# High Scalability, High Availability, High Stability, High Performance, and High Intelligence Back-end Designs

An updated and curated list of selected readings to illustrate best practices in building High Scalability, High Availability, High Stability, High Performance, and High Intelligence back-end systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users.

#### If your back-end went slow :traffic_light:
> Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some [design principles](#principles) and checking how [scalability](#scalability) and [performance](#performance) problems are solved at tech companies. The section of [intelligence](#intelligence) are created for those who work with data and machine learning at big (data) and deep (learning) scale.

#### If your back-end went down :construction:
> "Even if you lose all one day, you can build all over again if you retain your calm!" - Thuan Pham, Vietnamese refugee, CTO of Uber Technologies Inc. So, keep calm and mind the [availability](#availability) and [stability](#stability) matters! 

#### If you have an incomming System Design interview :ocean:
> Look at some [interview notes](#interview) and [real-world architectures with completed diagrams](#architectures) to get a comprehensive view before designing your system on whiteboard. You can check some [talks](#talks) of engineers from tech giants to know how they build, scale, and optimize their systems. There are some selected [books](#books) for you (most of them are free)! Good luck :four_leaf_clover:

#### Community Power :mountain_cableway::aerial_tramway::mountain_cableway:

> Contributions are greatly welcome! You may want to take a look at the [contribution guidelines](CONTRIBUTING.md).

> If you find this project helpful, please share on your chat groups, [on Twitter](https://ctt.ec/V8B2p), or [on Weibo](http://t.cn/RnjFLCB) so more people can be helped! Power is gained by sharing knowledge, not hoarding it. Thank you! :hibiscus:

## Contents
- [Principles](#principles)
- [Scalability](#scalability)
- [Availability](#availability)
- [Stability](#stability)
- [Performance](#performance)
- [Intelligence](#intelligence)
- [Architectures](#architectures)
- [Ad-hoc](#ad-hoc)
- [Interview](#interview)
- [Talks](#talks)
- [Books](#books)

## Principles
* [Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google](https://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
* [On Efficiency, Reliability, Scaling - James Hamilton, VP at AWS](http://mvdirona.com/jrh/work/)
* [Things to Keep in Mind When Building a Platform for the Enterprise - Heidi Williams, VP Platform at Box](https://blog.box.com/blog/4-things-to-keep-in-mind-when-building-a-platform-for-the-enterprise/)
* [Principles of Chaos Engineering](https://www.usenix.org/conference/srecon17americas/program/presentation/rosenthal)
* [Finding the Order in Chaos](https://www.usenix.org/conference/srecon16/program/presentation/lueder)
* [The Twelve-Factor App](https://12factor.net/)
* [Clean Architecture](https://8thlight.com/blog/uncle-bob/2012/08/13/the-clean-architecture.html)
* [High Cohesion and Low Coupling](http://www.math-cs.gordon.edu/courses/cs211/lectures-2009/Cohesion,Coupling,MVC.pdf)
* [CAP Theorem and Trade-offs](http://robertgreiner.com/2014/08/cap-theorem-revisited/)
* [CP Databases and AP Databases](https://blog.andyet.com/2014/10/01/right-database)
* [Stateless vs Stateful Scalability](http://ithare.com/scaling-stateful-objects/)	
* [Scale Up vs Scale Out](https://www.brianjgraf.com/2013/05/17/scalability-scale-up-scale-out-care/)
* [Scale Up vs Scale Out: Hidden Costs](https://blog.codinghorror.com/scaling-up-vs-scaling-out-hidden-costs/)
* [Best Practices for Scaling Out](https://blog.openshift.com/best-practices-for-horizontal-application-scaling/)
* [ACID and BASE](https://neo4j.com/blog/acid-vs-base-consistency-models-explained/)
* [Blocking/Non-Blocking and Sync/Async](https://blogs.msdn.microsoft.com/csliu/2009/08/27/io-concept-blockingnon-blocking-vs-syncasync/)
* [Performance and Scalability of Databases](https://use-the-index-luke.com/sql/testing-scalability)
* [Database Isolation Levels and Effects on Performance and Scalability](http://highscalability.com/blog/2011/2/10/database-isolation-levels-and-their-effects-on-performance-a.html)
* [The Probability of Data Loss in Large Clusters](https://martin.kleppmann.com/2017/01/26/data-loss-in-large-clusters.html)
* [SQL vs NoSQL](https://www.upwork.com/hiring/data/sql-vs-nosql-databases-whats-the-difference/)
* [SQL vs NoSQL - Lesson Learned from Salesforce](https://engineering.salesforce.com/sql-or-nosql-9eaf1d92545b)
* [NoSQL Databases: Survey and Decision Guidance](https://medium.baqend.com/nosql-databases-a-survey-and-decision-guidance-ea7823a822d)
* [How Sharding Works](https://medium.com/@jeeyoungk/how-sharding-works-b4dec46b3f6)
* [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
* [Consistent Hashing: Algorithmic Tradeoffs](https://medium.com/@dgryski/consistent-hashing-algorithmic-tradeoffs-ef6b8e2fcae8)
* [Uniform Consistent Hashing (used at Netflix)](https://medium.com/netflix-techblog/distributing-content-to-open-connect-3e3e391d4dc9)
* [Eventually Consistent - Werner Vogels, CTO at Amazon](https://www.allthingsdistributed.com/2008/12/eventually_consistent.html)
* [Cache is King](https://www.stevesouders.com/blog/2012/10/11/cache-is-king/)
* [Anti-Caching](http://the-paper-trail.org/blog/paper-notes-anti-caching/)
* [Understand Latency](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
* [Latency Numbers Every Programmer Should Know](http://norvig.com/21-days.html#answers)
* [The Calculus of Service Availability](https://queue.acm.org/detail.cfm?id=3096459&__s=dnkxuaws9pogqdnxmx8i)
* [Architecture Issues When Scaling Web Applications: Bottlenecks, Database, CPU, IO](http://highscalability.com/blog/2014/5/12/4-architecture-issues-when-scaling-web-applications-bottlene.html)	
* [Common Bottlenecks](http://highscalability.com/blog/2012/5/16/big-list-of-20-common-bottlenecks.html)
* [Life Beyond Distributed Transactions](https://queue.acm.org/detail.cfm?id=3025012)
* [Relying on Software to Redirect Traffic Reliably at Various Layers](https://www.usenix.org/conference/srecon15/program/presentation/taveira)
* [Breaking Things on Purpose](https://www.usenix.org/conference/srecon17americas/program/presentation/andrus)
* [Avoid Over Engineering](https://medium.com/@rdsubhas/10-modern-software-engineering-mistakes-bc67fbef4fc8)
* [Scalability Worst Practices](https://www.infoq.com/articles/scalability-worst-practices)
* [Use Solid Technologies - Don’t Re-invent the Wheel - Keep It Simple!](https://medium.com/@DataStax/instagram-engineerings-3-rules-to-a-scalable-cloud-application-architecture-c44afed31406)
* [Simplicity by Distributing Complexity](https://jobs.zalando.com/tech/blog/simplicity-by-distributing-complexity/)
* [Why Over-Reusing is Bad](http://tech.transferwise.com/why-over-reusing-is-bad/)
* [Performance is a Feature](https://blog.codinghorror.com/performance-is-a-feature/)
* [Make Performance Part of Your Workflow](https://codeascraft.com/2014/12/11/make-performance-part-of-your-workflow/)
* [The Benefits of Server Side Rendering Over Client Side Rendering](https://medium.com/walmartlabs/the-benefits-of-server-side-rendering-over-client-side-rendering-5d07ff2cefe8)
* [Writing Code that Scales](https://blog.rackspace.com/writing-code-that-scales)
* [Automate and Abstract: Lessons from Facebook on Engineering for Scale](https://architecht.io/lessons-from-facebook-on-engineering-for-scale-f5716f0afc7a)
* [AWS Do's and Don'ts](https://8thlight.com/blog/sarah-sunday/2017/09/15/aws-dos-and-donts.html)
* [(UI) Design Doesn’t Scale - Stanley Wood, Design Director at Spotify](https://medium.com/@hellostanley/design-doesnt-scale-4d81e12cbc3e)
* [Linux Performance](http://www.brendangregg.com/linuxperf.html)
* [How To Design A Good API and Why it Matters - Joshua Bloch](https://www.infoq.com/presentations/effective-api-design)
* [Building Fast & Resilient Web Applications - Ilya Grigorik](https://www.igvita.com/2016/05/20/building-fast-and-resilient-web-applications/)
* [Design for Loose-coupling](http://bulgerpartners.com/how-loosely-coupled-architectures-are-helping-the-modernization-of-legacy-software/)
* [Design for Resiliency](http://highscalability.com/blog/2012/12/31/designing-for-resiliency-will-be-so-2013.html)
* [Design for Self-healing](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/self-healing)
* [Design for Scaling Out](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/scale-out)	
* [Design for Evolution](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/design-for-evolution)	
* [Learn from Mistakes](http://highscalability.com/blog/2013/8/26/reddit-lessons-learned-from-mistakes-made-scaling-to-1-billi.html)
* [Code Review Best Practices at Palantir](https://medium.com/@palantir/code-review-best-practices-19e02780015f)

