• All the Stuff the Internet Says on Scalability articles.
• YouTube Architecture
• Hilarious Video: Relational Database Vs NoSQL Fanbois
• Plenty Of Fish Architecture
• Machine Learning Driven Programming: A New Programming For A New World
• Jeff Dean On Large-Scale Deep Learning At Google
• Scaling Pinterest – From 0 To 10s Of Billions Of Page Views A Month In Two Years
• Google Architecture
• Building Super Scalable Systems: Blade Runner Meets Autonomic Computing in the Ambient Cloud
• Making The Case For Building Scalable Stateful Services In The Modern Era
• How Twitter Stores 250 Million Tweets A Day Using MySQL
• Scaling Twitter: Making Twitter 10000 Percent Faster
• The WhatsApp Architecture Facebook Bought For $19 Billion
• How WhatsApp Grew To Nearly 500 Million Users, 11,000 Cores, And 70 Million Messages A Second
• Flickr Architecture
• A Beginner’s Guide To Scaling To 11 Million+ Users On Amazon’s AWS
• How Do We Explain The Unreasonable Effectiveness Of IT?
• Matt Cutts: 10 Lessons Learned From The Early Days Of Google
• Amazon Architecture
• Jeff Dean On Large-Scale Deep Learning At Google
• A Beginner’s Guide To Scaling To 11 Million+ Users On Amazon’s AWS
• StackOverflow Update: 560M Pageviews A Month, 25 Servers, And It’s All About Performance
• Oculus Causes A Rift, But The Facebook Deal Will Avoid A Scaling Crisis For Virtual Reality
• How I Learned to Stop Worrying and Love Using a Lot of Disk Space to Scale
• Stack Overflow Architecture
• How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs
• How Does Google Do Planet-Scale Engineering For A Planet-Scale Infrastructure?
• 7 Years Of YouTube Scalability Lessons In 30 Minutes
• Facebook
• How Facebook’s Safety Check Works
• The Architecture Twitter Uses To Deal With 150M Active Users, 300K QPS, A 22 MB/S Firehose, And Send Tweets In Under 5 Seconds
• Google On Latency Tolerant Systems: Making A Predictable Whole Out Of Unpredictable Parts
• An Unorthodox Approach to Database Design : The Coming of the Shard
• Building Super Scalable Systems: Blade Runner Meets Autonomic Computing in the Ambient Cloud
• Startups Are Creating A New System Of The World For IT
• Are Cloud Based Memory Architectures the Next Big Thing?
• Latency is Everywhere and it Costs You Sales – How to Crush it
• How will memristors change everything?
• A 360 Degree View Of The Entire Netflix Stack
• DataSift Architecture: Realtime Datamining At 120,000 Tweets Per Second
• Useful Scalability Blogs
• Pinterest Architecture Update – 18 Million Visitors, 10x Growth,12 Employees, 410 TB Of Data
• Scaling Traffic: People Pod Pool of On Demand Self Driving Robotic Cars who Automatically Refuel from Cheap Solar
• Architecting Backend For A Social Product
• Why My Slime Mold Is Better Than Your Hadoop Cluster
• VoltDB Decapitates Six SQL Urban Myths And Delivers Internet Scale OLTP In The Process
• The Canonical Cloud Architecture 
• How Do You Program A Computer With 10 Terabytes Of RAM?
• Justin.Tv’s Live Video Broadcasting Architecture
• Why Are Facebook, Digg, And Twitter So Hard To Scale?
• What The Heck Are You Actually Using NoSQL For?
• How Google Invented An Amazing Datacenter Network Only They Could Create
• Playfish’s Social Gaming Architecture – 50 Million Monthly Users And Growing
• The Updated Big List Of Articles On The Amazon Outage
• Using Gossip Protocols For Failure Detection, Monitoring, Messaging And Other Good Things
• The Etsy Saga: From Silos To Happy To Billions Of Pageviews A Month
• How Twitter Stores 250 Million Tweets A Day Using MySQL
• Tumblr Architecture – 15 Billion Page Views A Month And Harder To Scale Than Twitter
• Is It Time To Get Rid Of The Linux OS Model In The Cloud?
• The State Of NoSQL In 2012
• Ask HighScalability: Facing Scaling Issues With News Feeds On Redis. Any Advice?
• Facebook Timeline: Brought To You By The Power Of Denormalization
• A Perfect Fifth Of Notes On Scalability
• Cell Architectures
• Elements Of Scale: Composing And Scaling Data Platforms
• Instagram Improved Their App’s Performance. Here’s How.
