Youtube
  • Scaling Backend at Uber - Matt Ranney, Chief Systems Architect at Uber
  • Scaling Global CDN at Netflix - Dave Temkin, Director of Global Networks at Netflix
  • Scaling Load Balancing Infra to Support 1.3 Billion Users at Facebook - Patrick Shuff, Production Engineer at Facebook
  • Scaling (a NSFW site) to 200 Million Views A Day And Beyond - Eric Pickup, Lead Platform Developer at MindGeek
  • Scaling Counting Infrastructure at Quora - Chun-Ho Hung and Nikhil Gar, SEs at Quora
  • Scaling Git at Microsoft - Saeed Noursalehi, Principal Program Manager at Microsoft
  • Scaling Multitenant Architecture Across Multiple Data Centres at Shopify - Weingarten, Engineering Lead at Shopify

Book

  • Big Data, Web Ops & DevOps Ebooks - O'Reilly (Online - Free)
  • Google Site Reliability Engineering (Online - Free)
  • Distributed Systems for Fun and Profit (Online - Free)
  • What Every Developer Should Know About SQL Performance (Online - Free)
  • Beyond the Twelve-Factor App - Exploring the DNA of Highly Scalable, Resilient Cloud Applications (Free)
  • Chaos Engineering - Building Confidence in System Behavior through Experiments (Free)
  • The Art of Scalability
  • Web Scalability for Startup Engineers
  • Scalability Rules: 50 Principles for Scaling Web Sites

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