## Scalability
* [Microservices and Orchestration](https://hackernoon.com/microservices-are-hard-an-invaluable-guide-to-microservices-2d06bd7bcf5d)
	* [Microservices Resource Guide - Martin Fowler, Chief Scientist at ThoughtWorks](https://martinfowler.com/microservices/)
	* [Microservices Patterns](http://microservices.io/patterns/)
	* [Advantages and Drawbacks of Microservices](https://cloudacademy.com/blog/microservices-architecture-challenge-advantage-drawback/)
	* [Microservices Scale Cube](http://microservices.io/articles/scalecube.html)
	* [Thinking Inside the Container (8 parts) at Riot Games](https://engineering.riotgames.com/news/thinking-inside-container)
	* [Containerization at Pinterest](https://medium.com/@Pinterest_Engineering/containerization-at-pinterest-92295347f2f3)
	* [Techniques for Splitting Up a Codebase into Microservices and Artifacts at LinkedIn](https://engineering.linkedin.com/blog/2016/02/q-a-with-jim-brikman--splitting-up-a-codebase-into-microservices)
	* [The Evolution of Container Usage at Netflix](https://medium.com/netflix-techblog/the-evolution-of-container-usage-at-netflix-3abfc096781b)
	* [Dockerizing MySQL at Uber](https://eng.uber.com/dockerizing-mysql/)
	* [Testing of Microservices at Spotify](https://labs.spotify.com/2018/01/11/testing-of-microservices/)
	* [Organize Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0)
	* [Lessons learned running Docker in production at Treehouse](https://medium.com/treehouse-engineering/lessons-learned-running-docker-in-production-5dce99ece770)
	* [Inside a SoundCloud Microservice](https://developers.soundcloud.com/blog/inside-a-soundcloud-microservice)
	* [Microservices at BlaBlaCar](http://blablatech.com/blog/micro-service-at-blablacar)
	* [Operate Kubernetes Reliably at Stripe](https://stripe.com/blog/operating-kubernetes)
	* [Kubernetes Traffic Routing (2 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/09/28/k8s-routing2/)
	* [Agrarian-Scale Kubernetes (3 parts) at New York Times](https://open.nytimes.com/agrarian-scale-kubernetes-part-3-ee459887ed7e)
	* [Mesos, Docker and Ochopod in Localization Services at Autodesk](http://cloudengineering.autodesk.com/blog/2015/11/mesos-docker-and-ochopod-in-autodesk-localization-services.html)
	* [Nanoservices at BBC Online](https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b)
	* [PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg](https://www.techatbloomberg.com/blog/powerfulseal-testing-tool-kubernetes-clusters/)
	* [Conductor: Microservices Orchestrator at Netflix](https://medium.com/netflix-techblog/netflix-conductor-a-microservices-orchestrator-2e8d4771bf40)
	* [Making 10x Improvement in Release Times with Docker and Amazon ECS at Nextdoor](https://engblog.nextdoor.com/how-nextdoor-made-a-10x-improvement-in-release-times-with-docker-and-amazon-ecs-35aab52b726f)
	* [K8Guard: Auditing System for Kubernetes Clusters at Target.com](http://target.github.io/infrastructure/k8guard-the-guardian-angel-for-kuberentes)
	* [Deconstructing Monolithic Applications into (Kafka-driven) Services at Heroku](https://blog.heroku.com/monolithic-applications-into-services)
* [Distributed Caching](https://www.wix.engineering/single-post/scaling-to-100m-to-cache-or-not-to-cache)
	* [Read-Through, Write-Through, Write-Behind, and Refresh-Ahead Caching](https://docs.oracle.com/cd/E15357_01/coh.360/e15723/cache_rtwtwbra.htm#COHDG5177)
	* [Eviction Policy and Expiration Policy](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
	* [EVCache: Caching for a Global Netflix](https://medium.com/netflix-techblog/caching-for-a-global-netflix-7bcc457012f1)
	* [Memsniff: Robust Memcache Traffic Analyzer at Box](https://blog.box.com/blog/introducing-memsniff-robust-memcache-traffic-analyzer/)
	* [Caching with Consistent Hashing and Cache Smearing at Etsy](https://codeascraft.com/2017/11/30/how-etsy-caches/)
	* [Analysis of Photo Caching at Facebook](https://code.facebook.com/posts/220956754772273/an-analysis-of-facebook-photo-caching/)
	* [Cache Efficiency Exercise at Facebook](https://code.facebook.com/posts/964122680272229/web-performance-cache-efficiency-exercise/)
	* [tCache: Scalable Data-aware Java Caching at Trivago](http://tech.trivago.com/2015/10/15/tcache/)
	* [Reduce Memcached Memory Usage by 50% at Trivago](http://tech.trivago.com/2017/12/19/how-trivago-reduced-memcached-memory-usage-by-50/)
	* [Caching Internal Service Calls at Yelp](https://engineeringblog.yelp.com/2018/03/caching-internal-service-calls-at-yelp.html)
	* [Scaling Live Streaming for Large Events (with Distributed Cache) at Hulu](https://medium.com/hulu-tech-blog/scaling-hulu-live-streaming-for-large-events-march-madness-and-beyond-bedd73874f2)
	* [Estimating the Cache Efficiency using Big Data at Allegro](https://allegro.tech/2017/01/estimating-the-cache-efficiency-using-big-data.html)
* [Distributed Tracking and Tracing](https://www.oreilly.com/ideas/understanding-the-value-of-distributed-tracing)
	* [Tracking Service Infrastructure at Scale at Shopify](https://www.usenix.org/conference/srecon17americas/program/presentation/arthorne)
	* [Distributed Tracing with Pintrace at Pinterest](https://medium.com/@Pinterest_Engineering/distributed-tracing-at-pinterest-with-new-open-source-tools-a4f8a5562f6b)
	* [Distributed Tracing at HelloFresh](https://engineering.hellofresh.com/scaling-hellofresh-distributed-tracing-7b182928247d)
	* [Analyzing Distributed Trace Data at Pinterest](https://medium.com/@Pinterest_Engineering/analyzing-distributed-trace-data-6aae58919949)
	* [Distributed Tracing at Uber](https://eng.uber.com/distributed-tracing/)
	* [Data Checking at Dropbox](https://www.usenix.org/conference/srecon17asia/program/presentation/mah)
	* [Tracing Distributed Systems at Showmax](https://tech.showmax.com/2016/10/tracing-distributed-systems-at-showmax/)
	* [Real-time Distributed Tracing at LinkedIn](https://engineering.linkedin.com/distributed-service-call-graph/real-time-distributed-tracing-website-performance-and-efficiency)
	* [Zipkin: Distributed Systems Tracing at Twitter](https://blog.twitter.com/engineering/en_us/a/2012/distributed-systems-tracing-with-zipkin.html)
	* [osquery Across the Enterprise at Palantir](https://medium.com/@palantir/osquery-across-the-enterprise-3c3c9d13ec55)
* [Distributed Logging](https://blog.treasuredata.com/blog/2016/08/03/distributed-logging-architecture-in-the-container-era/)
	* [The Problem with Logging - Jeff Atwood](https://blog.codinghorror.com/the-problem-with-logging/)
	* [The Log: What Every Software Engineer Should Know](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying)
	* [Using Logs to Build a Solid Data Infrastructure - Martin Kleppmann](https://www.confluent.io/blog/using-logs-to-build-a-solid-data-infrastructure-or-why-dual-writes-are-a-bad-idea/)
	* [Scalable and Reliable Log Ingestion at Pinterest](https://medium.com/@Pinterest_Engineering/scalable-and-reliable-data-ingestion-at-pinterest-b921c2ee8754)
	* [Building DistributedLog at Twitter: High-performance replicated log service](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2015/building-distributedlog-twitter-s-high-performance-replicated-log-servic.html)
	* [Logging Service with Spark at CERN Accelerator](https://databricks.com/blog/2017/12/14/the-architecture-of-the-next-cern-accelerator-logging-service.html)
	* [Logging and Aggregation at Quora](https://engineering.quora.com/Logging-and-Aggregation-at-Quora)
	* [BookKeeper: Distributed Log Storage at Yahoo](https://yahooeng.tumblr.com/post/109908973316/bookkeeper-yahoos-distributed-log-storage-is)
	* [LogDevice: Distributed Data Store for Logs at Facebook](https://code.facebook.com/posts/357056558062811/logdevice-a-distributed-data-store-for-logs/)
	* [LogFeeder: Log Collection System at Yelp](https://engineeringblog.yelp.com/2018/03/introducing-logfeeder.html)
* [Distributed Security](https://msdn.microsoft.com/en-us/library/cc767123.aspx)
	* [Approach to Security at Scale at Dropbox](https://blogs.dropbox.com/tech/2018/02/security-at-scale-the-dropbox-approach/)
	* [Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix](https://medium.com/netflix-techblog/introducing-aardvark-and-repokid-53b081bf3a7e)	
	* [LISA: Distributed Firewall at LinkedIn](https://www.slideshare.net/MikeSvoboda/2017-lisa-linkedins-distributed-firewall-dfw)
	* [Distributed Security Alerting at Slack](https://slack.engineering/distributed-security-alerting-c89414c992d6)
	* [Secure Infrastructure To Store Bitcoin In The Cloud at Coinbase](https://engineering.coinbase.com/how-coinbase-builds-secure-infrastructure-to-store-bitcoin-in-the-cloud-30a6504e40ba)
	* [BinaryAlert: Real-time Serverless Malware Detection at Airbnb](https://medium.com/airbnb-engineering/binaryalert-real-time-serverless-malware-detection-ca44370c1b90)
	* [Scalable IAM Architecture to Secure Access to 100 AWS Accounts at Segment](https://segment.com/blog/secure-access-to-100-aws-accounts/)
	* [OAuth Audit Toolbox at Indeed](http://engineering.indeedblog.com/blog/2018/04/oaudit-toolbox/)
	* [Active Directory Password Blacklisting at Yelp](https://engineeringblog.yelp.com/2018/04/ad-password-blacklisting.html)
	* [Secure Infrastructure to Store Bitcoin in the Cloud at Coinbase](https://engineering.coinbase.com/how-coinbase-builds-secure-infrastructure-to-store-bitcoin-in-the-cloud-30a6504e40ba)	
* [Distributed Messaging and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
	* [When to use RabbitMQ or Kafka](https://content.pivotal.io/blog/understanding-when-to-use-rabbitmq-or-apache-kafka)
	* [Should You Put Several Event Types in the Same Kafka Topic? - Martin Kleppmann](https://www.confluent.io/blog/put-several-event-types-kafka-topic/)
	* [Kafka at Scale at LinkedIn](https://engineering.linkedin.com/kafka/running-kafka-scale)
	* [Samza: Stream Processing System for Latency Insighs at LinkedIn](https://engineering.linkedin.com/blog/2018/04/samza-aeon--latency-insights-for-asynchronous-one-way-flows)
	* [Delaying Asynchronous Message Processing with RabbitMQ at Indeed](http://engineering.indeedblog.com/blog/2017/06/delaying-messages/)
	* [Real-time Data Pipeline with Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html)
	* [Building Reliable Reprocessing and Dead Letter Queues with Kafka at Uber](https://eng.uber.com/reliable-reprocessing/)
	* [Audit Kafka End-to-End at Uber (count each message exactly once, audit a message across tiers)](https://eng.uber.com/chaperone/)
	* [Kafka for PaaS at Rakuten](https://techblog.rakuten.co.jp/2016/01/28/rakuten-paas-kafka/)
	* [Publishing with Kafka at The New York Times](https://open.nytimes.com/publishing-with-apache-kafka-at-the-new-york-times-7f0e3b7d2077)
	* [Kafka Streams on Heroku](https://blog.heroku.com/kafka-streams-on-heroku)
	* [Kafka in Platform Events Architecture at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63)	
	* [Kafka in Socket Architecture (with a Comprehensive Comparison Table) at Trello](https://tech.trello.com/why-we-chose-kafka/)	
	* [Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo](https://yahooeng.tumblr.com/post/161855616651/open-sourcing-bullet-yahoos-forward-looking)
	* [Benchmarking Streaming Computation Engines at Yahoo](https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at)
	* [Messaging Service at Riot Games](https://engineering.riotgames.com/news/riot-messaging-service)
	* [Event Stream Analytics with Druid (Search Engine meet Column DB) at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)
	* [Analytics Pipeline (Kafka, Dataflow, BigQuery) at Teads.tv](http://highscalability.com/blog/2018/4/9/give-meaning-to-100-billion-events-a-day-the-analytics-pipel.html)
	* [Deduplication Techniques](https://en.wikipedia.org/wiki/Data_deduplication)
		* [Exactly-once Semantics are Possible: Here’s How Kafka Does it](https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/)
		* [Real-time Deduping at Scale with Kafka-based Pipleline at Tapjoy](http://eng.tapjoy.com/blog-list/real-time-deduping-at-scale)
		* [Delivering Billions of Messages Exactly Once: Deduping at Segment](https://segment.com/blog/exactly-once-delivery/)
		* [Deduplication For Efficient Storage (From 50 PB To 32 PB) At Mail.Ru](https://medium.com/@andrewsumin/efficient-storage-how-we-went-down-from-50-pb-to-32-pb-99f9c61bf6b4)				
* [Distributed Searching](http://nwds.cs.washington.edu/files/nwds/pdf/Distributed-WR.pdf)
	* [Search Architecture of Instagram](https://engineering.instagram.com/search-architecture-eeb34a936d3a)
	* [Search Architecture of eBay](http://www.cs.otago.ac.nz/homepages/andrew/papers/2017-8.pdf)
	* [Improving Search Engine Efficiency by over 25% at eBay](https://www.ebayinc.com/stories/blogs/tech/making-e-commerce-search-faster/)	
	* [Search Federation Architecture at LinkedIn (2018)](https://engineering.linkedin.com/blog/2018/03/search-federation-architecture-at-linkedin)
	* [Search at Slack](https://slack.engineering/search-at-slack-431f8c80619e)
	* [Search and Recommendations at DoorDash](https://blog.doordash.com/powering-search-recommendations-at-doordash-8310c5cfd88c)
	* [Search Service at Twitter (2014)](https://blog.twitter.com/engineering/en_us/a/2014/building-a-complete-tweet-index.html)
	* [Nautilus: Travel Search Engine of Expedia](http://blog.expedia.com/expedias-nautilus-travel-search-engine-overview-and-applications/)
	* [Galene: Search Architecture of LinkedIn](https://engineering.linkedin.com/search/did-you-mean-galene)
	* [Manas: High Performing Customized Search System at Pinterest](https://medium.com/@Pinterest_Engineering/manas-a-high-performing-customized-search-system-cf189f6ca40f)
	* [Sherlock: Near Real Time Search Indexing at Flipkart](https://tech.flipkart.com/sherlock-near-real-time-search-indexing-95519783859d)
	* [Nebula: Storage Platform to Build Search Backends at Airbnb](https://medium.com/airbnb-engineering/nebula-as-a-storage-platform-to-build-airbnbs-search-backends-ecc577b05f06)
	* [ELK (Elasticsearch, Logstash, Kibana) Stack](https://logz.io/blog/15-tech-companies-chose-elk-stack/)
		* [Predictions in Real Time with ELK at Uber](https://eng.uber.com/elk/)
		* [Scaling Elasticsearch Clusters at Uber](https://www.infoq.com/presentations/uber-elasticsearch-clusters?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study)
		* [Elasticsearch Performance Tuning Practice at eBay](https://www.ebayinc.com/stories/blogs/tech/elasticsearch-performance-tuning-practice-at-ebay/)
		* [Elasticsearch at Kickstarter](https://kickstarter.engineering/elasticsearch-at-kickstarter-db3c487887fc)
		* [Distributed Troubleshooting Platform with ELK Stack at Target.com](http://target.github.io/infrastructure/distributed-troubleshooting)
		* [ELK at Robinhood](https://robinhood.engineering/taming-elk-4e1349f077c3)
		* [Log Parsing with Logstash and Google Protocol Buffers at Trivago](https://tech.trivago.com/2016/01/19/logstash_protobuf_codec/)
* [Distributed Storage](http://highscalability.com/blog/2011/11/1/finding-the-right-data-solution-for-your-application-in-the.html)
	* [In-memory Storage](https://medium.com/@denisanikin/what-an-in-memory-database-is-and-how-it-persists-data-efficiently-f43868cff4c1)
		* [Introduction to In-memory Data - Viktor Gamov, Solutions Architect at Hazelcast](https://www.infoq.com/presentations/in-memory-data)
		* [MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)](http://highscalability.com/blog/2012/8/14/memsql-architecture-the-fast-mvcc-inmem-lockfree-codegen-and.html)
		* [Optimizing Memcached Efficiency at Quora](https://engineering.quora.com/Optimizing-Memcached-Efficiency)
		* [Real-Time Data Warehouse with MemSQL on Cisco UCS](https://blogs.cisco.com/datacenter/memsql)
		* [Moving to MemSQL (with Horizontally Scalable, ACID Compliant, MySQL Compatibility) at Tapjoy](http://eng.tapjoy.com/blog-list/moving-to-memsql)
		* [MemSQL and Kinesis for Real-time Insights at Disney-ABC TV](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/68131)
	* [Durable Storage (S3, HDFS)](http://www.datacenterknowledge.com/archives/2013/10/04/object-storage-the-future-of-scale-out)
		* [Scaling HDFS at Uber](https://eng.uber.com/scaling-hdfs/)
		* [Reasons for Choosing S3 over HDFS at Databricks](https://databricks.com/blog/2017/05/31/top-5-reasons-for-choosing-s3-over-hdfs.html)
		* [Quantcast File System on Amazon S3](https://www.quantcast.com/blog/quantcast-file-system-on-amazon-s3/)
		* [Using S3 in Netflix Chukwa](https://medium.com/netflix-techblog/evolution-of-the-netflix-data-pipeline-da246ca36905)	
		* [Yahoo Cloud Object Store - Object Storage at Exabyte Scale](https://yahooeng.tumblr.com/post/116391291701/yahoo-cloud-object-store-object-storage-at)
		* [Ambry: Distributed Immutable Object Store at LinkedIn](https://www.usenix.org/conference/srecon17americas/program/presentation/shenoy)
		* [Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb](https://medium.com/airbnb-engineering/hammerspace-persistent-concurrent-off-heap-storage-3db39bb04472)	
* [Relational Databases (MySQL, MSSQL, PostgreSQL)](https://www.mysql.com/products/cluster/scalability.html)
	* [Microsoft SQL versus MySQL](https://www.upwork.com/hiring/data/sql-vs-mysql-which-relational-database-is-right-for-you/)
	* [SQL Database Performance Tuning](https://www.toptal.com/sql-server/sql-database-tuning-for-developers)
	* [Scaling PostgreSQL Using CUDA](http://highscalability.com/blog/2009/5/28/scaling-postgresql-using-cuda.html)
	* [Scaling Distributed Joins](http://blog.memsql.com/scaling-distributed-joins/)
	* [MySQL System Design at Booking.com](https://www.percona.com/live/mysql-conference-2015/sessions/bookingcom-evolution-mysql-system-design)
	* [PostgreSQL at Twitch](https://blog.twitch.tv/how-twitch-uses-postgresql-c34aa9e56f58)
	* [Scaling MySQL-based Financial Reporting System at Airbnb](https://medium.com/airbnb-engineering/tracking-the-money-scaling-financial-reporting-at-airbnb-6d742b80f040)
	* [Scaling MySQL at Wix](https://www.wix.engineering/single-post/scaling-to-100m-mysql-is-a-better-nosql)
	* [Switching from Postgres to MySQL at Uber](https://eng.uber.com/mysql-migration/)
	* [Handling Growth with Postgres at Instagram](https://engineering.instagram.com/handling-growth-with-postgres-5-tips-from-instagram-d5d7e7ffdfcb)
	* [Scaling the Analytics Database (Postgres) at TransferWise](http://tech.transferwise.com/scaling-our-analytics-database/)
	* [Updating a 50 Terabyte PostgreSQL Database at Adyen](https://medium.com/adyen/updating-a-50-terabyte-postgresql-database-f64384b799e7)
	* [Replication](https://m.alphasights.com/a-primer-on-database-replication-381b319cd032)		
		* [MySQL Parallel Replication (4 parts) at Booking.com](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-4-annex-under-the-hood-eb456cf8b2fb)
		* [Mitigating MySQL Replication Lag and Reducing Read Load at Github](https://githubengineering.com/mitigating-replication-lag-and-reducing-read-load-with-freno/)
		* [Black-Box Auditing: Verifying End-to-End Replication Integrity between MySQL and Redshift at Yelp](https://engineeringblog.yelp.com/2018/04/black-box-auditing.html)
		* [Monitoring MySQL Delayed Replication at IMVU](https://engineering.imvu.com/2013/01/09/monitoring-delayed-replication-with-a-focus-on-mysql/)
	* [Sharding (Horizontal Partitioning)](https://www.educative.io/collection/page/5668639101419520/5649050225344512/5146118144917504)
		* [Sharding MySQL at Pinterest](https://medium.com/@Pinterest_Engineering/sharding-pinterest-how-we-scaled-our-mysql-fleet-3f341e96ca6f)
		* [Sharding MySQL at MailChimp](https://devs.mailchimp.com/blog/using-shards-to-accommodate-millions-of-users/)
		* [Sharding MySQL at Twilio](https://www.twilio.com/engineering/2014/06/26/how-we-replaced-our-data-pipeline-with-zero-downtime)
		* [Sharding MySQL (3 parts) at Evernote](https://blog.evernote.com/tech/2015/10/08/the-great-shard-migration-part-ii/)
		* [Sharding Layer of Schemaless Datastore at Uber](https://eng.uber.com/schemaless-rewrite/)
		* [Sharding & IDs at Instagram](https://instagram-engineering.com/sharding-ids-at-instagram-1cf5a71e5a5c)
		* [Partitioning Main MySQL Database at Airbnb](https://medium.com/airbnb-engineering/how-we-partitioned-airbnb-s-main-database-in-two-weeks-55f7e006ff21)			
* [NoSQL Databases](https://www.thoughtworks.com/insights/blog/nosql-databases-overview)
	* [Key-Value Databases (DynamoDB, Voldemort, Manhattan)](http://highscalability.com/anti-rdbms-list-distributed-key-value-stores)
		* [Scaling Mapbox infrastructure with DynamoDB Streams](https://blog.mapbox.com/scaling-mapbox-infrastructure-with-dynamodb-streams-d53eabc5e972)
		* [Manhattan: Twitter’s distributed key-value database](https://blog.twitter.com/engineering/en_us/a/2014/manhattan-our-real-time-multi-tenant-distributed-database-for-twitter-scale.html)
		* [Sherpa: Yahoo’s distributed NoSQL key-value store](https://yahooeng.tumblr.com/post/120730204806/sherpa-scales-new-heights)
		* [Riak inside Chat Service Architecture at Riot Games](https://engineering.riotgames.com/news/chat-service-architecture-persistence)
		* [MPH: Fast and Compact Immutable Key-Value Stores at Indeed](http://engineering.indeedblog.com/blog/2018/02/indeed-mph/)
		* [zBase: High Performance, Elastic, Distributed Key-Value Store at Zynga](https://www.zynga.com/blogs/engineering/zbase-high-performance-elastic-distributed-key-value-store-2)
		* [Venice: Distributed Key-Value Database at Linkedin](https://engineering.linkedin.com/blog/2017/02/building-venice-with-apache-helix)
	* [Columnar Databases (Cassandra, HBase, Redshift)](https://aws.amazon.com/nosql/columnar/)
		* [Consistent Hashing in Cassandra](https://blog.imaginea.com/consistent-hashing-in-cassandra/)
		* [Understanding Gossip (Cassandra Internals)](https://www.youtube.com/watch?v=FuP1Fvrv6ZQ)
		* [When NOT to use Cassandra?](https://stackoverflow.com/questions/2634955/when-not-to-use-cassandra)
		* [Avoid Pitfalls in Scaling Cassandra Cluster at Walmart](https://medium.com/walmartlabs/avoid-pitfalls-in-scaling-your-cassandra-cluster-lessons-and-remedies-a71ca01f8c04)
		* [Storing Images in Cassandra at Walmart](https://medium.com/walmartlabs/building-object-store-storing-images-in-cassandra-walmart-scale-a6b9c02af593)
		* [Cassandra at Instagram](https://www.slideshare.net/DataStax/cassandra-at-instagram-2016)
		* [Scale Ad Analytics with Cassandra at Yelp](https://engineeringblog.yelp.com/2016/08/how-we-scaled-our-ad-analytics-with-cassandra.html)
		* [Store Billions of Messages with Cassandra at Discord](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7)
		* [Scale to 100+ Million Reads/Writes using Spark and Cassandra at Dream11](https://medium.com/dream11-tech-blog/leaderboard-dream11-4efc6f93c23e)		
		* [Moving Food Feed from Redis to Cassandra at Zomato](https://www.zomato.com/blog/how-we-moved-our-food-feed-from-redis-to-cassandra)
		* [Benchmarking Cassandra Scalability on AWS at Netflix](https://medium.com/netflix-techblog/benchmarking-cassandra-scalability-on-aws-over-a-million-writes-per-second-39f45f066c9e)
		* [Imgur Notification: From MySQL to HBASE at Imgur](https://blog.imgur.com/2015/09/15/tech-tuesday-imgur-notifications-from-mysql-to-hbase/)
		* [Improving HBase Backup Efficiency at Pinterest](https://medium.com/@Pinterest_Engineering/improving-hbase-backup-efficiency-at-pinterest-86159da4b954)
		* [ClickHouse - Open Source Distributed Column Database at Yandex](https://clickhouse.yandex/)
		* [Scaling Redshift without Scaling Costs at GIPHY](https://engineering.giphy.com/scaling-redshift-without-scaling-costs/)
	* [Document Databases (MongoDB, SimpleDB, CouchDB)](https://msdn.microsoft.com/en-us/magazine/hh547103.aspx)
		* [eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB](https://www.mongodb.com/blog/post/ebay-building-mission-critical-multi-data-center-applications-with-mongodb)
		* [MongoDB at Baidu: Multi-Tenant Cluster Storing 200+ Billion Documents across 160 Shards](https://www.mongodb.com/blog/post/mongodb-at-baidu-powering-100-apps-across-600-nodes-at-pb-scale)
		* [Migrating Mongo Data at Addepar](https://medium.com/build-addepar/migrating-mountains-of-mongo-data-63e530539952)
		* [The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)](https://medium.baqend.com/parse-is-gone-a-few-secrets-about-their-infrastructure-91b3ab2fcf71)
		* [Migrating Mountains of Mongo Data at Addepar](https://medium.com/build-addepar/migrating-mountains-of-mongo-data-63e530539952)
		* [Couchbase Ecosystem at LinkedIn](https://engineering.linkedin.com/blog/2017/12/couchbase-ecosystem-at-linkedin)
		* [SimpleDB at Zendesk](https://medium.com/zendesk-engineering/resurrecting-amazon-simpledb-9404034ec506)
	* [Graph Databases](https://www.ibm.com/developerworks/library/cl-graph-database-1/index.html)
		* [Handling Billions of Edges in a Graph Database](https://www.infoq.com/presentations/graph-database-scalability)		
		* [Neo4j case studies with Walmart, eBay, AirBnB, NASA, etc](https://neo4j.com/customers/)
		* [FlockDB: Distributed Graph Database for Storing Adjancency Lists at Twitter](https://blog.twitter.com/engineering/en_us/a/2010/introducing-flockdb.html)
		* [JanusGraph: Scalable Graph Database backed by Google, IBM and Hortonworks](https://architecht.io/google-ibm-back-new-open-source-graph-database-project-janusgraph-1d74fb78db6b)
		* [Amazon Neptune](https://aws.amazon.com/neptune/)
	* [Datastructure Databases (Redis, Hazelcast)](https://db-engines.com/en/system/Hazelcast%3BMemcached%3BRedis)
		* [Using Redis To Scale at Twitter](http://highscalability.com/blog/2014/9/8/how-twitter-uses-redis-to-scale-105tb-ram-39mm-qps-10000-ins.html)
		* [Scaling Job Queue with Redis at Slack](https://slack.engineering/scaling-slacks-job-queue-687222e9d100)
		* [Moving persistent data out of Redis at Github](https://githubengineering.com/moving-persistent-data-out-of-redis/)
		* [Storing Hundreds of Millions of Simple Key-Value Pairs in Redis at Instagram](https://engineering.instagram.com/storing-hundreds-of-millions-of-simple-key-value-pairs-in-redis-1091ae80f74c)
		* [Redis in Chat Architecture of Twitch (from 27:22)](https://www.infoq.com/presentations/twitch-pokemon)
		* [Learn Redis the hard way (in production) at Trivago](http://tech.trivago.com/2017/01/25/learn-redis-the-hard-way-in-production/)
		* [Optimizing Session Key Storage in Redis at Deliveroo](https://deliveroo.engineering/2016/10/07/optimising-session-key-storage.html)
		* [Optimizing Redis Storage at Deliveroo](https://deliveroo.engineering/2017/01/19/optimising-membership-queries.html)		
* [Time Series Database (TSDB)](https://www.influxdata.com/time-series-database/)
	* [What is Time-Series Data & Why We Need a Time-Series Database](https://blog.timescale.com/what-the-heck-is-time-series-data-and-why-do-i-need-a-time-series-database-dcf3b1b18563)
	* [Time Series Data: Why and How to Use a Relational Database instead of NoSQL](https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c)
	* [Beringei: High-performance Time Series Storage Engine at Facebook](https://code.facebook.com/posts/952820474848503/beringei-a-high-performance-time-series-storage-engine/)	
	* [Atlas: In-memory Dimensional Time Series Database at Netflix](https://medium.com/netflix-techblog/introducing-atlas-netflixs-primary-telemetry-platform-bd31f4d8ed9a)
	* [Heroic: Time Series Database at Spotify](https://labs.spotify.com/2015/11/17/monitoring-at-spotify-introducing-heroic/)
	* [Roshi: Distributed Storage System for Time-Series Event at SoundCloud](https://developers.soundcloud.com/blog/roshi-a-crdt-system-for-timestamped-events)
	* [Building a Scalable Time Series Database on PostgreSQL](https://blog.timescale.com/when-boring-is-awesome-building-a-scalable-time-series-database-on-postgresql-2900ea453ee2)
	* [Scaling Time Series Data Storage at Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-i-ec2b6d44ba39)
* [HTTP Caching (Reverse Proxy, CDN)](https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching)
	* [Reverse Proxy (Nginx, Varnish, Squid, rack-cache)](https://www.mertech.com/overview-reverse-proxying/)
	* [Stop Worrying and Love the Proxy](https://blog.turbinelabs.io/how-we-learned-to-stop-worrying-and-love-the-proxy-89af98fabaf8)
	* [Playing HTTP Tricks with Nginx](https://www.elastic.co/blog/playing-http-tricks-nginx)
	* [Using CDN to Improve Site Performance at Coursera](https://building.coursera.org/blog/2015/07/09/improving-coursera-global-site-performance-a-head-to-head-cdn-battle-with-production-traffic/)
	* [Strategy: Caching 404s Saved 66% On Server Time at The Onion](http://highscalability.com/blog/2010/3/26/strategy-caching-404s-saved-the-onion-66-on-server-time.html)
	* [Increasing Application Performance with HTTP Cache Headers](https://devcenter.heroku.com/articles/increasing-application-performance-with-http-cache-headers)
	* [Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga](https://www.zynga.com/blogs/engineering/zynga-geo-proxy-reducing-mobile-game-latency)
	* [Google AMP at Condé Nast](https://technology.condenast.com/story/the-why-and-how-of-google-amp-at-conde-nast)
	* [Running A/B Tests on Hosting Infrastructure (CDNs) at Deliveroo](https://deliveroo.engineering/2016/09/19/ab-testing-cdns.html)
	* [HAProxy with Kubernetes for User-facing Traffic at SoundCloud](https://developers.soundcloud.com/blog/how-soundcloud-uses-haproxy-with-kubernetes-for-user-facing-traffic)
	* [Bandaid: Service Proxy at Dropbox](https://blogs.dropbox.com/tech/2018/03/meet-bandaid-the-dropbox-service-proxy/)
	* [CDN in LIVE's Encoder Layer at LINE](https://engineering.linecorp.com/en/blog/detail/230)
* [Load Balancing](https://blog.vivekpanyam.com/scaling-a-web-service-load-balancing/)
	* [Introduction to Modern Network Load Balancing and Proxying](https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236)
	* [Load Balancing infrastructure to support more than 1.3 billion users at Facebook](https://www.usenix.org/conference/srecon15europe/program/presentation/shuff)
	* [DHCPLB: Open Source Load Balancer for DHCP at Facebook](https://code.facebook.com/posts/1734309626831603/dhcplb-an-open-source-load-balancer/)
	* [Load Balancing with Eureka at Netflix](https://medium.com/netflix-techblog/netflix-shares-cloud-load-balancing-and-failover-tool-eureka-c10647ef95e5)
	* [Load Balancing at Yelp](https://engineeringblog.yelp.com/2017/05/taking-zero-downtime-load-balancing-even-further.html)
	* [Load Balancing at Github](https://githubengineering.com/introducing-glb/)
	* [Consistent Hashing to Improve Load Balancing at Vimeo](https://medium.com/vimeo-engineering-blog/improving-load-balancing-with-a-new-consistent-hashing-algorithm-9f1bd75709ed)
	* [UDP Load Balancing at 500 pixel](https://developers.500px.com/udp-load-balancing-with-keepalived-167382d7ad08)
	* [QALM: QoS Load Management Framework at Uber](https://eng.uber.com/qalm/)	
* [Rate Limiting](https://www.keycdn.com/support/rate-limiting/)
	* [Rate Limiting for Scaling to Millions of Domains at Cloudfare](https://blog.cloudflare.com/counting-things-a-lot-of-different-things/)
	* [Cloud Bouncer: Distributed Rate Limiting at Yahoo](https://yahooeng.tumblr.com/post/111288877956/cloud-bouncer-distributed-rate-limiting-at-yahoo)
	* [Scaling API with Rate Limiters at Stripe](https://stripe.com/blog/rate-limiters)
	* [Rate Limiting at Etsy](https://www.sans.org/summit-archives/file/summit-archive-1509593697.pdf)
	* [Rate Limiter at BloomReach](http://engineering.bloomreach.com/qps-monitoring-throttling-system/)
	* [Distributed Rate Limiting at Allegro](https://allegro.tech/2017/04/hermes-max-rate.html)
	* [Ratequeue: Core Queueing-And-Rate-Limiting System at Twilio](https://www.twilio.com/blog/2017/11/chaos-engineering-ratequeue-ha.html)
* [Autoscaling](https://medium.com/@BotmetricHQ/top-11-hard-won-lessons-learned-about-aws-auto-scaling-5bfe56da755f)
	* [A Horror Movie Featuring Auto Scaling Groups, EBS Volumes, Terraform, and Bash](https://blog.gruntwork.io/yak-shaving-series-1-all-i-need-is-a-little-bit-of-disk-space-6e5ef1644f67)
	* [Autoscaling Pinterest](https://medium.com/@Pinterest_Engineering/auto-scaling-pinterest-df1d2beb4d64)
	* [Autoscaling Based on Request Queuing at Square](https://medium.com/square-corner-blog/autoscaling-based-on-request-queuing-c4c0f57f860f)
	* [Autoscaling Applications at PayPal](https://www.paypal-engineering.com/2017/08/16/autoscaling-applications-paypal/)
	* [Autoscaling Jenkins at Trivago](http://tech.trivago.com/2017/02/17/your-definite-guide-for-autoscaling-jenkins/)
	* [Scryer: Predictive Auto Scaling Engine at Netflix](https://medium.com/netflix-techblog/scryer-netflixs-predictive-auto-scaling-engine-a3f8fc922270)
* [Concurrency](http://joeduffyblog.com/2016/11/30/15-years-of-concurrency/)
	* [Message-Passing Concurrency](https://link.springer.com/chapter/10.1007/978-3-642-35170-9_11)
	* [Software Transactional Memory](https://dl.acm.org/citation.cfm?id=3037750)
	* [Dataflow Concurrency](http://www.marketwired.com/press-release/java-concurrency-and-scalability-platform-akka-celebrates-fifth-anniversary-1928674.htm)
	* [Shared-State Concurrency](https://common-lisp.net/project/ssc/darcs/spec/specification.pdf)
	* [Concurrency series by Larry Osterman (Principal SDE at Microsoft)](https://social.msdn.microsoft.com/Profile/Larry%2bOsterman%2b%5BMSFT%5D/activity)
		* [Part 8 – Concurrency for scalability](https://blogs.msdn.microsoft.com/larryosterman/2005/02/28/concurrency-part-8-concurrency-for-scalability/)
		* [Part 9 - APIs that enable scalable programming](https://blogs.msdn.microsoft.com/larryosterman/2005/03/02/concurrency-part-9-apis-that-enable-scalable-programming/)
		* [Part 10 - How do you know if you’ve got a scalability issue?](https://blogs.msdn.microsoft.com/larryosterman/2005/03/03/concurrency-part-10-how-do-you-know-if-youve-got-a-scalability-issue/)
		* [Part 11 – Hidden scalability issues](https://blogs.msdn.microsoft.com/larryosterman/2005/03/04/concurrency-part-11-hidden-scalability-issues/)
		* [Part 12 – Hidden scalability issues (cont)](https://blogs.msdn.microsoft.com/larryosterman/2005/03/07/concurrency-part-12-hidden-scalability-issues-part-2/)
	* [Concurrency with Erlang](http://learnyousomeerlang.com/the-hitchhikers-guide-to-concurrency)
		* [Erlang in WhatsApp](https://blog.whatsapp.com/196/1-million-is-so-2011)
		* [Erlang in Riot Chat Server](https://engineering.riotgames.com/news/chat-service-architecture-servers)
		* [How Discord Scaled Elixir to Five Millions Concurrent Users](https://blog.discordapp.com/scaling-elixir-f9b8e1e7c29b)
		* [Mnesia: A Distributed DBMS Rooted in Concurrency](https://www.developer.com/db/article.php/3864331/Mnesia-A-Distributed-DBMS-Rooted-in-Concurrency.htm)
		* [Mesia and CAP](https://medium.com/@jlouis666/mnesia-and-cap-d2673a92850)		
	* [Running Concurrent Queries in GoSocial (Go and Neo4j) at Medium](https://medium.engineering/running-concurrent-queries-in-gosocial-28e5841b05b5)
	* [The Secret To 10 Million Concurrent Connections](http://highscalability.com/blog/2013/5/13/the-secret-to-10-million-concurrent-connections-the-kernel-i.html)
* [Parallel Computing](https://blogs.msdn.microsoft.com/ddperf/2009/05/02/are-we-taking-advantage-of-parallelism/)
	* [SPMD (Single Program Multiple Data): The Genetic Pattern](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-186.html)
	* [Master/Worker Pattern](https://docs.gigaspaces.com/sbp/master-worker-pattern.html)
	* [Loop Parallelism Pattern: Extracting parallel tasks from loops](https://www.cs.umd.edu/class/fall2001/cmsc411/projects/unroll/main.htm)
	* [Fork/Join Pattern: Good for recursive data processing](http://highscalability.com/learn-how-exploit-multiple-cores-better-performance-and-scalability)
	* [Map-Reduce: Born for Simplified Data Processing on Large Clusters](http://static.googleusercontent.com/media/research.google.com/en/us/archive/mapreduce-osdi04.pdf)
	* [On the Death of Map-Reduce - Henry Robinson, Cloudera](http://the-paper-trail.org/blog/the-elephant-was-a-trojan-horse-on-the-death-of-map-reduce-at-google/)
	* [Server-side Optimization to Parallelize the Rendering of Web Pages at Yelp](https://engineeringblog.yelp.com/2017/07/generating-web-pages-in-parallel-with-pagelets.html)
	* [Accelerator: Data Processing Framework with Fast Data Access and Parallel Execution at eBay](https://www.ebayinc.com/stories/blogs/tech/announcing-the-accelerator-processing-1-000-000-000-lines-per-second-on-a-single-computer/)
* [Event-Driven Architecture](https://martinfowler.com/articles/201701-event-driven.html)
	* [Pub-Sub Messaging](https://aws.amazon.com/pub-sub-messaging/)
		* [Autoscaling Pub-Sub Consumers at Spotify](https://labs.spotify.com/2017/11/20/autoscaling-pub-sub-consumers/)
		* [Pulsar: Pub-Sub Messaging at Scale at Yahoo](https://yahooeng.tumblr.com/post/150078336821/open-sourcing-pulsar-pub-sub-messaging-at-scale)
		* [Wormhole: Pub-Sub system at Facebook (2013)](https://code.facebook.com/posts/188966771280871/wormhole-pub-sub-system-moving-data-through-space-and-time/)
		* [Pub-Sub in Chatting Architecture at LINE](https://engineering.linecorp.com/en/blog/detail/85)
	* [Domain Events](https://martinfowler.com/eaaDev/DomainEvent.html)
		* [Domain Events: Simple and Reliable Solution](http://enterprisecraftsmanship.com/2017/10/03/domain-events-simple-and-reliable-solution/)
		* [Domain-Driven Design in Organizing Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0)
		* [Modelling for Domain Driven Design at Moonpig](https://engineering.moonpig.com/development/modelling-for-domain-driven-design)
	* [Event Sourcing](https://martinfowler.com/eaaDev/EventSourcing.html)
		* [Event Sourced Architectures for High Availability](https://www.infoq.com/presentations/Event-Sourced-Architectures-for-High-Availability)
		* [Event Sourcing and Stream Processing at Scale](https://martin.kleppmann.com/2016/01/29/event-sourcing-stream-processing-at-ddd-europe.html)
		* [Scaling Event Sourcing for Netflix Downloads](https://www.infoq.com/presentations/netflix-scale-event-sourcing)
		* [Scaling Event-Sourcing at Jet.com](https://medium.com/@eulerfx/scaling-event-sourcing-at-jet-9c873cac33b8)
	* [Command & Query Responsibility Segregation (CQRS)](https://docs.microsoft.com/en-us/azure/architecture/patterns/cqrs)
		* [Exploring CQRS and Event Sourcing - MSDN (with free ebook)](https://msdn.microsoft.com/en-us/library/jj554200.aspx)
		* [CQRS Simple Architecture](https://www.future-processing.pl/blog/cqrs-simple-architecture/)
		* [Building Scalable Applications Using Event Sourcing and CQRS with Kafka](https://initiate.andela.com/event-sourcing-and-cqrs-a-look-at-kafka-e0c1b90d17d8)
	* [Stream Processing, Event Sourcing, Reactive, CEP, etc - Martin Kleppmann](https://www.confluent.io/blog/making-sense-of-stream-processing/)
		* [Point-To-Point and Its Differences from Pub-Sub](https://www.journaldev.com/9743/jms-messaging-models)
		* [Store-Forward](https://docs.oracle.com/cd/E13222_01/wls/docs91/saf_admin/overview.html)
		* [Request-Reply](https://docs.tibco.com/pub/ftl/4.3.0/doc/html/GUID-A64ABED1-682E-4E1D-A94A-5590CB91B9BB.html)
		* [Enterprise Service Bus](http://www.oracle.com/technetwork/articles/soa/ind-soa-esb-1967705.html)		
* [Distributed Source Code and Configuration Files Management](https://betterexplained.com/articles/intro-to-distributed-version-control-illustrated/)
	* [Distributed Version Control Systems: A Not-So-Quick Guide Through](https://www.infoq.com/articles/dvcs-guide)
	* [Stemma: Distributed Git Server at Palantir](https://medium.com/@palantir/stemma-distributed-git-server-70afbca0fc29)
	* [Configuration Management for Distributed Systems at Flickr](https://code.flickr.net/2016/03/24/configuration-management-for-distributed-systems-using-github-and-cfg4j/)
	* [Git Repo at Microsoft - The Largest Git Repo on The Planet](https://blogs.msdn.microsoft.com/bharry/2017/05/24/the-largest-git-repo-on-the-planet/)
	* [How Microsoft Solved Git’s Problem with Large Repositories](https://www.infoq.com/news/2017/02/GVFS)		
	* [Scaling Infrastructure and (Git) Workflow at Adyen](https://medium.com/adyen/from-0-100-billion-scaling-infrastructure-and-workflow-at-adyen-7b63b690dfb6)	