• Netflix: Developing, Deploying, And Supporting Software According To The Way Of The Cloud
• Instagram Architecture: 14 Million Users, Terabytes Of Photos, 100s Of Instances, Dozens Of Technologies
• How Can We Build Better Complex Systems? Containers, Microservices, And Continuous Delivery.
• The Stunning Scale Of AWS And What It Means For The Future Of The Cloud
• The Instagram Architecture Facebook Bought For A Cool Billion Dollars
• 10 Core Architecture Pattern Variations For Achieving Scalability
• StackExchange Architecture Updates – Running Smoothly, Amazon 4x More Expensive
• Pursue Robust Indefinite Scalability With The Movable Feast Machine
• Tagged Architecture – Scaling To 100 Million Users, 1000 Servers, And 5 Billion Page Views
• 17 Techniques Used To Scale Turntable.Fm And Labmeeting To Millions Of Users
• 5 Scalability Poisons And 3 Cloud Scalability Antidotes
• The Secret Of Scaling: You Can’t Linearly Scale Effort With Capacity
• Must See: 5 Steps To Scaling MongoDB (Or Any DB) In 8 Minutes
• What Google App Engine Price Changes Say About The Future Of Web Architecture
• The Three Ages Of Google – Batch, Warehouse, Instant
• Big List Of 20 Common Bottlenecks
• 10 EBay Secrets For Planet Wide Scaling
• Instagram Architecture Update: What’s New With Instagram?
• Strategy: Run A Scalable, Available, And Cheap Static Site On S3 Or GitHub
• Paper: The Akamai Network – 61,000 Servers, 1,000 Networks, 70 Countries 
• LevelDB – Fast And Lightweight Key/Value Database From The Authors Of MapReduce And BigTable
• Jim Starkey Is Creating A Brave New World By Rethinking Databases For The Cloud
• Peecho Architecture – Scalability On A Shoestring
• Google+ Is Built Using Tools You Can Use Too: Closure, Java Servlets, JavaScript, BigTable, Colossus, Quick Turnaround
• Cloud Architecture Revolution
• The Secret To 10 Million Concurrent Connections -The Kernel Is The Problem, Not The Solution
• 11 Common Web Use Cases Solved In Redis
• TripAdvisor Architecture – 40M Visitors, 200M Dynamic Page Views, 30TB Data
• 35+ Use Cases For Choosing Your Next NoSQL Database
• 101 Questions To Ask When Considering A NoSQL Database
• Awesome List Of Advanced Distributed Systems Papers
• Stack Overflow Makes Slow Pages 100x Faster By Simple SQL Tuning
• Heroku Emergency Strategy: Incident Command System And 8 Hour Ops Rotations For Fresh Minds
• 6 Ways Not To Scale That Will Make You Hip, Popular And Loved By VCs
• Aztec Empire Strategy: Use Dual Pipes In Your Aqueduct For High Availability
• Did The Microsoft Stack Kill MySpace?
• Facebook’s New Realtime Analytics System: HBase To Process 20 Billion Events Per Day
• 6 Lessons From Dropbox – One Million Files Saved Every 15 Minutes
• This Stuff Isn’t Taught, You Learn It Bit By Bit As You Solve Each Problem.
• Is Node.Js Becoming A Part Of The Stack? SimpleGeo Says Yes.
• Mollom Architecture – Killing Over 373 Million Spams At 100 Requests Per Second

  Google Pro Tip: Use Back-Of-The-Envelope-Calculations To Choose The Best Design

• Netflix: Continually Test By Failing Servers With Chaos Monkey
• 7 Design Patterns For Almost-Infinite Scalability
• What The Heck Are You Actually Using NoSQL For?
• The Stunning Scale Of AWS And What It Means For The Future Of The Cloud
• GPU Vs CPU Smackdown : The Rise Of Throughput-Oriented Architectures
• 8 Commonly Used Scalable System Design Patterns
• Great Introductory Video On Scalability From Harvard Computer Science
• Facebook’s New Real-Time Messaging System: HBase To Store 135+ Billion Messages A Month
• Facebook At 13 Million Queries Per Second Recommends: Minimize Request Variance
• Machine VM + Cloud API – Rewriting The Cloud From Scratch
• 10 Golden Principles For Building Successful Mobile/Web Applications
• Troubles With Sharding – What Can We Learn From The Foursquare Incident?