## Availability
* [Failover](http://cloudpatterns.org/mechanisms/failover_system)
	* [The Evolution of Global Traffic Routing and Failover](https://www.usenix.org/conference/srecon16/program/presentation/heady)
	* [Testing for Disaster Recovery Failover Testing](https://www.usenix.org/conference/srecon17asia/program/presentation/liu_zehua)
	* [Designing a Microservices Architecture for Failure](https://blog.risingstack.com/designing-microservices-architecture-for-failure/)
* [Resilience Engineering: Learning to Embrace Failure](https://queue.acm.org/detail.cfm?id=2371297)	
	* [Resilience Engineering with Project Waterbear at LinkedIn](https://engineering.linkedin.com/blog/2017/11/resilience-engineering-at-linkedin-with-project-waterbear)
	* [Resiliency against Traffic Oversaturation at iHeartRadio](https://tech.iheart.com/resiliency-against-traffic-oversaturation-77c5ed92a5fb)
	* [Resiliency in Distributed Systems at GO-JEK](https://blog.gojekengineering.com/resiliency-in-distributed-systems-efd30f74baf4)
	* [Practical NoSQL Resilience Design Pattern for the Enterprise at eBay](https://www.ebayinc.com/stories/blogs/tech/practical-nosql-resilience-design-pattern-for-the-enterprise/)
	* [Ensuring Resilience to Disaster at Quora](https://engineering.quora.com/Ensuring-Quoras-Resilience-to-Disaster)
	* [Resilience at Shopify](https://scaleyourcode.com/blog/article/23)
	* [Site Resiliency at Expedia](https://www.infoq.com/presentations/expedia-website-resiliency?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study)
* [Availability in Globally Distributed Storage Systems](http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36737.pdf)	
* [NodeJS High Availability at Yahoo](https://yahooeng.tumblr.com/post/68823943185/nodejs-high-availability)
* [Every Day Is Monday in Operations (11 parts) at LinkedIn ](https://www.linkedin.com/pulse/introduction-every-day-monday-operations-benjamin-purgason)
* [Practical Guide to Monitoring and Alerting with Time Series at Scale](https://www.usenix.org/conference/srecon17americas/program/presentation/wilkinson)
* [How Robust Monitoring Powers High Availability for LinkedIn Feed](https://www.usenix.org/conference/srecon17americas/program/presentation/barot)
* [Architectural Patterns for High Availability - Adrian Cockcroft, Director of Architecture at Netflix](https://www.infoq.com/presentations/Netflix-Architecture)
* [Supporting Global Events at Facebook](https://code.facebook.com/posts/166966743929963/how-production-engineers-support-global-events-on-facebook/)
* [Backends High Availability at BlaBlaCar](https://medium.com/blablacar-tech/the-expendables-backends-high-availability-at-blablacar-8cea3b95b26b)
* [Chubby: Lock Service for Loosely Coupled Distributed Systems at Google](https://blog.acolyer.org/2015/02/13/the-chubby-lock-service-for-loosely-coupled-distributed-systems/)
* [Tips for High Availability at Netflix](https://medium.com/@NetflixTechBlog/tips-for-high-availability-be0472f2599c)
* [Scaling High-Availability Infrastructure in the Cloud at Twilio](https://www.twilio.com/engineering/2011/12/12/scaling-high-availablity-infrastructure-in-cloud)

## Stability
* [Circuit Breaker](https://martinfowler.com/bliki/CircuitBreaker.html)
	* [Circuit Breaking in Distributed Systems](https://www.infoq.com/presentations/circuit-breaking-distributed-systems)
	* [Circuit Breakers for Distributed Services at LINE](https://engineering.linecorp.com/en/blog/detail/76)
	* [Applying Circuit Breaker to Channel Gateway at LINE](https://engineering.linecorp.com/en/blog/detail/78)
	* [Lessons in Resilience at SoundCloud](https://developers.soundcloud.com/blog/lessons-in-resilience-at-SoundCloud)
	* [Circuit Breaker for Scaling Containers](https://f5.com/about-us/blog/articles/the-art-of-scaling-containers-circuit-breakers-28919)
	* [Protector: Circuit Breaker for Time Series Databases at Trivago](http://tech.trivago.com/2016/02/23/protector/)
	* [Improved Production Stability with Circuit Breakers at Heroku](https://blog.heroku.com/improved-production-stability-with-circuit-breakers)
* [Always use timeouts (if possible)](https://www.javaworld.com/article/2824163/application-performance/stability-patterns-applied-in-a-restful-architecture.html)
* [Let it Crash/Supervisors: Embrace Failure As Natural State](http://erlang.org/doc/design_principles/sup_princ.html)
* [Crash Early: Better Error Now Than Response Tomorrow](http://odino.org/better-performance-the-case-for-timeouts/)
* [Crash-safe Replication for MySQL at Booking.com](https://medium.com/booking-com-infrastructure/better-crash-safe-replication-for-mysql-a336a69b317f)
* [Bulkheads: Partition and Tolerate Failure in One Part](https://skife.org/architecture/fault-tolerance/2009/12/31/bulkheads.html)
* [Steady State: Always Put Logs on Separate Disk](https://docs.microsoft.com/en-us/sql/relational-databases/policy-based-management/place-data-and-log-files-on-separate-drives)
* [Throttling: Maintain a Steady Pace](http://www.sosp.org/2001/papers/welsh.pdf)
* [Multi-Clustering: Improving Resiliency and Stability of a Large-scale Monolithic API Service at LinkedIn](https://engineering.linkedin.com/blog/2017/11/improving-resiliency-and-stability-of-a-large-scale-api)