• Google’s Colossus Makes Search Real-Time By Dumping MapReduce
• 6 Ways To Kill Your Servers – Learning How To Scale The Hard Way
• Misco: A MapReduce Framework For Mobile Systems – Start Of The Ambient Cloud?
• Scaling An AWS Infrastructure – Tools And Patterns
• Vertical Scaling Ascendant – How Are SSDs Changing  Architectures?
• Think Of Latency As A Pseudo-Permanent Network Partition
• 7 Scaling Strategies Facebook Used To Grow To 500 Million Users
• How Can We Spark The Movement Of Research Out Of The Ivory Tower And Into Production?
• Big Data Counting: How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory
• Google: Taming The Long Latency Tail – When More Machines Equals Worse Results
• Ask For Forgiveness Programming – Or How We’ll Program 1000 Cores
• Grace Hopper To Programmers: Mind Your Nanoseconds!
• The Anatomy Of Search Technology: Blekko’s NoSQL Database
• The Anatomy Of Search Technology: Crawling Using Combinators
• C Is For Compute – Google Compute Engine (GCE)
• 10 Golden Principles For Building Successful Mobile/Web Applications
• The Performance Of Distributed Data-Structures Running On A “Cache-Coherent” In-Memory Data Grid
• MemSQL Architecture – The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)
• Prismatic Architecture – Using Machine Learning On Social Networks To Figure Out What You Should Read On The Web
• Changing Architectures: New Datacenter Networks Will Set Your Code And Data Free
• MemSQL Architecture – The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)
• Prismatic Architecture – Using Machine Learning On Social Networks To Figure Out What You Should Read On The Web
• Hidden History: Driving The Last Spike Of The Transcontinental Railroad Was An Early Version Of The Internet Of Things
• Your Load Generator Is Probably Lying To You – Take The Red Pill And Find Out Why
• What Can The Amazing Race To The South Pole Teach Us About Startups?
• If You’re Programming A Cell Phone Like A Server You’re Doing It Wrong
• Vertical Scaling Ascendant – How Are SSDs Changing  Architectures?
• 10 Golden Principles For Building Successful Mobile/Web Applications
• The Clever Ways Chrome Hides Latency By Anticipating Your Every Need
• An Epic TripAdvisor Update: Why Not Run On The Cloud? The Grand Experiment.
• Google Spanner’s Most Surprising Revelation: NoSQL is Out and NewSQL is In
• Russ’ 10 Ingredient Recipe for Making 1 Million TPS on $5K Hardware
• Sharding The Hibernate Way
• The Mother Of All Database Normalization Debates On Coding Horror
• Log Everything All The Time
• Scaling Secret #2: Denormalizing Your Way To Speed And Profit
• Strategy: Diagonal Scaling – Don’t Forget To Scale Out AND Up
• Paper: On Designing And Deploying Internet-Scale Services
• Strategy: Three Techniques To Survive Traffic Surges By Quickly Scaling Your Site
• ZooKeeper – A Reliable, Scalable Distributed Coordination System
• GridGain: One Compute Grid, Many Data Grids
• Scaling Spam Eradication Using Purposeful Games: Die Spammer Die!
• Google AppEngine – A Second Look
• Cloud Programming Directly Feeds Cost Allocation Back Into Software Design
• Paper: The End Of An Architectural Era (It’s Time For A Complete Rewrite)
• At Some Point The Cost Of Servers Outweighs The Cost Of Programmers
• Drop ACID And Think About Data
• How To Succeed At Capacity Planning Without Really Trying : An Interview With Flickr’s John Allspaw On His New Book
• Ten Lessons From GitHub’s First Year In 2008
• How Google Serves Data From Multiple Datacenters
• Strategy: Break Up The Memcache Dog Pile
• Building Scalable Systems Using Data As A Composite Material
• MySQL And Memcached: End Of An Era?
• Seven Signs You May Need A NoSQL Database
• 7 Lessons Learned While Building Reddit To 270 Million Page Views A Month
• How Can We Spark The Movement Of Research Out Of The Ivory Tower And Into Production?
• 6 Ways To Kill Your Servers – Learning How To Scale The Hard Way
• Machine VM + Cloud API – Rewriting The Cloud From Scratch
• Heroku Emergency Strategy: Incident Command System And 8 Hour Ops Rotations For Fresh Minds
• 6 Ways Not To Scale That Will Make You Hip, Popular And Loved By VCs
• Google+ Is Built Using Tools You Can Use Too: Closure, Java Servlets, JavaScript, BigTable, Colossus, Quick Turnaround
• Six Lessons Learned The Hard Way About Scaling A Million User System
• Sean Hull’s 20 Biggest Bottlenecks That Reduce And Slow Down Scalability
• How Twitter Stores 250 Million Tweets A Day Using MySQL
• Resiliency Is The New Normal – A Deep Look At What It Means And How To Build It
• Switch Your Databases To Flash Storage. Now. Or You’re Doing It Wrong.