## Performance
* [Performance Optimization on Operating Systems, Databases, Network](https://stackify.com/application-performance-metrics/)
	* [Improving Performance with Background Data Prefetching at Instagram](https://engineering.instagram.com/improving-performance-with-background-data-prefetching-b191acb39898)
	* [Compression Techniques to Solve Network I/O Bottlenecks at eBay](https://www.ebayinc.com/stories/blogs/tech/how-ebays-shopping-cart-used-compression-techniques-to-solve-network-io-bottlenecks/)
	* [Optimizing Web Servers for High Throughput and Low Latency at Dropbox](https://blogs.dropbox.com/tech/2017/09/optimizing-web-servers-for-high-throughput-and-low-latency/)
	* [Boosting Site Speed Using Brotli Compression at LinkedIn](https://engineering.linkedin.com/blog/2017/05/boosting-site-speed-using-brotli-compression)
	* [Linux Performance Analysis in 60.000 Milliseconds at Netflix](https://medium.com/netflix-techblog/linux-performance-analysis-in-60-000-milliseconds-accc10403c55)
	* [Performance Testing with SSDs (2 parts) at MailChimp](https://devs.mailchimp.com/blog/performance-testing-with-ssds-pt-2/)
	* [Decreasing RAM Usage by 40% Using jemalloc with Python & Celery at Zapier](https://zapier.com/engineering/celery-python-jemalloc/)
	* [Reducing Memory Footprint at Slack](https://slack.engineering/reducing-slacks-memory-footprint-4480fec7e8eb)
	* [Using Java Large Heap (110 GB) for Boosting Site Perpormance at Expedia](https://techblog.expedia.com/2015/09/25/solving-problems-with-very-large-java-heaps/)
	* [Optimizing JVM at Alibaba](https://www.youtube.com/watch?v=X4tmr3nhZRg)
	* [Python Garbage Collection for Dropping 50% Memory Growth Per Request at Instagram](https://instagram-engineering.com/copy-on-write-friendly-python-garbage-collection-ad6ed5233ddf)
	* [Performance Improvements at Pinterest](https://medium.com/@Pinterest_Engineering/driving-user-growth-with-performance-improvements-cfc50dafadd7)
	* [Server Side Rendering at Wix](https://www.youtube.com/watch?v=f9xI2jR71Ms)
	* [30x Performance Improvements on MySQLStreamer at Yelp](https://engineeringblog.yelp.com/2018/02/making-30x-performance-improvements-on-yelps-mysqlstreamer.html)
	* [Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix](https://medium.com/netflix-techblog/optimizing-the-netflix-api-5c9ac715cf19)
	* [Performance Monitoring with Riemann and Clojure at Walmart](https://medium.com/walmartlabs/performance-monitoring-with-riemann-and-clojure-eafc07fcd375)
	* [Performance Tracking Dashboard for Live Games at Zynga](https://www.zynga.com/blogs/engineering/live-games-have-evolving-performance)
	* [Optimizing CAL Report Hadoop MapReduce Jobs at eBay](https://www.ebayinc.com/stories/blogs/tech/optimization-of-cal-report-hadoop-mapreduce-job/)
	* [Performance Tuning on Quartz Scheduler at eBay](https://www.ebayinc.com/stories/blogs/tech/performance-tuning-on-quartz-scheduler/)
* [Performance Optimization on Video, Image, Page Load](https://developers.google.com/web/fundamentals/performance/why-performance-matters/)
	* [Optimizing 360 Photos at Scale at Facebook](https://code.facebook.com/posts/129055711052260/optimizing-360-photos-at-scale/)
	* [Reducing Image File Size in the Photos Infrastructure at Etsy](https://codeascraft.com/2017/05/30/reducing-image-file-size-at-etsy/)
	* [Improving GIF Performance at Pinterest](https://medium.com/@Pinterest_Engineering/improving-gif-performance-on-pinterest-8dad74bf92f1)
	* [Optimizing Video Playback Performance at Pinterest](https://medium.com/@Pinterest_Engineering/optimizing-video-playback-performance-caf55ce310d1)
	* [Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix](https://medium.com/netflix-techblog/optimized-shot-based-encodes-now-streaming-4b9464204830)
	* [Reducing Video Loading Time by Prefetching during Preroll at Dailymotion](http://engineering.dailymotion.com/reducing-video-loading-time-prefetching-video-during-preroll/)
	* [Improving Homepage Performance at Zillow](https://www.zillow.com/engineering/improving-homepage-performance/)
	* [The Process of Optimizing for Client Performance at Expedia](https://techblog.expedia.com/2018/03/09/go-fast-or-go-home-the-process-of-optimizing-for-client-performance/)