• Ask HS: What Will Programming And Architecture Look Like In 2020?
• Designing For Resiliency Will Be So 2013
• Pinterest Cut Costs From $54 To $20 Per Hour By Automatically Shutting Down Systems
• Robert Scoble’s Rules For Successfully Scaling Startups
• What If Cars Were Rented Like We Hire Programmers?
• How Facebook Makes Mobile Work At Scale For All Phones, On All Screens, On All Networks
• The Four Meta Secrets Of Scaling At Facebook
• Facebook At 13 Million Queries Per Second Recommends: Minimize Request Variance
• Google: Taming The Long Latency Tail – When More Machines Equals Worse Results
• Google Strategy: Tree Distribution Of Requests And Responses
• AppBackplane – A Framework For Supporting Multiple Application Architectures
• The Changing Face Of Scale – The Downside Of Scaling In The Contextual Age
• Beyond Threads And Callbacks – Application Architecture Pros And Cons
• 42 Monster Problems That Attack As Loads Increase
• When All The Program’s A Graph – Prismatic’s Plumbing Library
• Better Browser Caching Is More Important Than No Javascript Or Fast Networks For HTTP Performance
• DuckDuckGo Architecture – 1 Million Deep Searches A Day And Growing
• More Numbers Every Awesome Programmer Must Know
• What Can The Amazing Race To The South Pole Teach Us About Startups?
• 100 Curse Free Lessons From Gordon Ramsay On Building Great Software
• How Do You Create A 100th Monkey Software Development Culture?
• Leveraging Cloud Computing At Yelp – 102 Million Monthly Vistors And 39 Million Reviews
• Busting 4 Modern Hardware Myths – Are Memory, HDDs, And SSDs Really Random Access?
• The 10 Deadly Sins Against Scalability
• That’s Not My Problem – I’m Renting Them
• 100 Curse Free Lessons From Gordon Ramsay On Building Great Software
• Salesforce Architecture – How They Handle 1.3 Billion Transactions A Day
• Scaling Mailbox – From 0 To One Million Users In 6 Weeks And 100 Million Messages Per Day
• Cinchcast Architecture – Producing 1,500 Hours Of Audio Every Day
• StubHub Architecture: The Surprising Complexity Behind The World’s Largest Ticket Marketplace
• IDoneThis – Scaling An Email-Based App From Scratch
• ESPN’s Architecture At Scale – Operating At 100,000 Duh Nuh Nuhs Per Second
• One Story Of Life As Told Through Queues
• How Can Batching Requests Actually Reduce Latency?
• How Google Backs Up The Internet Along With Exabytes Of Other Data
• 10 Things Bitly Should Have Monitored
• How Next Big Sound Tracks Over A Trillion Song Plays, Likes, And More Using A Version Control System For Hadoop Data
• How Would You Build The Next Internet? Loons, Drones, Copters, Satellites, Or Something Else?
• 8 Ways Stardog Made Its Database Insanely Scalable
• NYTimes Architecture: No Head, No Master, No Single Point Of Failure
• Under Snowden’s Light Software Architecture Choices Become Murky
• How HipChat Stores And Indexes Billions Of Messages Using ElasticSearch And Redis
• What Happens While Your Brain Sleeps Is Surprisingly Like How Computers Stay Sane
• 22 Recommendations For Building Effective High Traffic Web Software
• How Can Batching Requests Actually Reduce Latency?
• Evolution Of Bazaarvoice’s Architecture To 500M Unique Users Per Month
• One Story Of Life As Told Through Queues
• Hidden History: Driving The Last Spike Of The Transcontinental Railroad Was An Early Version Of The Internet Of Things
• We Finally Cracked The 10K Problem – This Time For Managing Servers With 2000x Servers Managed Per Sysadmin
• Google Says Cloud Prices Will Follow Moore’s Law: Are We All Renters Now?