## Intelligence
* [Big Data](https://insights.sei.cmu.edu/sei_blog/2017/05/reference-architectures-for-big-data-systems.html)		
	* [Data Platform at Netflix](https://www.youtube.com/watch?v=CSDIThSwA7s)
	* [Data Platform at Flipkart](https://tech.flipkart.com/overview-of-flipkart-data-platform-20c6d3e9a196)
	* [Data Infrastructure at Airbnb](https://medium.com/airbnb-engineering/data-infrastructure-at-airbnb-8adfb34f169c)
	* [Data Infrastructure at LinkedIn](https://www.infoq.com/presentations/big-data-infrastructure-linkedin)
	* [Data Infrastructure at GO-JEK](https://blog.gojekengineering.com/data-infrastructure-at-go-jek-cd4dc8cbd929)
	* [Data Ingestion Infrastructure at Pinterest](https://medium.com/@Pinterest_Engineering/scalable-and-reliable-data-ingestion-at-pinterest-b921c2ee8754)
	* [Data Analytics Architecture at Pinterest](https://medium.com/@Pinterest_Engineering/behind-the-pins-building-analytics-f7b508cdacab)
	* [Big Data Processing (2 parts) at Spotify](https://labs.spotify.com/2017/10/23/big-data-processing-at-spotify-the-road-to-scio-part-2/)
	* [Big Data Processing at Uber](https://cdn.oreillystatic.com/en/assets/1/event/160/Big%20data%20processing%20with%20Hadoop%20and%20Spark%2C%20the%20Uber%20way%20Presentation.pdf)
	* [Analytics Pipeline at Lyft](https://cdn.oreillystatic.com/en/assets/1/event/269/Lyft_s%20analytics%20pipeline_%20From%20Redshift%20to%20Apache%20Hive%20and%20Presto%20Presentation.pdf)
	* [Big Data Analytics and ML Techniques at LinkedIn](https://cdn.oreillystatic.com/en/assets/1/event/269/Big%20data%20analytics%20and%20machine%20learning%20techniques%20to%20drive%20and%20grow%20business%20Presentation%201.pdf)
	* [Self-Serve Reporting Platform on Hadoop at LinkedIn](https://cdn.oreillystatic.com/en/assets/1/event/137/Building%20a%20self-serve%20real-time%20reporting%20platform%20at%20LinkedIn%20Presentation%201.pdf)
	* [RBEA: Real-time Analytics Platform at King](https://techblog.king.com/rbea-scalable-real-time-analytics-king/)
	* [Gimel: Analytics Data Processing Platform at PayPal](https://www.paypal-engineering.com/2018/04/17/gimel/)
	* [AthenaX: Streaming Analytics Platform at Uber](https://eng.uber.com/athenax/)
	* [TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/157196488076/open-sourcing-tensorflowonspark-distributed-deep)
	* [CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo](https://yahooeng.tumblr.com/post/139916828451/caffeonspark-open-sourced-for-distributed-deep)
	* [Scaling Experimentation Platform at Airbnb](https://medium.com/airbnb-engineering/https-medium-com-jonathan-parks-scaling-erf-23fd17c91166)
	* [Log Analysis Platform at LINE](https://www.slideshare.net/wyukawa/strata2017-sg)
* [Distributed Machine Learning](https://www.csie.ntu.edu.tw/~cjlin/talks/bigdata-bilbao.pdf)
	* [AIOps in Practice at Baidu](https://www.usenix.org/conference/srecon17asia/program/presentation/qu)
	* [Scalable Deep Learning Platform on Spark at Baidu](https://www.slideshare.net/JenAman/scalable-deep-learning-platform-on-spark-in-baidu)
	* [Michelangelo: Machine Learning Platform at Uber](https://eng.uber.com/michelangelo/)
	* [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/)
	* [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/)	
	* [Repo-Topix: Topic Extraction Framework at Github](https://githubengineering.com/topics/)
	* [Scaling Gradient Boosted Trees for Click-Through-Rate Prediction at Yelp](https://engineeringblog.yelp.com/2018/01/building-a-distributed-ml-pipeline-part1.html)	
	* [Learning with Privacy at Scale at Apple](https://machinelearning.apple.com/2017/12/06/learning-with-privacy-at-scale.html)
	* [Deep Learning for Image Classification Experiment at Mercari](https://medium.com/mercari-engineering/mercaris-image-classification-experiment-using-deep-learning-9b4e994a18ec)
	* [Deep Learning for Frame Detection in Product Images at Allegro](https://allegro.tech/2016/12/deep-learning-for-frame-detection.html)
	* [Content-based Video Relevance Prediction at Hulu](https://medium.com/hulu-tech-blog/content-based-video-relevance-prediction-b2c448e14752)
	* [Training ML Models with Airflow and BigQuery at WePay](https://wecode.wepay.com/posts/training-machine-learning-models-with-airflow-and-bigquery)
	* [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/)
	* [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection)
	* [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/)
	* [Venue Rating System at Foursquare](https://engineering.foursquare.com/finding-the-perfect-10-how-we-developed-the-foursquare-venue-rating-system-c76b08f7b9b3)
	* [Using Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f)
	* [Box Graph: Spontaneous Social Network at Box](https://blog.box.com/blog/box-graph-how-we-built-spontaneous-social-network/)
	* [Improving Video Thumbnails with Deep Neural Nets at YouTube](https://youtube-eng.googleblog.com/2015/10/improving-youtube-video-thumbnails-with_8.html)
	* [Quantile Regression for Delivering On Time at Instacart](https://tech.instacart.com/how-instacart-delivers-on-time-using-quantile-regression-2383e2e03edb)
	* [Cross-Lingual End-to-End Product Search with Deep Learning at Zalando](https://jobs.zalando.com/tech/blog/search-deep-neural-network/)
	* [PricingNet: Pricing Modelling with Neural Networks at Skyscanner](https://hackernoon.com/pricingnet-modelling-the-global-airline-industry-with-neural-networks-833844d20ea6)
	* [Machine Learning at Jane Street](https://blog.janestreet.com/real-world-machine-learning-part-1/)
	* [Machine Learning for Ranking Answers End-to-End at Quora](https://engineering.quora.com/A-Machine-Learning-Approach-to-Ranking-Answers-on-Quora)
	* [Clustering Similar Stories Using LDA at Flipboard](http://engineering.flipboard.com/2017/02/storyclustering)
	* [Similarity Search at Flickr](https://code.flickr.net/2017/03/07/introducing-similarity-search-at-flickr/)
	* [Large-Scale Machine Learning Pipeline for Job Recommendations at Indeed](http://engineering.indeedblog.com/blog/2016/04/building-a-large-scale-machine-learning-pipeline-for-job-recommendations/)
	* [Deep Learning from Prototype to Production at Taboola](http://engineering.taboola.com/deep-learning-from-prototype-to-production/)
	* [Atom Smashing using Machine Learning at CERN](https://cdn.oreillystatic.com/en/assets/1/event/144/Atom%20smashing%20using%20machine%20learning%20at%20CERN%20Presentation.pdf)

## Architectures
* [Tech Stack (2 parts) at Uber](https://eng.uber.com/tech-stack-part-two/)
* [API Platform at Riot Games](https://engineering.riotgames.com/news/riot-games-api-deep-dive)
* [Back-end (Multi-tier Service Oriented Architecture) at LinkedIn](https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin)
* [Back-end at Flickr](https://yahooeng.tumblr.com/post/157200523046/introducing-tripod-flickrs-backend-refactored)
* [Back-end at BlaBlaCar](http://blablatech.com/blog/BlaBlaTech-behind-the-scene)
* [Stack Overflow Enterprise at Palantir](https://medium.com/@palantir/terraforming-stack-overflow-enterprise-in-aws-47ee431e6be7)
* [Distributed Cron at Quora](https://engineering.quora.com/Quoras-Distributed-Cron-Architecture)
* [Real-Time Presence Platform at LinkedIn](https://engineering.linkedin.com/blog/2018/01/now-you-see-me--now-you-dont--linkedins-real-time-presence-platf)
* [Simone: Distributed Simulation Service at Netflix](https://medium.com/netflix-techblog/https-medium-com-netflix-techblog-simone-a-distributed-simulation-service-b2c85131ca1b)
* [Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp](https://engineeringblog.yelp.com/2017/04/how-yelp-runs-millions-of-tests-every-day.html)
* [MySQL Realtime Traffic Emulator at KakaoTalk](http://tech.kakao.com/2016/02/16/opensource-2-mtre/)
* [Data Visualisation Platform at Myntra](https://medium.com/myntra-engineering/universal-dashboarding-platform-udp-data-visualisation-platform-at-myntra-5f2522fcf72d)
* [Architectures of Finance and Banking Systems](https://www.sesameindia.com/images/core-banking-system-architecture)
	* [Reference Architecture For The Open Banking Standard](https://hortonworks.com/blog/reference-architecture-open-banking-standard/)
	* [Building a Modern Bank Backend at Monzo](https://monzo.com/blog/2016/09/19/building-a-modern-bank-backend/)
	* [Choosing an Architecture for Core Banking System at TrustBK](https://blog.trustbk.com/choosing-an-architecture-85750e1e5a03)
	* [Reinventing the Trading Platform for Scale at Wealthsimple](https://medium.com/@Wealthsimple/engineering-at-wealthsimple-reinventing-our-trading-platform-for-scale-17e332241b6c)
	* [Tech Stack at TransferWise](http://tech.transferwise.com/the-transferwise-stack-heartbeat-of-our-little-revolution/)

## Ad-hoc
* [Systems We Make (Academic Papers)](https://systemswemake.com/)
* [Criteria for Selecting a Cloud Provider at Etsy](https://codeascraft.com/2018/01/04/selecting-a-cloud-provider/)
* [Saving One Million Dollars Annually by DynamoDB Hot Shards, Service Auto-scaling, etc at Segment](https://segment.com/blog/the-million-dollar-eng-problem/)
* [Basic Infrastructure Patterns at Zenefits](https://engineering.zenefits.com/2016/02/basic-infrastructure-patterns/)
* [Syscall Auditing at Scale at Slack](https://slack.engineering/syscall-auditing-at-scale-e6a3ca8ac1b8)
* [Service Decomposition at Scale at Intuit QuickBooks](https://quickbooks-engineering.intuit.com/service-decomposition-at-scale-70405ac2f637)
* [Scalable Gaming Patterns on AWS](https://d0.awsstatic.com/whitepapers/aws-scalable-gaming-patterns.pdf)
* [Scaling Chat To 70 Million Players at League Of Legends](http://highscalability.com/blog/2014/10/13/how-league-of-legends-scaled-chat-to-70-million-players-it-t.html)
* [Scaling Online Migrations at Stripe](https://stripe.com/blog/online-migrations)
* [Scaling NodeJS at Alibaba](https://www.linux.com/blog/can-nodejs-scale-ask-team-alibaba)
* [Horizontal Scalability in Web Serving Tier of Airbnb](https://medium.com/airbnb-engineering/unlocking-horizontal-scalability-in-our-web-serving-tier-d907449cdbcf)