• 10 Things You Should Know About AWS
• The FireBox Warehouse Scale Computer In 2020 Will Have 1K Sockets, 100K Cores, 100PB NV RAM, And A 4Pb/S Network
• ESPN’s Architecture At Scale – Operating At 100,000 Duh Nuh Nuhs Per Second
• Google’s Sanjay Ghemawat On What Made Google Google And Great Big Data Career Advice
• Little’s Law, Scalability And Fault Tolerance: The OS Is Your Bottleneck. What You Can Do?
• How Google Backs Up The Internet Along With Exabytes Of Other Data
• Planetary-Scale Computing Architectures For Electronic Trading And How Algorithms Shape Our World
• Paper: Network Stack Specialization For Performance
• How The AOL.Com Architecture Evolved To 99.999% Availability, 8 Million Visitors Per Day, And 200,000 Requests Per Second
• 5 Tips For Scaling NoSQL Databases: Don’t Trust Assumptions
• Little’s Law, Scalability And Fault Tolerance: The OS Is Your Bottleneck. What You Can Do?
• Here’s A 1300 Year Old Solution To Resilience – Rebuild, Rebuild, Rebuild
• This Is Why Microsoft Won. And Why They Lost.
• Microservices – Not A Free Lunch!
• Update On Disqus: It’s Still About Realtime, But Go Demolishes Python
• 10 Program Busting Caching Mistakes
• Bitly: Lessons Learned Building A Distributed System That Handles 6 Billion Clicks A Month
• 9 Principles Of High Performance Programs
• How Twitter Uses Redis To Scale – 105TB RAM, 39MM QPS, 10,000+ Instances
• Getting Things Right: A Look At Centralized Vs Decentralized Systems Through The Eyes Of Instant Replay
• 10 Common Server Setups For Your Web Application
• Strategy: Change The Problem
• Let’s Build Maker Cities For Maker People Around New Resources Like Bandwidth, Compute, And Atomically-Precise Manufacturing
• The Easy Way Of Building A Growing Startup Architecture Using HAProxy, PHP, Redis And MySQL To Handle 1 Billion Requests A Week
• The Great Microservices Vs Monolithic Apps Twitter Melee
• StackOverflow Update: 560M Pageviews A Month, 25 Servers, And It’s All About Performance
• The Secret Of Scaling: You Can’t Linearly Scale Effort With Capacity
• 10 Common Server Setups For Your Web Application
• All Employees Should Be Limited Only By Their Ability Rather Than An Absence Of Resources
• The Big Problem Is Medium Data
• The Machine: HP’s New Memristor Based Datacenter Scale Computer – Still Changing Everything
• Make Any Framework Suck Less With These 10 Insightful Lessons
• We Are Leaving 3x-4x Performance On The Table Just Because Of Configuration
• Aeron: Do We Really Need Another Messaging System?
• Facebook Mobile Drops Pull For Push-Based Snapshot + Delta Model
• How League Of Legends Scaled Chat To 70 Million Players – It Takes Lots Of Minions
• That’s Not My Problem – I’m Renting Them
• Instagram Improved Their App’s Performance. Here’s How
• Rescuing An Outsourced Project From Collapse: 8 Problems Found And 8 Lessons Learned
• Vinted Architecture: Keeping A Busy Portal Stable By Deploying Several Hundred Times Per Day
• Matt Cutts: 10 Lessons Learned From The Early Days Of Google
• Paper: Immutability Changes Everything By Pat Helland
• Learn From My Pain – 5 Lessons From Ello’s Adventures In Rapid Scaling
• The Ultimate Guide: 5 Methods For Debugging Production Servers At Scale
• Von Neumann Had One Piece Of Advice For Us: Not To Originate Anything.
• Linus: The Whole “Parallel Computing Is The Future” Is A Bunch Of Crock.
• Scalability As A Service
• Paper: Large-Scale Cluster Management At Google With Borg
• The Big Problem Is Medium Data
• Multithreaded Programming Has Really Gone To The Dogs
• The Machine: HP’s New Memristor Based Datacenter Scale Computer – Still Changing Everything
• All Employees Should Be Limited Only By Their Ability Rather Than An Absence Of Resources.
• Auth0 Architecture – Running In Multiple Cloud Providers And Regions
• Make Any Framework Suck Less With These 10 Insightful Lessons
• The Black Magic Of Systematically Reducing Linux OS Jitter
• 6 Ways To Defeat The Coming Robot Army Swarms
• How We Scale VividCortex’s Backend Systems
• Seven Of The Nastiest Anti-Patterns In Microservices
• HappyPancake: A Retrospective On Building A Simple And Scalable Foundation
• The Convergence That Changes Everything: Data Gravity + Containers + Microservices
• AppLovin: Marketing To Mobile Consumers Worldwide By Processing 30 Billion Requests A Day
• Scaling Kim Kardashian To 100 Million Page Views
• Rescuing An Outsourced Project From Collapse: 8 Problems Found And 8 Lessons Learned
• Vinted Architecture: Keeping A Busy Portal Stable By Deploying Several Hundred Times Per Day
• How Debugging Is Like Hunting Serial Killers
• Algolia’s Fury Road To A Worldwide API Part 3
• Architecting Backend For A Social Product
• This. Just. This.
• 64 Network DO’s And DON’Ts For Game Engines. Part IIIa: Server-Side
• Why My Water Droplet Is Better Than Your Hadoop Cluster
• How Autodesk Implemented Scalable Eventing Over Mesos
• Want IoT? Here’s How A Major US Utility Collects Power Data From Over 5.5 Million Meters
• How Uber Scales Their Real-Time Market Platform
• Trade Stimulators And The Very Old Idea Of Increasing User Engagement 
• Building Globally Distributed, Mission Critical Applications: Lessons From The Trenches Part 2
• 7 Strategies For 10x Transformative Change
• Ask HighScalability: Choose An Async App Server Or Multiple Blocking Servers?
• How Facebook Tells Your Friends You’re Safe In A Disaster In Under Five Minutes
• How Will New Memory Technologies Impact In-Memory Databases?
• Uber Goes Unconventional: Using Driver Phones As A Backup Datacenter
• 5 Lessons And 8 Industry Changes Over 5 Years As Etsy CTO
• How Uber Scales Their Real-Time Market Platform
• How Shopify Scales To Handle Flash Sales From Kanye West And The Superbowl
• What Ideas In IT Must Die?
• 5 Lessons From 5 Years Of Building Instagram
• Segment: Rebuilding Our Infrastructure With Docker, ECS, And Terraform
• Deep Lessons From Google And EBay On Building Ecosystems Of Microservices
• How Does The Use Of Docker Effect Latency?
• The Serverless Start-Up – Down With Servers!
• Malice Or Stupidity Or Inattention? Using Code Reviews To Find Backdoors
• Google’s Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture
• How To Build Your Property Management System Integration Using Microservices
• Let’s Donate Our Organs And Unused Cloud Cycles To Science
• Lessons Learned From Scaling Uber To 2000 Engineers, 1000 Services, And 8000 Git Repositories
• How Uber Manages A Million Writes Per Second Using Mesos And Cassandra Across Multiple Datacenters
• The Dollar Shave Club Architecture Unilever Bought For $1 Billion
• Code Generation: The Inner Sanctum Of Database Performance
• The Cat-And-Mouse Story Of Implementing Anti-Spam For Mail.Ru Group’s Email Service And What Tarantool Has To Do With This
• The Always On Architecture – Moving Beyond Legacy Disaster Recovery
• How Facebook Live Streams To 800,000 Simultaneous Viewers
• How Twitter Handles 3,000 Images Per Second
• The Gig Economy Breaks Social Security
• A Journey Through How Zapier Automates Billions Of Workflow Automation Tasks

Posts Teaching the Basics

• Intuitively Showing How To Scale A Web Application Using A Coffee Shop As An Example
• 7 Scaling Strategies Facebook Used To Grow To 500 Million Users
• The 7 Stages Of Scaling Web Apps
• The 4 Building Blocks Of Architecting Systems For Scale
• Scalability for Dummies by Sebastian Kreutzberger
• Great Introductory Video On Scalability From Harvard Computer Science
• The 7 Stages Of Scaling Web Apps
• Five Ways To Stop Framework Fixation From Crashing Your Scaling Strategy
• What’s Your Scalability Plan?
• Some Facebook Secrets To Better Operations
• Papers: Readings In Distributed Systems
• Learn How To Think At Scale
• Real World Web: Performance & Scalability
• The Canonical Cloud Architecture
• How Google Taught Me To Cache And Cash-In
• 8 Commonly Used Scalable System Design Patterns
• Google Pro Tip: Use Back-Of-The-Envelope-Calculations To Choose The Best Design
• Awesome List Of Advanced Distributed Systems Papers
• A Flock Of Tasty Sources On How To Start Learning High Scalability
• A Beginner’s Guide To Scaling To 11 Million+ Users On Amazon’s AWS

from:http://highscalability.com/all-time-favorites/ 2017-7-27