## Interview
* [Designing Large-Scale Systems](https://www.somethingsimilar.com/2013/01/14/notes-on-distributed-systems-for-young-bloods/)
	* [My Scaling Hero - Jeff Atwood (a dose of Endorphins before your interview, JK)](https://blog.codinghorror.com/my-scaling-hero/)
	* [Software Engineering Advice from Building Large-Scale Distributed Systems - Jeff Dean](https://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf)
	* [Introduction to Architecting Systems for Scale](https://lethain.com/introduction-to-architecting-systems-for-scale/)
	* [Anatomy of a System Design Interview](https://hackernoon.com/anatomy-of-a-system-design-interview-4cb57d75a53f)
	* [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
	* [Top 10 System Design Interview Questions ](https://hackernoon.com/top-10-system-design-interview-questions-for-software-engineers-8561290f0444)
	* [Top 10 Common Large-Scale Software Architectural Patterns in a Nutshell](https://towardsdatascience.com/10-common-software-architectural-patterns-in-a-nutshell-a0b47a1e9013)
	* [How NOT to design Netflix in your 45-minute System Design Interview?](https://hackernoon.com/how-not-to-design-netflix-in-your-45-minute-system-design-interview-64953391a054)
* [Explaining Low-Level Systems (OS, Network/Protocol, Storage, etc)](https://www.palantir.com/how-to-ace-a-systems-design-interview/)	
	* [OSI and TCP/IP Cheat Sheet (Short but Sweet)](http://jaredheinrichs.com/mastering-the-osi-tcpip-models.html)
	* [The Precise Meaning of I/O Wait Time in Linux](http://veithen.github.io/2013/11/18/iowait-linux.html)
	* [Paxos Made Live – An Engineering Perspective](https://research.google.com/archive/paxos_made_live.html)
	* [How to do Distributed Locking](https://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html)
* ["What Happens When..." Questions](https://www.glassdoor.com/Interview/What-happens-when-you-type-www-google-com-in-your-browser-QTN_56396.htm)
	* [What Happens When You Type google.com into Browser and Press Enter?](https://github.com/alex/what-happens-when)
	* [Netflix: What Happens When You Press Play?](http://highscalability.com/blog/2017/12/11/netflix-what-happens-when-you-press-play.html)
	* [Transit and Peering: How Your Requests Reach GitHub](https://githubengineering.com/transit-and-peering-how-your-requests-reach-github/)
	* [How Expedia Finds your Flights: A Detailed View](https://techblog.expedia.com/2016/03/07/how-expedia-finds-flights-a-detailed-view/)

## Talks
* [Distributed Systems in One Lesson - Tim Berglund, Senior Director of Developer Experience at Confluent](https://www.youtube.com/watch?v=Y6Ev8GIlbxc)
* [Building Real Time Infrastructure at Facebook - Jeff Barber and Shie Erlich, Software Engineer at Facebook](https://www.usenix.org/conference/srecon17americas/program/presentation/erlich)
* [Building Reliable Social Infrastructure for Google - Marc Alvidrez, Senior Manager at Google](https://www.usenix.org/conference/srecon16/program/presentation/alvidrez)
* [Building a Distributed Build System at Google Scale - Aysylu Greenberg, SDE at Google](https://www.youtube.com/watch?v=K8YuavUy6Qc)
* [Site Reliability Engineering at Dropbox - Tammy Butow, Site Reliability Engineering Manager at Dropbox](https://www.youtube.com/watch?v=ggizCjUCCqE)
* [How Google Does Planet-Scale for Planet-Scale Infra - Melissa Binde, SRE Director for Google Cloud Platform](https://www.youtube.com/watch?v=H4vMcD7zKM0)
* [Netflix Guide to Microservices - Josh Evans, Director of Operations Engineering at Netflix](https://www.youtube.com/watch?v=CZ3wIuvmHeM&t=2837s)
* [Achieving Rapid Response Times in Large Online Services - Jeff Dean, Google Senior Fellow](https://www.youtube.com/watch?v=1-3Ahy7Fxsc)
* [Architecture to Handle 80K RPS Celebrity Sales at Shopify - Simon Eskildsen, Engineering Lead at Shopify](https://www.youtube.com/watch?v=N8NWDHgWA28)
* [Lessons of Scale at Facebook - Bobby Johnson, Director of Engineering at Facebook](https://www.youtube.com/watch?v=QCHiNEw73AU)
* [Performance Optimization for the Greater China Region at Salesforce - Jeff Cheng, Enterprise Architect at Salesforce](https://www.salesforce.com/video/1757880/)
* [How GIPHY Delivers a GIF to 300 Millions Users - Alex Hoang and Nima Khoshini, Services Engineers at GIPHY](https://vimeo.com/252367076)
* [High Performance Packet Processing Platform at Alibaba - Haiyong Wang, Senior Director at Alibaba](https://www.youtube.com/watch?v=wzsxJqeVIhY&list=PLMu8-hpCxIVENuAue7bd0eCAglLGY_8AW&index=7)
* [Solving Large-scale Data Center and Cloud Interconnection Problems -  Ihab Tarazi, CTO at Equinix](https://atscaleconference.com/videos/solving-large-scale-data-center-and-cloud-interconnection-problems/)
* [Scaling Dropbox - Kevin Modzelewski, Back-end Engineer at Dropbox](https://www.youtube.com/watch?v=PE4gwstWhmc)
* [Scaling Reliability at Dropbox - Sat Kriya Khalsa, SRE at Dropbox](https://www.youtube.com/watch?v=IhGWOaD5BYQ)
* [Scaling with Performance at Facebook - Bill Jia, VP of Infrastructure at Facebook](https://atscaleconference.com/videos/performance-scale-2018-opening-remarks/)
* [Scaling Live Videos to a Billion Users at Facebook - Sachin Kulkarni, Director of Engineering at Facebook](https://www.youtube.com/watch?v=IO4teCbHvZw)
* [Scaling Low-latency Live Streams at Facebook (Latencies for Real-time Interactions) - Saral Shodhan, SDE at Facebook](https://atscaleconference.com/videos/scaling-low-latency-live-streams/)
* [Scaling Low-latency Live Streams at Facebook (End-to-End Considerations) - Federico Larumbe, SDE at Facebook](https://atscaleconference.com/videos/scaling-low-latency-live-streams-2-of-2/)
* [Scaling Infrastructure at Instagram - Lisa Guo, Instagram Engineering](https://www.youtube.com/watch?v=hnpzNAPiC0E)
* [Scaling Infrastructure at Twitter - Yao Yue, Staff Software Engineer at Twitter](https://www.youtube.com/watch?v=6OvrFkLSoZ0)
* [Scaling Infrastructure at Etsy - Bethany Macri, Engineering Manager at Etsy](https://www.youtube.com/watch?v=LfqyhM1LeIU)
* [Scaling Real-time Infrastructure at Alibaba for Global Shopping Holiday - Xiaowei Jiang, Senior Director at Alibaba](https://atscaleconference.com/videos/scaling-alibabas-real-time-infrastructure-for-global-shopping-holiday/)
* [Scaling Data Infrastructure at Spotify - Matti (Lepistö) Pehrs, Spotify](https://www.youtube.com/watch?v=cdsfRXr9pJU)
* [Scaling Pinterest - Marty Weiner, Pinterest’s founding engineer](https://www.youtube.com/watch?v=jQNCuD_hxdQ&list=RDhnpzNAPiC0E&index=11)
* [Scaling Slack - Bing Wei, Software Engineer (Infrastructure) at Slack](https://www.infoq.com/presentations/slack-scalability)
* [Scaling Backend at Youtube - Sugu Sougoumarane, SDE at Youtube](https://www.youtube.com/watch?v=5yDO-tmIoXY&feature=youtu.be)
* [Scaling Backend at Uber - Matt Ranney, Chief Systems Architect at Uber](https://www.youtube.com/watch?v=nuiLcWE8sPA)
* [Scaling Global CDN at Netflix - Dave Temkin, Director of Global Networks at Netflix](https://www.youtube.com/watch?v=tbqcsHg-Q_o)
* [Scaling Load Balancing Infra to Support 1.3 Billion Users at Facebook - Patrick Shuff, Production Engineer at Facebook](https://www.youtube.com/watch?v=bxhYNfFeVF4)
* [Scaling (a NSFW site) to 200 Million Views A Day And Beyond - Eric Pickup, Lead Platform Developer at MindGeek](https://www.youtube.com/watch?v=RlkCdM_f3p4)
* [Scaling Counting Infrastructure at Quora - Chun-Ho Hung and Nikhil Gar, SEs at Quora](https://www.infoq.com/presentations/quora-analytics)
* [Scaling Git at Microsoft - Saeed Noursalehi, Principal Program Manager at Microsoft](https://www.youtube.com/watch?v=g_MPGU_m01s)

## Books
* [Big Data, Web Ops & DevOps Ebooks - O'Reilly (Online - Free)](http://www.oreilly.com/webops/free/)
* [Google Site Reliability Engineering (Online - Free)](https://landing.google.com/sre/book.html)
* [Distributed Systems for Fun and Profit (Online - Free)](http://book.mixu.net/distsys/)
* [What Every Developer Should Know About SQL Performance (Online - Free)](https://use-the-index-luke.com/sql/table-of-contents)
* [Beyond the Twelve-Factor App - Exploring the DNA of Highly Scalable, Resilient Cloud Applications (Free)](http://www.oreilly.com/webops-perf/free/beyond-the-twelve-factor-app.csp)
* [Chaos Engineering - Building Confidence in System Behavior through Experiments (Free)](http://www.oreilly.com/webops-perf/free/chaos-engineering.csp?intcmp=il-webops-free-product-na_new_site_chaos_engineering_text_cta)
* [The Art of Scalability](http://theartofscalability.com/)
* [Designing Data-Intensive Applications](https://dataintensive.net/)
* [Web Scalability for Startup Engineers](https://www.goodreads.com/book/show/23615147-web-scalability-for-startup-engineers)
* [Scalability Rules: 50 Principles for Scaling Web Sites](http://scalabilityrules.com/)

## Special Thanks
* Jonas Bonér, CTO at Lightbend, for the [original inspiration](https://www.slideshare.net/jboner/scalability-availability-stability-patterns)

## License

[![CC-BY](https://mirrors.creativecommons.org/presskit/buttons/88x31/svg/by.svg)](https://creativecommons.org/licenses/by/4.0/)

This repo is crafted by [Binh Nguyen](https://www.linkedin.com/in/binhnguyennus/) with the helps of Taiwan bubble milk tea in the morning and Germany cereal at night. Feel free to use it to your convenience. Thank You and Happy Coding :heart: