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awesome-scalability

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확장 가능하고 신뢰할 수 있으며 고성능인 대규모 시스템의 패턴

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확장 가능하고, 신뢰할 수 있으며, 고성능의 대규모 시스템 패턴을 설명하기 위한 최신 및 체계화된 읽기 목록입니다. 개념들은 유명 엔지니어들의 아티클과 신뢰할 수 있는 레퍼런스를 통해 설명됩니다. 사례 연구는 수백만에서 수십억 명의 사용자를 서비스하는 검증된 시스템에서 가져왔습니다.

#### 시스템이 느려질 때
> [디자인 원칙](#principle)을 검토하고, 기술 기업들이 [확장성(scalability)](#scalability) 및 [성능(performance)](#performance) 문제를 어떻게 해결했는지 확인하여 문제를 파악하세요. 단일 사용자에게는 빠르지만 부하가 클 때 느린 확장성 문제인지, 단일 사용자에게도 느린 성능 문제인지 이해할 수 있습니다. [지능형 시스템(intelligence)](#intelligence) 섹션은 대규모 데이터(Big Data) 및 딥러닝(Deep Learning) 규모에서 데이터 및 머신러닝을 다루는 분들을 위해 만들어졌습니다.

#### 시스템이 다운될 때
> "어느 날 모든 것을 잃더라도, 평정심을 유지한다면 처음부터 다시 쌓아올릴 수 있습니다!" - Thuan Pham, 전 우버(Uber) CTO. 따라서 평정을 유지하고 [가용성(availability)](#availability)과 [안정성(stability)](#stability) 문제를 신경 쓰세요!

#### 시스템 디자인 면접을 준비할 때
> 화이트보드에 시스템을 설계하기 전에 [면접 노트](#interview)와 [완성된 다이어그램이 포함된 실제 아키텍처](#architecture)를 살펴보고 종합적인 시각을 갖추세요. 기술 기업 엔지니어들의 [발표 자료(talk)](#talk)를 통해 그들이 어떻게 시스템을 구축하고, 확장하며, 최적화하는지 확인할 수 있습니다. 행운을 빕니다!

#### 드림 팀을 구축할 때
> 팀 확장의 목표는 팀 규모를 키우는 것이 아니라 팀의 산출물과 가치를 높이는 것입니다. [조직(organization)](#organization) 섹션에서 채용, 관리, 조직, 문화, 커뮤니케이션 등 다양한 측면에서 기술 기업들이 어떻게 그 목표에 도달하는지 찾아볼 수 있습니다.

#### 커뮤니케이션의 힘

> 기여를 언제나 환영합니다! [기여 가이드라인(CONTRIBUTING.md)](CONTRIBUTING.md)을 살펴보세요. 여기에 더 이상 유지보수되지 않거나 적합하지 않은 링크가 있다면 풀 리퀘스트(pull request)를 제출해 주세요!

> 이 프로젝트에는 오랜 시간 동안 많은 노력이 들어갔습니다. 유용하다고 생각하신다면 Facebook, [Twitter](https://ctt.ec/V8B2p), [Weibo](http://t.cn/RnjFLCB) 또는 채팅 그룹에 공유해 주세요! 아는 것이 힘이며, 지식을 공유하면 힘이 배가 됩니다. 감사합니다!

## Content
- [Principle](#principle)
- [Scalability](#scalability)
- [Availability](#availability)
- [Stability](#stability)
- [Performance](#performance)
- [Intelligence](#intelligence)
- [Architecture](#architecture)
- [Interview](#interview)
- [Organization](#organization)
- [Talk](#talk)
- [Book](#book)

## Principle
* [Lessons from Giant-Scale Services - Eric Brewer, UC Berkeley & Google](https://people.eecs.berkeley.edu/~brewer/papers/GiantScale-IEEE.pdf)
* [Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google](https://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
* [How to Design a Good API & Why it Matters - Joshua Bloch, CMU & Google](https://www.infoq.com/presentations/effective-api-design)
* [On Efficiency, Reliability, Scaling - James Hamilton, VP at AWS](http://mvdirona.com/jrh/work/)
* [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://blog.cleancoder.com/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)
* [Monoliths and Microservices](https://medium.com/@SkyscannerEng/monoliths-and-microservices-8c65708c3dbf)
* [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: Hidden Costs](https://blog.codinghorror.com/scaling-up-vs-scaling-out-hidden-costs/)
* [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)
* [Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn271399(v=pandp.10))
* [SQL vs NoSQL](https://www.upwork.com/hiring/data/sql-vs-nosql-databases-whats-the-difference/)
* [SQL vs NoSQL - Lesson Learned at 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)
* [Don’t be tricked by the Hashing Trick](https://booking.ai/dont-be-tricked-by-the-hashing-trick-192a6aae3087)
* [Uniform Consistent Hashing 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](https://www.the-paper-trail.org/post/2014-06-06-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://engineering.zalando.com/posts/2018/01/simplicity-by-distributing-complexity.html)
* [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)
* [Automate and Abstract: Lessons at Facebook](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)
* [Building Fast and Resilient Web Applications - Ilya Grigorik](https://www.igvita.com/2016/05/20/building-fast-and-resilient-web-applications/)
* [Accept Partial Failures, Minimize Service Loss](https://www.usenix.org/conference/srecon17asia/program/presentation/wang_daxin)
* [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)

## Scalability
* [Microservices and Orchestration](https://martinfowler.com/microservices/)
	* [Domain-Oriented Microservice Architecture at Uber](https://eng.uber.com/microservice-architecture/)
	* [Service Architecture (3 parts: Domain Gateways, Value-Added Services, BFF) at SoundCloud](https://developers.soundcloud.com/blog/service-architecture-3)
	* [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)
	* [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/)
	* [Docker in Production at Treehouse](https://medium.com/treehouse-engineering/lessons-learned-running-docker-in-production-5dce99ece770)
	* [Microservice at SoundCloud](https://developers.soundcloud.com/blog/inside-a-soundcloud-microservice)
	* [Operate Kubernetes Reliably at Stripe](https://stripe.com/blog/operating-kubernetes)
	* [Cross-Cluster Traffic Mirroring with Istio at Trivago](https://tech.trivago.com/2020/06/10/cross-cluster-traffic-mirroring-with-istio/)
	* [Agrarian-Scale Kubernetes (3 parts) at New York Times](https://open.nytimes.com/agrarian-scale-kubernetes-part-3-ee459887ed7e)
	* [Nanoservices at BBC](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)
	* [Docker Containers that Power Over 100.000 Online Shops at Shopify](https://shopifyengineering.myshopify.com/blogs/engineering/docker-at-shopify-how-we-built-containers-that-power-over-100-000-online-shops)
	* [Microservice Architecture at Medium](https://medium.engineering/microservice-architecture-at-medium-9c33805eb74f)
	* [From bare-metal to Kubernetes at Betabrand](https://boxunix.com/post/bare_metal_to_kube/)
	* [Kubernetes at Tinder](https://medium.com/tinder-engineering/tinders-move-to-kubernetes-cda2a6372f44)
	* [Kubernetes at Quora](https://www.quora.com/q/quoraengineering/Adopting-Kubernetes-at-Quora)	
	* [Kubernetes Platform at Pinterest](https://medium.com/pinterest-engineering/building-a-kubernetes-platform-at-pinterest-fb3d9571c948)
	* [Microservices at Nubank](https://medium.com/building-nubank/microservices-at-nubank-an-overview-2ebcb336c64d)
	* [Payment Transaction Management in Microservices at Mercari](https://engineering.mercari.com/en/blog/entry/20210831-2019-06-07-155849/)
	* [Service Mesh at Snap](https://eng.snap.com/monolith-to-multicloud-microservices-snap-service-mesh)
	* [GRIT: Protocol for Distributed Transactions across Microservices at eBay](https://tech.ebayinc.com/engineering/grit-a-protocol-for-distributed-transactions-across-microservices/)
	* [Rubix: Kubernetes at Palantir](https://medium.com/palantir/introducing-rubix-kubernetes-at-palantir-ab0ce16ea42e)
	* [CRISP: Critical Path Analysis for Microservice Architectures at Uber](https://eng.uber.com/crisp-critical-path-analysis-for-microservice-architectures/)
* [Distributed Caching](https://www.wix.engineering/post/scaling-to-100m-to-cache-or-not-to-cache)
	* [EVCache: Distributed In-memory Caching at Netflix](https://medium.com/netflix-techblog/caching-for-a-global-netflix-7bcc457012f1)
	* [EVCache Cache Warmer Infrastructure at Netflix](https://medium.com/netflix-techblog/cache-warming-agility-for-a-stateful-service-2d3b1da82642)
	* [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/)
	* [Pycache: In-process Caching at Quora](https://quoraengineering.quora.com/Pycache-lightning-fast-in-process-caching)
	* [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)
	* [Estimating the Cache Efficiency using Big Data at Allegro](https://allegro.tech/2017/01/estimating-the-cache-efficiency-using-big-data.html)
	* [Distributed Cache at Zalando](https://engineering.zalando.com/posts/2018/04/distributed-cache-akka-kubernetes.html)
	* [Distributed Cache for S3 at ClickHouse](https://clickhouse.com/blog/building-a-distributed-cache-for-s3)
	* [Application Data Caching from RAM to SSD at NetFlix](https://medium.com/netflix-techblog/evolution-of-application-data-caching-from-ram-to-ssd-a33d6fa7a690)
	* [Tradeoffs of Replicated Cache at Skyscanner](https://medium.com/@SkyscannerEng/the-tradeoffs-of-a-replicated-cache-b6680c722f58)
	* [Location Caching with Quadtrees at Yext](http://engblog.yext.com/post/geolocation-caching)
	* [Video Metadata Caching at Vimeo](https://medium.com/vimeo-engineering-blog/video-metadata-caching-at-vimeo-a54b25f0b304)
	* [Scaling Redis 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 at Trivago](http://tech.trivago.com/2017/01/25/learn-redis-the-hard-way-in-production/)
	* [Optimizing Redis Storage at Deliveroo](https://deliveroo.engineering/2017/01/19/optimising-membership-queries.html)
	* [Memory Optimization in Redis at Wattpad](http://engineering.wattpad.com/post/23244724794/store-more-stuff-memory-optimization-in-redis)
	* [Redis Fleet at Heroku](https://blog.heroku.com/rolling-redis-fleet)
	* [Solving Remote Build Cache Misses (2 parts) at SoundCloud](https://developers.soundcloud.com/blog/gradle-remote-build-cache-misses-part-2)
	* [Ratings & Reviews (2 parts) at Flipkart](https://blog.flipkart.tech/ratings-reviews-flipkart-part-2-574ab08e75cf)
	* [Prefetch Caching of Items at eBay](https://tech.ebayinc.com/engineering/prefetch-caching-of-ebay-items/)
	* [Cross-Region Caching Library at Wix](https://www.wix.engineering/post/how-we-built-a-cross-region-caching-library)
	* [Improving Distributed Caching Performance and Efficiency at Pinterest](https://medium.com/pinterest-engineering/improving-distributed-caching-performance-and-efficiency-at-pinterest-92484b5fe39b)
	* [Standardize and Improve Microservices Caching at DoorDash](https://doordash.engineering/2023/10/19/how-doordash-standardized-and-improved-microservices-caching/)
    * [HTTP Caching and CDN](https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching)
        * [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)
        * [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://dropbox.tech/infrastructure/meet-bandaid-the-dropbox-service-proxy)
		* [Service Workers at Slack](https://slack.engineering/service-workers-at-slack-our-quest-for-faster-boot-times-and-offline-support-3492cf79c88)
		* [CDN Services at Spotify](https://labs.spotify.com/2020/02/24/how-spotify-aligned-cdn-services-for-a-lightning-fast-streaming-experience/)
* [Distributed Locking](https://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html)
	* [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/)
	* [Distributed Locking at Uber](https://www.youtube.com/watch?v=MDuagr729aU)
	* [Distributed Locks using Redis at GoSquared](https://engineering.gosquared.com/distributed-locks-using-redis)
	* [ZooKeeper at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/zookeeper-at-twitter.html)
	* [Eliminating Duplicate Queries using Distributed Locking at Chartio](https://chartio.com/blog/eliminating-duplicate-queries-using-distributed-locking/)
* [Distributed Tracking, Tracing, and Measuring](https://www.oreilly.com/ideas/understanding-the-value-of-distributed-tracing)
	* [Zipkin: Distributed Systems Tracing at Twitter](https://blog.twitter.com/engineering/en_us/a/2012/distributed-systems-tracing-with-zipkin.html)
	* [Improve Zipkin Traces using Kubernetes Pod Metadata at SoundCloud](https://developers.soundcloud.com/blog/using-kubernetes-pod-metadata-to-improve-zipkin-traces)
	* [Canopy: Scalable Distributed Tracing & Analysis at Facebook](https://www.infoq.com/presentations/canopy-scalable-tracing-analytics-facebook)
	* [Pintrace: Distributed Tracing at Pinterest](https://medium.com/@Pinterest_Engineering/distributed-tracing-at-pinterest-with-new-open-source-tools-a4f8a5562f6b)
	* [XCMetrics: All-in-One Tool for Tracking Xcode Build Metrics at Spotify](https://engineering.atspotify.com/2021/01/20/introducing-xcmetrics-our-all-in-one-tool-for-tracking-xcode-build-metrics/)
	* [Real-time Distributed Tracing at LinkedIn](https://engineering.linkedin.com/distributed-service-call-graph/real-time-distributed-tracing-website-performance-and-efficiency)	
	* [Tracking Service Infrastructure at Scale at Shopify](https://www.usenix.org/conference/srecon17americas/program/presentation/arthorne)	
	* [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/)
	* [JVM Profiler: Tracing Distributed JVM Applications at Uber](https://eng.uber.com/jvm-profiler/)
	* [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/)
	* [osquery Across the Enterprise at Palantir](https://medium.com/@palantir/osquery-across-the-enterprise-3c3c9d13ec55)
	* [StatsD at Etsy](https://codeascraft.com/2011/02/15/measure-anything-measure-everything/)
* [Distributed Scheduling](https://www.csee.umbc.edu/courses/graduate/CMSC621/fall02/lectures/ch11.pdf)
	* [Distributed Task Scheduling (3 parts) at PagerDuty](https://www.pagerduty.com/eng/distributed-task-scheduling-3/)
    * [Building Cron at Google](https://landing.google.com/sre/sre-book/chapters/distributed-periodic-scheduling/)
    * [Distributed Cron Architecture at Quora](https://quoraengineering.quora.com/Quoras-Distributed-Cron-Architecture)
    * [Chronos: A Replacement for Cron at Airbnb](https://medium.com/airbnb-engineering/chronos-a-replacement-for-cron-f05d7d986a9d)
    * [Scheduler at Nextdoor](https://engblog.nextdoor.com/we-don-t-run-cron-jobs-at-nextdoor-6f7f9cc62040)
    * [Peloton: Unified Resource Scheduler for Diverse Cluster Workloads at Uber](https://eng.uber.com/peloton/)
    * [Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix](https://medium.com/netflix-techblog/fenzo-oss-scheduler-for-apache-mesos-frameworks-5c340e77e543)
    * [Airflow - Workflow Orchestration](https://airflow.apache.org/)
		* [Airflow at Airbnb](https://medium.com/airbnb-engineering/airflow-a-workflow-management-platform-46318b977fd8)
		* [Airflow at Adyen](https://www.adyen.com/knowledge-hub/apache-airflow-at-adyen)
		* [Airflow at Pandora](https://engineering.pandora.com/apache-airflow-at-pandora-1d7a844d68ee)
        * [Airflow at Robinhood](https://medium.com/robinhood-engineering/why-robinhood-uses-airflow-aed13a9a90c8)
        * [Airflow at Lyft](https://eng.lyft.com/running-apache-airflow-at-lyft-6e53bb8fccff)
        * [Airflow at Drivy](https://drivy.engineering/airflow-architecture/)
		* [Airflow at Grab](https://engineering.grab.com/experimentation-platform-data-pipeline)
		* [Airflow at Adobe](https://medium.com/adobetech/adobe-experience-platform-orchestration-service-with-apache-airflow-952203723c0b)
        * [Auditing Airflow Job Runs at Walmart](https://medium.com/walmartlabs/auditing-airflow-batch-jobs-73b45100045)
        * [MaaT: DAG-based Distributed Task Scheduler at Alibaba](https://hackernoon.com/meet-maat-alibabas-dag-based-distributed-task-scheduler-7c9cf0c83438)
        * [boundary-layer: Declarative Airflow Workflows at Etsy](https://www.etsy.com/codeascraft/boundary-layer-declarative-airflow-workflows)
* [Distributed Monitoring and Alerting](https://www.oreilly.com/ideas/monitoring-distributed-systems)
	* [Unicorn: Remediation System at eBay](https://www.ebayinc.com/stories/blogs/tech/unicorn-rheos-remediation-center/)
	* [M3: Metrics and Monitoring Platform at Uber](https://eng.uber.com/optimizing-m3/)
	* [Athena: Automated Build Health Management System at Dropbox](https://dropbox.tech/infrastructure/athena-our-automated-build-health-management-system)
	* [Vortex: Monitoring Server Applications at Dropbox](https://dropbox.tech/infrastructure/monitoring-server-applications-with-vortex)
	* [Nuage: Cloud Management Service at LinkedIn](https://engineering.linkedin.com/blog/2019/solving-manageability-challenges-with-nuage)
	* [Telltale: Application Monitoring at Netflix](https://netflixtechblog.com/telltale-netflix-application-monitoring-simplified-5c08bfa780ba)
	* [ThirdEye: Monitoring Platform at LinkedIn](https://engineering.linkedin.com/blog/2019/06/smart-alerts-in-thirdeye--linkedins-real-time-monitoring-platfor)
	* [Periskop: Exception Monitoring Service at SoundCloud](https://developers.soundcloud.com/blog/periskop-exception-monitoring-service)
    * [Securitybot: Distributed Alerting Bot at Dropbox](https://dropbox.tech/security/meet-securitybot-open-sourcing-automated-security-at-scale)
    * [Monitoring System at Alibaba](https://www.usenix.org/conference/srecon18asia/presentation/xinchi)
    * [Real User Monitoring at Dailymotion](https://medium.com/dailymotion/real-user-monitoring-1948375f8be5)
    * [Alerting Ecosystem at Uber](https://eng.uber.com/observability-at-scale/)
	* [Alerting Framework at Airbnb](https://medium.com/airbnb-engineering/alerting-framework-at-airbnb-35ba48df894f)
	* [Alerting on Service-Level Objectives (SLOs) at SoundCloud](https://developers.soundcloud.com/blog/alerting-on-slos)
    * [Job-based Forecasting Workflow for Observability Anomaly Detection at Uber](https://eng.uber.com/observability-anomaly-detection/)
	* [Monitoring and Alert System using Graphite and Cabot at HackerEarth](http://engineering.hackerearth.com/2017/03/21/monitoring-and-alert-system-using-graphite-and-cabot/)
    * [Observability (2 parts) at Twitter](https://blog.twitter.com/engineering/en_us/a/2016/observability-at-twitter-technical-overview-part-ii.html)
    * [Distributed Security Alerting at Slack](https://slack.engineering/distributed-security-alerting-c89414c992d6)
    * [Real-Time News Alerting at Bloomberg](https://www.infoq.com/presentations/news-alerting-bloomberg)
	* [Data Pipeline Monitoring System at LinkedIn](https://engineering.linkedin.com/blog/2019/an-inside-look-at-linkedins-data-pipeline-monitoring-system-)
	* [Monitoring and Observability at Picnic](https://blog.picnic.nl/monitoring-and-observability-at-picnic-684cefd845c4)
* [Distributed Security](https://msdn.microsoft.com/en-us/library/cc767123.aspx)
	* [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)
	* [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)	
	* [Syscall Auditing at Scale at Slack](https://slack.engineering/syscall-auditing-at-scale-e6a3ca8ac1b8)
	* [Athenz: Fine-Grained, Role-Based Access Control at Yahoo](https://yahooeng.tumblr.com/post/160481899076/open-sourcing-athenz-fine-grained-role-based)
	* [Security Development Lifecycle at Slack](https://slack.engineering/moving-fast-and-securing-things-540e6c5ae58a)
	* [Unprivileged Container Builds at Kinvolk](https://kinvolk.io/blog/2018/04/towards-unprivileged-container-builds/)
	* [Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix](https://medium.com/netflix-techblog/netflix-sirt-releases-diffy-a-differencing-engine-for-digital-forensics-in-the-cloud-37b71abd2698)
	* [Detecting Credential Compromise in AWS at Netflix](https://medium.com/netflix-techblog/netflix-cloud-security-detecting-credential-compromise-in-aws-9493d6fd373a)
	* [Scalable User Privacy at Spotify](https://labs.spotify.com/2018/09/18/scalable-user-privacy/)
	* [AVA: Audit Web Applications at Indeed](https://engineering.indeedblog.com/blog/2018/09/application-scanning/)
	* [TTL as a Service: Automatic Revocation of Stale Privileges at Yelp](https://engineeringblog.yelp.com/2018/11/ttl-as-a-service.html)
	* [Enterprise Key Management at Slack](https://slack.engineering/engineering-dive-into-slack-enterprise-key-management-1fce471b178c)	
	* [Scalability and Authentication at Twitch](https://blog.twitch.tv/en/2019/03/15/how-twitch-addresses-scalability-and-authentication/)
	* [Edge Authentication and Token-Agnostic Identity Propagation at Netflix](https://netflixtechblog.com/edge-authentication-and-token-agnostic-identity-propagation-514e47e0b602)
	* [Hardening Kubernetes Infrastructure with Cilium at Palantir](https://blog.palantir.com/hardening-palantirs-kubernetes-infrastructure-with-cilium-1c40d4c7ef0)
	* [Improving Web Vulnerability Management through Automation at Lyft](https://eng.lyft.com/improving-web-vulnerability-management-through-automation-2631570d8415)
	* [Clock Skew when Syncing Password Payloads at Drobbox](https://dropbox.tech/application/dropbox-passwords-clock-skew-payload-sync-merge)
* [Distributed Messaging, Queuing, and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
	* [Cape: Event Stream Processing Framework at Dropbox](https://dropbox.tech/infrastructure/introducing-cape)
	* [Brooklin: Distributed Service for Near Real-Time Data Streaming at LinkedIn](https://engineering.linkedin.com/blog/2019/brooklin-open-source)
	* [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)	
	* [Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo](https://yahooeng.tumblr.com/post/161855616651/open-sourcing-bullet-yahoos-forward-looking)
	* [EventHorizon: Tool for Watching Events Streaming at Etsy](https://codeascraft.com/2018/05/29/the-eventhorizon-saga/)
	* [Qmessage: Distributed, Asynchronous Task Queue at Quora](https://quoraengineering.quora.com/Qmessage-Handling-Billions-of-Tasks-Per-Day)
	* [Cherami: Message Queue System for Transporting Async Tasks at Uber](https://eng.uber.com/cherami/)
	* [Dynein: Distributed Delayed Job Queueing System at Airbnb](https://medium.com/airbnb-engineering/dynein-building-a-distributed-delayed-job-queueing-system-93ab10f05f99)
	* [Timestone: Queueing System for Non-Parallelizable Workloads at Netflix](https://netflixtechblog.com/timestone-netflixs-high-throughput-low-latency-priority-queueing-system-with-built-in-support-1abf249ba95f)
	* [Messaging Service at Riot Games](https://engineering.riotgames.com/news/riot-messaging-service)
	* [Messaging System Model at Dropbox](https://dropbox.tech/infrastructure/infrastructure-messaging-system-model-async-platform-evolution)
	* [Debugging Production with Event Logging at Zillow](https://www.zillow.com/engineering/debugging-production-event-logging/)
	* [Cross-platform In-app Messaging Orchestration Service at Netflix](https://medium.com/netflix-techblog/building-a-cross-platform-in-app-messaging-orchestration-service-86ba614f92d8)
	* [Video Gatekeeper at Netflix](https://medium.com/netflix-techblog/re-architecting-the-video-gatekeeper-f7b0ac2f6b00)
	* [Scaling Push Messaging for Millions of Devices at Netflix](https://www.infoq.com/presentations/neflix-push-messaging-scale)
	* [Delaying Asynchronous Message Processing with RabbitMQ at Indeed](http://engineering.indeedblog.com/blog/2017/06/delaying-messages/)	
	* [Benchmarking Streaming Computation Engines at Yahoo](https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at)
	* [Improving Stream Data Quality With Protobuf Schema Validation at Deliveroo](https://deliveroo.engineering/2019/02/05/improving-stream-data-quality-with-protobuf-schema-validation.html)
	* [Scaling Email Infrastructure at Medium](https://medium.engineering/scaling-email-infrastructure-for-medium-digest-254223c883b8)
	* [Real-time Messaging at Slack](https://slack.engineering/real-time-messaging/)
	* [Event Stream Database at Nike](https://medium.com/nikeengineering/moving-faster-with-aws-by-creating-an-event-stream-database-dedec8ca3eeb)
	* [Event Tracking System at Udemy](https://medium.com/udemy-engineering/designing-the-new-event-tracking-system-at-udemy-a45e502216fd)
    * [Event-Driven Messaging](https://martinfowler.com/articles/201701-event-driven.html)
        * [Domain-Driven Design at Alibaba](https://medium.com/swlh/creating-coding-excellence-with-domain-driven-design-88f73d2232c3)
        * [Domain-Driven Design at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0)
        * [Domain-Driven Design at Moonpig](https://engineering.moonpig.com/development/modelling-for-domain-driven-design)
        * [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)
        * [Event Sourcing (2 parts) at eBay](https://www.ebayinc.com/stories/blogs/tech/event-sourcing-in-action-with-ebays-continuous-delivery-team/)
		* [Event Sourcing at FREE NOW](https://medium.com/inside-freenow/event-sourcing-an-evolutionary-perspective-31e7387aa6f1)
		* [Scalable content feed using Event Sourcing and CQRS patterns at Brainly](https://medium.com/engineering-brainly/scalable-content-feed-using-event-sourcing-and-cqrs-patterns-e09df98bf977)
    * [Pub-Sub Messaging](https://aws.amazon.com/pub-sub-messaging/)
		* [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](https://code.facebook.com/posts/188966771280871/wormhole-pub-sub-system-moving-data-through-space-and-time/)
		* [MemQ: Cloud Native Pub-Sub System at Pinterest](https://medium.com/pinterest-engineering/memq-an-efficient-scalable-cloud-native-pubsub-system-4402695dd4e7)
		* [Pub-Sub in Microservices at Netflix](https://medium.com/netflix-techblog/how-netflix-microservices-tackle-dataset-pub-sub-4a068adcc9a)
	* [Kafka - Message Broker](https://martin.kleppmann.com/papers/kafka-debull15.pdf)	
		* [Kafka at LinkedIn](https://engineering.linkedin.com/kafka/running-kafka-scale)
		* [Kafka at Pinterest](https://medium.com/pinterest-engineering/how-pinterest-runs-kafka-at-scale-ff9c6f735be)
		* [Kafka at Trello](https://tech.trello.com/why-we-chose-kafka/)	
		* [Kafka at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63)
		* [Kafka at The New York Times](https://open.nytimes.com/publishing-with-apache-kafka-at-the-new-york-times-7f0e3b7d2077)
		* [Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html)
		* [Kafka at Criteo](https://medium.com/criteo-labs/upgrading-kafka-on-a-large-infra-3ee99f56e970)
		* [Kafka on Kubernetes at Shopify](https://shopifyengineering.myshopify.com/blogs/engineering/running-apache-kafka-on-kubernetes-at-shopify)
		* [Kafka on PaaSTA: Running Kafka on Kubernetes at Yelp (2 parts)](https://engineeringblog.yelp.com/2022/03/kafka-on-paasta-part-two.html)
		* [Migrating Kafka's Zookeeper with No Downtime at Yelp](https://engineeringblog.yelp.com/2019/01/migrating-kafkas-zookeeper-with-no-downtime.html)
		* [Reprocessing and Dead Letter Queues with Kafka at Uber](https://eng.uber.com/reliable-reprocessing/)
		* [Chaperone: Audit Kafka End-to-End at Uber](https://eng.uber.com/chaperone/)
		* [Finding Kafka throughput limit in infrastructure at Dropbox](https://dropbox.tech/infrastructure/finding-kafkas-throughput-limit-in-dropbox-infrastructure)
		* [Cost Orchestration at Walmart](https://medium.com/walmartlabs/cost-orchestration-at-walmart-f34918af67c4)
		* [InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second at Hulu](https://medium.com/hulu-tech-blog/how-hulu-uses-influxdb-and-kafka-to-scale-to-over-1-million-metrics-a-second-1721476aaff5)
		* [Scaling Kafka to Support Data Growth at PayPal](https://medium.com/paypal-tech/scaling-kafka-to-support-paypals-data-growth-a0b4da420fab)
	* [Stream Data Deduplication](https://en.wikipedia.org/wiki/Data_deduplication)
		* [Exactly-once Semantics with Kafka](https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/)
		* [Real-time Deduping at Tapjoy](http://eng.tapjoy.com/blog-list/real-time-deduping-at-scale)
		* [Deduplication at Segment](https://segment.com/blog/exactly-once-delivery/)
		* [Deduplication at Mail.Ru](https://medium.com/@andrewsumin/efficient-storage-how-we-went-down-from-50-pb-to-32-pb-99f9c61bf6b4)
		* [Petabyte Scale Data Deduplication at Mixpanel](https://medium.com/mixpaneleng/petabyte-scale-data-deduplication-mixpanel-engineering-e808c70c99f8)
* [Distributed Logging](https://blog.codinghorror.com/the-problem-with-logging/)
	* [Logging at LinkedIn](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying)
	* [Scalable and Reliable Log Ingestion at Pinterest](https://medium.com/@Pinterest_Engineering/scalable-and-reliable-data-ingestion-at-pinterest-b921c2ee8754)
	* [High-performance Replicated Log Service at Twitter](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://quoraengineering.quora.com/Logging-and-Aggregation-at-Quora)
	* [Collection and Analysis of Daemon Logs at Badoo](https://badoo.com/techblog/blog/2016/06/06/collection-and-analysis-of-daemon-logs-at-badoo/)
	* [Log Parsing with Static Code Analysis at Palantir](https://medium.com/palantir/using-static-code-analysis-to-improve-log-parsing-18f0d1843965)		
	* [Centralized Application Logging at eBay](https://tech.ebayinc.com/engineering/low-latency-and-high-throughput-cal-ingress/)
	* [Enrich VPC Flow Logs at Hyper Scale to provide Network Insight at Netflix](https://netflixtechblog.com/hyper-scale-vpc-flow-logs-enrichment-to-provide-network-insight-e5f1db02910d)	
	* [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)
	* [DBLog: Generic Change-Data-Capture Framework at Netflix](https://medium.com/netflix-techblog/dblog-a-generic-change-data-capture-framework-69351fb9099b)	
* [Distributed Searching](http://nwds.cs.washington.edu/files/nwds/pdf/Distributed-WR.pdf)
	* [Search Architecture at Instagram](https://instagram-engineering.com/search-architecture-eeb34a936d3a)
	* [Search Architecture at eBay](http://www.cs.otago.ac.nz/homepages/andrew/papers/2017-8.pdf)
	* [Search Architecture at Box](https://medium.com/box-tech-blog/scaling-box-search-using-lumos-22d9e0cb4175)
	* [Search Discovery Indexing Platform at Coupang](https://medium.com/coupang-tech/the-evolution-of-search-discovery-indexing-platform-fa43e41305f9)
	* [Universal Search System at Pinterest](https://medium.com/pinterest-engineering/building-a-universal-search-system-for-pinterest-e4cb03a898d4)
	* [Improving Search Engine Efficiency by over 25% at eBay](https://www.ebayinc.com/stories/blogs/tech/making-e-commerce-search-faster/)	
	* [Indexing and Querying Telemetry Logs with Lucene at Palantir](https://medium.com/palantir/indexing-and-querying-telemetry-logs-with-lucene-234c5ce3e5f3)
	* [Query Understanding at TripAdvisor](https://www.tripadvisor.com/engineering/query-understanding-at-tripadvisor/)
	* [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 Engine at DoorDash](https://careersatdoordash.com/blog/introducing-doordashs-in-house-search-engine/)
	* [Stability and Scalability for Search at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2022/stability-and-scalability-for-search)
	* [Search Service at Twitter (2014)](https://blog.twitter.com/engineering/en_us/a/2014/building-a-complete-tweet-index.html)
	* [Autocomplete Search (2 parts) at Traveloka](https://medium.com/traveloka-engineering/high-quality-autocomplete-search-part-2-d5b15bb0dadf)
	* [Data-Driven Autocorrection System at Canva](https://product.canva.com/building-a-data-driven-autocorrection-system/)
	* [Adapting Search to Indian Phonetics at Flipkart](https://blog.flipkart.tech/adapting-search-to-indian-phonetics-cdbe65259686)
	* [Nautilus: Search Engine at Dropbox](https://dropbox.tech/machine-learning/architecture-of-nautilus-the-new-dropbox-search-engine)
	* [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://blog.flipkart.tech/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/)
		* [Building a scalable ELK stack at Envato](https://webuild.envato.com/blog/building-a-scalable-elk-stack/)
		* [ELK at Robinhood](https://robinhood.engineering/taming-elk-4e1349f077c3)
		* [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/)
		* [Improve Performance using Elasticsearch Plugins (2 parts) at Tinder](https://medium.com/tinder-engineering/how-we-improved-our-performance-using-elasticsearch-plugins-part-2-b051da2ee85b)
		* [Elasticsearch at Kickstarter](https://kickstarter.engineering/elasticsearch-at-kickstarter-db3c487887fc)
		* [Log Parsing with Logstash and Google Protocol Buffers at Trivago](https://tech.trivago.com/2016/01/19/logstash_protobuf_codec/)
		* [Fast Order Search using Data Pipeline and Elasticsearch at Yelp](https://engineeringblog.yelp.com/2018/06/fast-order-search.html)
		* [Moving Core Business Search to Elasticsearch at Yelp](https://engineeringblog.yelp.com/2017/06/moving-yelps-core-business-search-to-elasticsearch.html)
		* [Sharding out Elasticsearch at Vinted](http://engineering.vinted.com/2017/06/05/sharding-out-elasticsearch/)
		* [Self-Ranking Search with Elasticsearch at Wattpad](http://engineering.wattpad.com/post/146216619727/self-ranking-search-with-elasticsearch-at-wattpad)
		* [Vulcanizer: a library for operating Elasticsearch at Github](https://github.blog/2019-03-05-vulcanizer-a-library-for-operating-elasticsearch/)	
* [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)
		* [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://quoraengineering.quora.com/Optimizing-Memcached-Efficiency)
		* [Real-Time Data Warehouse with MemSQL on Cisco UCS](https://blogs.cisco.com/datacenter/memsql)
		* [Moving to MemSQL at Tapjoy](http://eng.tapjoy.com/blog-list/moving-to-memsql)
		* [MemSQL and Kinesis for Real-time Insights at Disney](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/68131)
		* [MemSQL to Query Hundreds of Billions of Rows in a Dashboard at Pandora](https://engineering.pandora.com/using-memsql-at-pandora-79a86cb09b57)
	* [Object Storage](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)
		* [File System on Amazon S3 at Quantcast](https://www.quantcast.com/blog/quantcast-file-system-on-amazon-s3/)
		* [Image Recovery at Scale Using S3 Versioning at Trivago](https://tech.trivago.com/2018/09/03/efficient-image-recovery-at-scale-using-amazon-s3-versioning/)
		* [Cloud Object Store at Yahoo](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)
		* [Dynamometer: Scale Testing HDFS on Minimal Hardware with Maximum Fidelity at LinkedIn](https://engineering.linkedin.com/blog/2018/02/dynamometer--scale-testing-hdfs-on-minimal-hardware-with-maximum)
		* [Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb](https://medium.com/airbnb-engineering/hammerspace-persistent-concurrent-off-heap-storage-3db39bb04472)
		* [MezzFS: Mounting Object Storage in Media Processing Platform at Netflix](https://medium.com/netflix-techblog/mezzfs-mounting-object-storage-in-netflixs-media-processing-platform-cda01c446ba)	
		* [Magic Pocket: In-house Multi-exabyte Storage System at Dropbox](https://dropbox.tech/infrastructure/inside-the-magic-pocket)
* [Relational Databases](https://www.mysql.com/products/cluster/scalability.html)
	* [MySQL at Uber](https://www.uber.com/en-SG/blog/mysql-at-uber/)
	* [MySQL at Pinterest](https://medium.com/@Pinterest_Engineering/learn-to-stop-using-shiny-new-things-and-love-mysql-3e1613c2ce14)
	* [PostgreSQL at Twitch](https://blog.twitch.tv/en/2016/10/11/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/post/scaling-to-100m-mysql-is-a-better-nosql)
	* [Building and Deploying MySQL Raft at Meta](https://engineering.fb.com/2023/05/16/data-infrastructure/mysql-raft-meta/)
	* [MaxScale (MySQL) Database Proxy at Airbnb](https://medium.com/airbnb-engineering/unlocking-horizontal-scalability-in-our-web-serving-tier-d907449cdbcf)
	* [Switching from Postgres to MySQL at Uber](https://www.uber.com/en-NL/blog/postgres-to-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)
	* [Scaling Database Access for 100s of Billions of Queries per Day at PayPal](https://medium.com/paypal-engineering/scaling-database-access-for-100s-of-billions-of-queries-per-day-paypal-introducing-hera-e192adacda54)
	* [Minimizing Read-Write MySQL Downtime at Yelp](https://engineeringblog.yelp.com/2020/11/minimizing-read-write-mysql-downtime.html)
	* [Migrating MySQL from 5.6 to 8.0 at Facebook](https://engineering.fb.com/2021/07/22/data-infrastructure/mysql/)
	* [Migration from HBase to MyRocks at Quora](https://quoraengineering.quora.com/Migration-from-HBase-to-MyRocks-at-Quora)
	* [Replication](https://docs.microsoft.com/en-us/sql/relational-databases/replication/types-of-replication)
		* [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/)
		* [Read Consistency with Database Replicas at Shopify](https://shopify.engineering/read-consistency-database-replicas)
		* [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)
		* [Partitioning Main MySQL Database at Airbnb](https://medium.com/airbnb-engineering/how-we-partitioned-airbnb-s-main-database-in-two-weeks-55f7e006ff21)
		* [Herb: Multi-DC Replication Engine for Schemaless Datastore at Uber](https://eng.uber.com/herb-datacenter-replication/)
	* [Sharding](https://quabase.sei.cmu.edu/mediawiki/index.php/Shard_data_set_across_multiple_servers_(Range-based))
		* [Sharding MySQL at Pinterest](https://medium.com/@Pinterest_Engineering/sharding-pinterest-how-we-scaled-our-mysql-fleet-3f341e96ca6f)
		* [Sharding MySQL at Twilio](https://www.twilio.com/engineering/2014/06/26/how-we-replaced-our-data-pipeline-with-zero-downtime)
		* [Sharding MySQL at Square](https://medium.com/square-corner-blog/sharding-cash-10280fa3ef3b)
		* [Sharding MySQL at Quora](https://www.quora.com/q/quoraengineering/MySQL-sharding-at-Quora)
		* [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)
		* [Sharding Postgres at Notion](https://www.notion.so/blog/sharding-postgres-at-notion)
		* [Sharding Postgres at Figma](https://www.figma.com/blog/how-figmas-databases-team-lived-to-tell-the-scale/)
		* [Solr: Improving Performance for Batch Indexing at Box](https://blog.box.com/blog/solr-improving-performance-batch-indexing/)	
		* [Geosharded Recommendations (3 parts) at Tinder](https://medium.com/tinder-engineering/geosharded-recommendations-part-3-consistency-2d2cb2f0594b)
		* [Scaling Services with Shard Manager at Facebook](https://engineering.fb.com/production-engineering/scaling-services-with-shard-manager/)
	* [Presto the Distributed SQL Query Engine](https://research.fb.com/wp-content/uploads/2019/03/Presto-SQL-on-Everything.pdf?)
		* [Presto at Pinterest](https://medium.com/@Pinterest_Engineering/presto-at-pinterest-a8bda7515e52)
		* [Presto Infrastructure at Lyft](https://eng.lyft.com/presto-infrastructure-at-lyft-b10adb9db01)
		* [Presto at Grab](https://engineering.grab.com/scaling-like-a-boss-with-presto)
		* [Engineering Data Analytics with Presto and Apache Parquet at Uber](https://eng.uber.com/presto/)
		* [Data Wrangling at Slack](https://slack.engineering/data-wrangling-at-slack-f2e0ff633b69)
		* [Presto in Big Data Platform on AWS at Netflix](https://medium.com/netflix-techblog/using-presto-in-our-big-data-platform-on-aws-938035909fd4)
		* [Presto Auto Scaling at Eventbrite](https://www.eventbrite.com/engineering/big-data-workloads-presto-auto-scaling/)
		* [Speed Up Presto with Alluxio Local Cache at Uber](https://www.uber.com/en-MY/blog/speed-up-presto-with-alluxio-local-cache/)
* [NoSQL Databases](https://www.thoughtworks.com/insights/blog/nosql-databases-overview)
	* [Key-Value Databases](http://www.cs.ucsb.edu/~agrawal/fall2009/dynamo.pdf)
		* [DynamoDB at Nike](https://medium.com/nikeengineering/becoming-a-nimble-giant-how-dynamo-db-serves-nike-at-scale-4cc375dbb18e)
		* [DynamoDB at Segment](https://segment.com/blog/the-million-dollar-eng-problem/)
		* [DynamoDB at Mapbox](https://blog.mapbox.com/scaling-mapbox-infrastructure-with-dynamodb-streams-d53eabc5e972)
		* [Manhattan: Distributed Key-Value Database at Twitter](https://blog.twitter.com/engineering/en_us/a/2014/manhattan-our-real-time-multi-tenant-distributed-database-for-twitter-scale.html)
		* [Sherpa: Distributed NoSQL Key-Value Store at Yahoo](https://yahooeng.tumblr.com/post/120730204806/sherpa-scales-new-heights)
		* [HaloDB: Embedded Key-Value Storage Engine at Yahoo](https://yahooeng.tumblr.com/post/178262468576/introducing-halodb-a-fast-embedded-key-value)
		* [MPH: Fast and Compact Immutable Key-Value Stores at Indeed](http://engineering.indeedblog.com/blog/2018/02/indeed-mph/)
		* [Venice: Distributed Key-Value Database at Linkedin](https://engineering.linkedin.com/blog/2017/02/building-venice-with-apache-helix)
	* [Columnar Databases](https://aws.amazon.com/nosql/columnar/)
		* [Cassandra](http://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf)
			* [Cassandra at Instagram](https://www.slideshare.net/DataStax/cassandra-at-instagram-2016)
			* [Storing Images in Cassandra at Walmart](https://medium.com/walmartlabs/building-object-store-storing-images-in-cassandra-walmart-scale-a6b9c02af593)
			* [Storing Messages with Cassandra at Discord](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7)
			* [Scaling Cassandra Cluster at Walmart](https://medium.com/walmartlabs/avoid-pitfalls-in-scaling-your-cassandra-cluster-lessons-and-remedies-a71ca01f8c04)
			* [Scaling Ad Analytics with Cassandra at Yelp](https://engineeringblog.yelp.com/2016/08/how-we-scaled-our-ad-analytics-with-cassandra.html)
			* [Scaling 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)
			* [Service Decomposition at Scale with Cassandra at Intuit QuickBooks](https://quickbooks-engineering.intuit.com/service-decomposition-at-scale-70405ac2f637)
			* [Cassandra for Keeping Counts In Sync at SoundCloud](https://developers.soundcloud.com/blog/keeping-counts-in-sync)
			* [Cassandra Driver Configuration for Improved Performance and Load Balancing at Glassdoor](https://medium.com/glassdoor-engineering/cassandra-driver-configuration-for-improved-performance-and-load-balancing-1b0106ce12bb)
			* [cstar: Cassandra Orchestration Tool at Spotify](https://labs.spotify.com/2018/09/04/introducing-cstar-the-spotify-cassandra-orchestration-tool-now-open-source/)
		* [HBase](https://hbase.apache.org/)
			* [HBase at Salesforce](https://engineering.salesforce.com/investing-in-big-data-apache-hbase-b9d98661a66b)
			* [HBase in Facebook Messages](https://www.facebook.com/notes/facebook-engineering/the-underlying-technology-of-messages/454991608919/)
			* [HBase in Imgur Notification](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)
			* [HBase at Xiaomi](https://www.slideshare.net/HBaseCon/hbase-practice-at-xiaomi)
		* [Redshift](https://www.allthingsdistributed.com/2018/11/amazon-redshift-performance-optimization.html)
			* [Redshift at GIPHY](https://engineering.giphy.com/scaling-redshift-without-scaling-costs/)
			* [Redshift at Hudl](https://www.hudl.com/bits/the-low-hanging-fruit-of-redshift-performance)
			* [Redshift at Drivy](https://drivy.engineering/redshift_tips_ticks_part_1/)
	* [Document Databases](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)
		* [Espresso: Distributed Document Store at LinkedIn](https://engineering.linkedin.com/espresso/introducing-espresso-linkedins-hot-new-distributed-document-store)
	* [Graph Databases](https://www.eecs.harvard.edu/margo/papers/systor13-bench/)
		* [FlockDB: Distributed Graph Database at Twitter](https://blog.twitter.com/engineering/en_us/a/2010/introducing-flockdb.html)
		* [TAO: Distributed Data Store for the Social Graph at Facebook](https://www.cs.cmu.edu/~pavlo/courses/fall2013/static/papers/11730-atc13-bronson.pdf)
		* [Akutan: Distributed Knowledge Graph Store at eBay](https://tech.ebayinc.com/engineering/akutan-a-distributed-knowledge-graph-store/)
* [Time Series Databases](https://www.influxdata.com/time-series-database/)
	* [Beringei: High-performance Time Series Storage Engine at Facebook](https://code.facebook.com/posts/952820474848503/beringei-a-high-performance-time-series-storage-engine/)
	* [MetricsDB: TimeSeries Database for storing metrics at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/metricsdb.html)	
	* [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)
	* [Goku: Time Series Database at Pinterest](https://medium.com/@Pinterest_Engineering/goku-building-a-scalable-and-high-performant-time-series-database-system-a8ff5758a181)
	* [Scaling Time Series Data Storage (2 parts) at Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-ii-d67939655586)
	* [Time Series Data Abstraction Layer at Netflix](https://netflixtechblog.com/introducing-netflix-timeseries-data-abstraction-layer-31552f6326f8)
	* [Druid - Real-time Analytics Database](https://druid.apache.org/)
		* [Druid at Airbnb](https://medium.com/airbnb-engineering/druid-airbnb-data-platform-601c312f2a4c)
		* [Druid at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)
		* [Druid at eBay](https://tech.ebayinc.com/engineering/monitoring-at-ebay-with-druid/)
		* [Druid at Netflix](https://netflixtechblog.com/how-netflix-uses-druid-for-real-time-insights-to-ensure-a-high-quality-experience-19e1e8568d06)
* [Distributed Repositories, Dependencies, and Configurations Management](https://betterexplained.com/articles/intro-to-distributed-version-control-illustrated/)
	* [DGit: Distributed Git at Github](https://githubengineering.com/introducing-dgit/)
	* [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 Repository at Microsoft](https://blogs.msdn.microsoft.com/bharry/2017/05/24/the-largest-git-repo-on-the-planet/)
	* [Solve Git Problem with Large Repositories at Microsoft](https://www.infoq.com/news/2017/02/GVFS)	
	* [Single Repository at Google](https://cacm.acm.org/magazines/2016/7/204032-why-google-stores-billions-of-lines-of-code-in-a-single-repository/fulltext)	
	* [Scaling Infrastructure and (Git) Workflow at Adyen](https://medium.com/adyen/from-0-100-billion-scaling-infrastructure-and-workflow-at-adyen-7b63b690dfb6)	
	* [Dotfiles Distribution at Booking.com](https://medium.com/booking-com-infrastructure/dotfiles-distribution-dedb69c66a75)
	* [Secret Detector: Preventing Secrets in Source Code at Yelp](https://engineeringblog.yelp.com/2018/06/yelps-secret-detector.html)
	* [Managing Software Dependency at Scale at LinkedIn](https://engineering.linkedin.com/blog/2018/09/managing-software-dependency-at-scale)
	* [Merging Code in High-velocity Repositories at LinkedIn](https://engineering.linkedin.com/blog/2020/continuous-integration)
	* [Dynamic Configuration at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/dynamic-configuration-at-twitter.html)
	* [Dynamic Configuration at Mixpanel](https://medium.com/mixpaneleng/dynamic-configuration-at-mixpanel-94bfcf97d6b8)
	* [Dynamic Configuration at GoDaddy](https://sg.godaddy.com/engineering/2019/03/06/dynamic-configuration-for-nodejs/)
	* [Fleet Management (3 parts) at Spotify](https://engineering.atspotify.com/2023/5/fleet-management-at-spotify-part-3-fleet-wide-refactoring)
* [Scaling Continuous Integration and Continuous Delivery](https://www.synopsys.com/blogs/software-security/agile-cicd-devops-glossary/)
	* [Continuous Integration Stack at Facebook](https://code.fb.com/web/rapid-release-at-massive-scale/)
	* [Continuous Integration with Distributed Repositories and Dependencies at Netflix](https://medium.com/netflix-techblog/towards-true-continuous-integration-distributed-repositories-and-dependencies-2a2e3108c051)
	* [Continuous Integration and Deployment with Bazel at Dropbox](https://dropbox.tech/infrastructure/continuous-integration-and-deployment-with-bazel)
	* [Adopting Bazel for Web at Airbnb](https://medium.com/airbnb-engineering/adopting-bazel-for-web-at-scale-a784b2dbe325)
	* [Continuous Deployments at BuzzFeed](https://tech.buzzfeed.com/continuous-deployments-at-buzzfeed-d171f76c1ac4)
	* [Screwdriver: Continuous Delivery Build System for Dynamic Infrastructure at Yahoo](https://yahooeng.tumblr.com/post/155765242061/open-sourcing-screwdriver-yahoos-continuous)
	* [CI/CD at Betterment](https://www.betterment.com/resources/ci-cd-shortening-the-feedback-loop/)
	* [CI/CD at Brainly](https://medium.com/engineering-brainly/ci-cd-at-scale-fdfb0f49e031)
	* [Scaling iOS CI with Anka at Shopify](https://engineering.shopify.com/blogs/engineering/scaling-ios-ci-with-anka)
	* [Scaling Jira Server at Yelp](https://engineeringblog.yelp.com/2019/04/Scaling-Jira-Server-Administration-For-The-Enterprise.html)
	* [Auto-scaling CI/CD cluster at Flexport](https://flexport.engineering/how-flexport-halved-testing-costs-with-an-auto-scaling-ci-cd-cluster-8304297222f)

## Availability
* [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://quoraengineering.quora.com/Ensuring-Quoras-Resilience-to-Disaster)
	* [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)
	* [Resiliency and Disaster Recovery with Kafka at eBay](https://tech.ebayinc.com/engineering/resiliency-and-disaster-recovery-with-kafka/)
	* [Disaster Recovery for Multi-Region Kafka at Uber](https://eng.uber.com/kafka/)
* [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/)
	* [ELB for Automatic Failover at GoSquared](https://engineering.gosquared.com/use-elb-automatic-failover)
	* [Eliminate the Database for Higher Availability at American Express](http://americanexpress.io/eliminate-the-database-for-higher-availability/)
	* [Failover with Redis Sentinel at Vinted](http://engineering.vinted.com/2015/09/03/failover-with-redis-sentinel/)
	* [High-availability SaaS Infrastructure at FreeAgent](http://engineering.freeagent.com/2017/02/06/ha-infrastructure-without-breaking-the-bank/)
	* [MySQL High Availability at GitHub](https://github.blog/2018-06-20-mysql-high-availability-at-github/)
	* [MySQL High Availability at Eventbrite](https://www.eventbrite.com/engineering/mysql-high-availability-at-eventbrite/)
	* [Business Continuity & Disaster Recovery at Walmart](https://medium.com/walmartlabs/business-continuity-disaster-recovery-in-the-microservices-world-ef2adca363df)
* [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)
	* [Top Five (Load Balancing) Scalability Patterns](https://www.f5.com/company/blog/top-five-scalability-patterns)
	* [Load Balancing infrastructure to support more than 1.3 billion users at Facebook](https://www.usenix.org/conference/srecon15europe/program/presentation/shuff)
	* [DHCPLB: DHCP Load Balancer at Facebook](https://code.facebook.com/posts/1734309626831603/dhcplb-an-open-source-load-balancer/)
	* [Katran: Scalable Network Load Balancer at Facebook](https://code.facebook.com/posts/1906146702752923/open-sourcing-katran-a-scalable-network-load-balancer/)
	* [Deterministic Aperture: A Distributed, Load Balancing Algorithm at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/daperture-load-balancer.html)	
	* [Load Balancing with Eureka at Netflix](https://medium.com/netflix-techblog/netflix-shares-cloud-load-balancing-and-failover-tool-eureka-c10647ef95e5)
	* [Edge Load Balancing at Netflix](https://medium.com/netflix-techblog/netflix-edge-load-balancing-695308b5548c)
	* [Zuul 2: Cloud Gateway at Netflix](https://medium.com/netflix-techblog/open-sourcing-zuul-2-82ea476cb2b3)
	* [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/)	
	* [Traffic Steering using Rum DNS at LinkedIn](https://www.usenix.org/conference/srecon17europe/program/presentation/rastogi)
	* [Traffic Infrastructure (Edge Network) at Dropbox](https://dropbox.tech/infrastructure/dropbox-traffic-infrastructure-edge-network)
	* [Intelligent DNS based load balancing at Dropbox](https://dropbox.tech/infrastructure/intelligent-dns-based-load-balancing-at-dropbox)
	* [Monitor DNS systems at Stripe](https://stripe.com/en-sg/blog/secret-life-of-dns)
	* [Multi-DNS Architecture (3 parts) at Monday](https://medium.com/monday-engineering/how-and-why-we-migrated-our-dns-from-cloudflare-to-a-multi-dns-architecture-part-3-584a470f4062)
	* [Dynamic Anycast DNS Infrastructure at Hulu](https://medium.com/hulu-tech-blog/building-hulus-dynamic-anycast-dns-infrastructure-985a7a11fd30)
* [Rate Limiting](https://www.keycdn.com/support/rate-limiting/)
	* [Rate Limiting for Scaling to Millions of Domains at Cloudflare](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)
	* [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)
	* [Quotas Service at Grab](https://engineering.grab.com/quotas-service)
	* [Rate Limiting at Figma](https://medium.com/figma-design/an-alternative-approach-to-rate-limiting-f8a06cf7c94c)	
* [Autoscaling](https://medium.com/@BotmetricHQ/top-11-hard-won-lessons-learned-about-aws-auto-scaling-5bfe56da755f)
	* [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 Jenkins at Trivago](http://tech.trivago.com/2017/02/17/your-definite-guide-for-autoscaling-jenkins/)
	* [Autoscaling Pub-Sub Consumers at Spotify](https://labs.spotify.com/2017/11/20/autoscaling-pub-sub-consumers/)
	* [Autoscaling Bigtable Clusters based on CPU Load at Spotify](https://labs.spotify.com/2018/12/18/bigtable-autoscaler-saving-money-and-time-using-managed-storage/)
	* [Autoscaling AWS Step Functions Activities at Yelp](https://engineeringblog.yelp.com/2019/06/autoscaling-aws-step-functions-activities.html)
	* [Scryer: Predictive Auto Scaling Engine at Netflix](https://medium.com/netflix-techblog/scryer-netflixs-predictive-auto-scaling-engine-a3f8fc922270)	
	* [Bouncer: Simple AWS Auto Scaling Rollovers at Palantir](https://medium.com/palantir/bouncer-simple-aws-auto-scaling-rollovers-c5af601d65d4)
	* [Clusterman: Autoscaling Mesos Clusters at Yelp](https://engineeringblog.yelp.com/2019/02/autoscaling-mesos-clusters-with-clusterman.html)
* [Availability in Globally Distributed Storage Systems at Google](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)
* [Operations (11 parts) at LinkedIn](https://www.linkedin.com/pulse/introduction-every-day-monday-operations-benjamin-purgason)
* [Monitoring Powers High Availability for LinkedIn Feed](https://www.usenix.org/conference/srecon17americas/program/presentation/barot)
* [Supporting Global Events at Facebook](https://code.facebook.com/posts/166966743929963/how-production-engineers-support-global-events-on-facebook/)
* [High Availability at BlaBlaCar](https://medium.com/blablacar-tech/the-expendables-backends-high-availability-at-blablacar-8cea3b95b26b)
* [High Availability at Netflix](https://medium.com/@NetflixTechBlog/tips-for-high-availability-be0472f2599c)
* [High Availability Cloud Infrastructure at Twilio](https://www.twilio.com/engineering/2011/12/12/scaling-high-availablity-infrastructure-in-cloud)
* [High Availability with Distributed DB on Kubernetes at Airbnb](https://airbnb.tech/infrastructure/achieving-high-availability-with-distributed-database-on-kubernetes-at-airbnb/)
* [Automating Datacenter Operations at Dropbox](https://dropbox.tech/infrastructure/automating-datacenter-operations-at-dropbox)
* [Globalizing Player Accounts at Riot Games](https://technology.riotgames.com/news/globalizing-player-accounts)

## Stability
* [Circuit Breaker](https://martinfowler.com/bliki/CircuitBreaker.html)
	* [Circuit Breaking in Distributed Systems](https://www.infoq.com/presentations/circuit-breaking-distributed-systems)
	* [Circuit Breaker for Scaling Containers](https://f5.com/about-us/blog/articles/the-art-of-scaling-containers-circuit-breakers-28919)
	* [Lessons in Resilience at SoundCloud](https://developers.soundcloud.com/blog/lessons-in-resilience-at-SoundCloud)
	* [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)
	* [Circuit Breaker at Zendesk](https://medium.com/zendesk-engineering/the-joys-of-circuit-breaking-ee6584acd687)
	* [Circuit Breaker at Traveloka](https://medium.com/traveloka-engineering/circuit-breakers-dont-let-your-dependencies-bring-you-down-5ba1c5cf1eec)
	* [Circuit Breaker at Shopify](https://shopify.engineering/circuit-breaker-misconfigured)
* [Timeouts](https://www.javaworld.com/article/2824163/application-performance/stability-patterns-applied-in-a-restful-architecture.html)
	* [Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Netflix](https://medium.com/netflix-techblog/fault-tolerance-in-a-high-volume-distributed-system-91ab4faae74a)
	* [Enforce Timeout: A Reliability Methodology at DoorDash](https://doordash.engineering/2018/12/21/enforce-timeout-a-doordash-reliability-methodology/)
	* [Troubleshooting a Connection Timeout Issue with tcp_tw_recycle Enabled at eBay](https://www.ebayinc.com/stories/blogs/tech/a-vip-connection-timeout-issue-caused-by-snat-and-tcp-tw-recycle/)
* [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)
* [Determinism (4 parts) in League of Legends Server](https://engineering.riotgames.com/news/determinism-league-legends-fixing-divergences)

## Performance
* [Performance Optimization on OS, Storage, Database, 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)
	* [Fixing Linux filesystem performance regressions at LinkedIn](https://engineering.linkedin.com/blog/2020/fixing-linux-filesystem-performance-regressions)
	* [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://dropbox.tech/infrastructure/optimizing-web-servers-for-high-throughput-and-low-latency)
	* [Linux Performance Analysis in 60.000 Milliseconds at Netflix](https://medium.com/netflix-techblog/linux-performance-analysis-in-60-000-milliseconds-accc10403c55)
	* [Live Downsizing Google Cloud Persistent Disks (PD-SSD) at Mixpanel](https://engineering.mixpanel.com/2018/07/31/live-downsizing-google-cloud-pds-for-fun-and-profit/)
	* [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)
	* [Continuous Load Testing at Slack](https://slack.engineering/continuous-load-testing/)
	* [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 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/)
	* [Profiling C++ (Part 1: Optimization, Part 2: Measurement and Analysis) at Riot Games](https://engineering.riotgames.com/news/profiling-optimisation)
	* [Profiling React Server-Side Rendering at HomeAway](https://medium.com/homeaway-tech-blog/profiling-react-server-side-rendering-to-free-the-node-js-event-loop-7f0fe455a901)
	* [Hardware-Assisted Video Transcoding at Dailymotion](https://medium.com/dailymotion-engineering/hardware-assisted-video-transcoding-at-dailymotion-66cd2db448ae)
	* [Cross Shard Transactions at 10 Million RPS at Dropbox](https://dropbox.tech/infrastructure/cross-shard-transactions-at-10-million-requests-per-second)
	* [API Profiling at Pinterest](https://medium.com/@Pinterest_Engineering/api-profiling-at-pinterest-6fa9333b4961)
	* [Pagelets Parallelize Server-side Processing at Yelp](https://engineeringblog.yelp.com/2017/07/generating-web-pages-in-parallel-with-pagelets.html)
	* [Improving key expiration in Redis at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/improving-key-expiration-in-redis.html)
	* [Ad Delivery Network Performance Optimization with Flame Graphs at MindGeek](https://medium.com/mindgeek-engineering-blog/ad-delivery-network-performance-optimization-with-flame-graphs-bc550cf59cf7)
	* [Predictive CPU isolation of containers at Netflix](https://medium.com/netflix-techblog/predictive-cpu-isolation-of-containers-at-netflix-91f014d856c7)
	* [Improving HDFS I/O Utilization for Efficiency at Uber](https://eng.uber.com/improving-hdfs-i-o-utilization-for-efficiency/)
	* [Cloud Jewels: Estimating kWh in the Cloud at Etsy](https://codeascraft.com/2020/04/23/cloud-jewels-estimating-kwh-in-the-cloud/)
	* [Unthrottled: Fixing CPU Limits in the Cloud (2 parts) at Indeed](https://engineering.indeedblog.com/blog/2019/12/unthrottled-fixing-cpu-limits-in-the-cloud/)
* [Performance Optimization by Tuning Garbage Collection](https://confluence.atlassian.com/enterprise/garbage-collection-gc-tuning-guide-461504616.html)
	* [Garbage Collection in Java Applications at LinkedIn](https://engineering.linkedin.com/garbage-collection/garbage-collection-optimization-high-throughput-and-low-latency-java-applications)
	* [Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe](https://medium.com/adobetech/engineering-high-throughput-low-latency-machine-learning-services-7d45edac0271)
	* [Garbage Collection in Redux Applications at SoundCloud](https://developers.soundcloud.com/blog/garbage-collection-in-redux-applications)
	* [Garbage Collection in Go Application at Twitch](https://blog.twitch.tv/go-memory-ballast-how-i-learnt-to-stop-worrying-and-love-the-heap-26c2462549a2)
	* [Analyzing V8 Garbage Collection Logs at Alibaba](https://www.linux.com/blog/can-nodejs-scale-ask-team-alibaba)
	* [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 Impact of Removing Out of Band Garbage Collector (OOBGC) at Github](https://githubengineering.com/removing-oobgc/)
	* [Debugging Java Memory Leaks at Allegro](https://allegro.tech/2018/05/a-comedy-of-errors-debugging-java-memory-leaks.html)
	* [Optimizing JVM at Alibaba](https://www.youtube.com/watch?v=X4tmr3nhZRg)
	* [Tuning JVM Memory for Large-scale Services at Uber](https://eng.uber.com/jvm-tuning-garbage-collection/)
	* [Solr Performance Tuning at Walmart](https://medium.com/walmartglobaltech/solr-performance-tuning-beb7d0d0f8d9)
	* [Memory Tuning a High Throughput Microservice at Flipkart](https://blog.flipkart.tech/memory-tuning-a-high-throughput-microservice-ed57b3e60997)
* [Performance Optimization on Image, Video, 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)
	* [Adaptive Video Streaming at YouTube](https://youtube-eng.googleblog.com/2018/04/making-high-quality-video-efficient.html)
    * [Reducing Video Loading Time at Dailymotion](https://medium.com/dailymotion/reducing-video-loading-time-fa9c997a2294)
	* [Improving Homepage Performance at Zillow](https://www.zillow.com/engineering/improving-homepage-performance/)
	* [The Process of Optimizing for Client Performance at Expedia](https://medium.com/expedia-engineering/go-fast-or-go-home-the-process-of-optimizing-for-client-performance-57bb497402e)
	* [Web Performance at BBC](https://medium.com/bbc-design-engineering/bbc-world-service-web-performance-26b08f7abfcc)
* [Performance Optimization by Brotli Compression](https://blogs.akamai.com/2016/02/understanding-brotlis-potential.html)
	* [Boosting Site Speed Using Brotli Compression at LinkedIn](https://engineering.linkedin.com/blog/2017/05/boosting-site-speed-using-brotli-compression)	
	* [Brotli at Booking.com](https://medium.com/booking-com-development/bookings-journey-with-brotli-978b249d34f3)
	* [Brotli at Treebo](https://tech.treebo.com/a-tale-of-brotli-compression-bcb071d9780a)
	* [Deploying Brotli for Static Content at Dropbox](https://dropbox.tech/infrastructure/deploying-brotli-for-static-content)
	* [Progressive Enhancement with Brotli at Yelp](https://engineeringblog.yelp.com/2017/07/progressive-enhancement-with-brotli.html)
	* [Speeding Up Redis with Compression at DoorDash](https://doordash.engineering/2019/01/02/speeding-up-redis-with-compression/)
* [Performance Optimization on Languages and Frameworks](https://www.techempower.com/benchmarks/)
	* [Python at Netflix](https://netflixtechblog.com/python-at-netflix-bba45dae649e)
	* [Python at scale (3 parts) at Instagram](https://instagram-engineering.com/python-at-scale-strict-modules-c0bb9245c834)
	* [OCaml best practices (2 parts) at Issuu](https://engineering.issuu.com/2018/12/10/our-current-ocaml-best-practices-part-2)
	* [PHP at Slack](https://slack.engineering/taking-php-seriously-cf7a60065329)
	* [Go at Trivago](https://tech.trivago.com/2020/03/02/why-we-chose-go/)
	* [TypeScript at Etsy](https://codeascraft.com/2021/11/08/etsys-journey-to-typescript/)
	* [Kotlin for taming state at Etsy](https://www.etsy.com/sg-en/codeascraft/sealed-classes-opened-my-mind)
	* [Kotlin at DoorDash](https://doordash.engineering/2022/03/22/how-to-leverage-functional-programming-in-kotlin-to-write-better-cleaner-code/)
	* [BPF and Go at Bumble](https://medium.com/bumble-tech/bpf-and-go-modern-forms-of-introspection-in-linux-6b9802682223)
	* [Ruby on Rails at GitLab](https://medium.com/gitlab-magazine/why-we-use-ruby-on-rails-to-build-gitlab-601dce4a7a38)
	* [Rust in production at Figma](https://medium.com/figma-design/rust-in-production-at-figma-e10a0ec31929)
	* [Choosing a Language Stack at WeWork](https://engineering.wework.com/choosing-a-language-stack-cac3726928f6)
	* [Switching from Go to Rust at Discord](https://blog.discord.com/why-discord-is-switching-from-go-to-rust-a190bbca2b1f)
	* [ASP.NET Core Performance Optimization at Agoda](https://medium.com/agoda-engineering/happy-asp-net-core-performance-optimization-4e21a383d299)
	* [Data Race Patterns in Go at Uber](https://eng.uber.com/data-race-patterns-in-go/)
	* [Java 21 Virtual Threads at Netflix](https://netflixtechblog.com/java-21-virtual-threads-dude-wheres-my-lock-3052540e231d)	
    
## Intelligence
* [Big Data](https://insights.sei.cmu.edu/sei_blog/2017/05/reference-architectures-for-big-data-systems.html)	
	* [Data Platform at Uber](https://eng.uber.com/uber-big-data-platform/)
	* [Data Platform at BMW](https://www.unibw.de/code/events-u/jt-2018-workshops/ws3_bigdata_vortrag_widmann.pdf)
	* [Data Platform at Netflix](https://www.youtube.com/watch?v=CSDIThSwA7s)
	* [Data Platform at Flipkart](https://blog.flipkart.tech/overview-of-flipkart-data-platform-20c6d3e9a196)
	* [Data Platform at Coupang](https://medium.com/coupang-tech/evolving-the-coupang-data-platform-308e305a9c45)
	* [Data Platform at DoorDash](https://doordash.engineering/2020/09/25/how-doordash-is-scaling-its-data-platform/)
	* [Data Platform at Khan Academy](http://engineering.khanacademy.org/posts/khanalytics.htm)
	* [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)
	* [Data Orchestration Service at Spotify](https://engineering.atspotify.com/2022/03/why-we-switched-our-data-orchestration-service/)
	* [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)
	* [Analytics Pipeline at Grammarly](https://tech.grammarly.com/blog/building-a-versatile-analytics-pipeline-on-top-of-apache-spark)
	* [Analytics Pipeline at Teads](https://medium.com/teads-engineering/give-meaning-to-100-billion-analytics-events-a-day-d6ba09aa8f44)
	* [ML Data Pipelines for Real-Time Fraud Prevention at PayPal](https://www.infoq.com/presentations/paypal-ml-fraud-prevention-2018)
	* [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)
	* [Privacy-Preserving Analytics and Reporting at LinkedIn](https://engineering.linkedin.com/blog/2019/04/privacy-preserving-analytics-and-reporting-at-linkedin)
	* [Analytics Platform for Tracking Item Availability at Walmart](https://medium.com/walmartlabs/how-we-build-a-robust-analytics-platform-using-spark-kafka-and-cassandra-lambda-architecture-70c2d1bc8981)
	* [Real-Time Analytics for Mobile App Crashes using Apache Pinot at Uber](https://www.uber.com/en-SG/blog/real-time-analytics-for-mobile-app-crashes/)
	* [HALO: Hardware Analytics and Lifecycle Optimization at Facebook](https://code.fb.com/data-center-engineering/hardware-analytics-and-lifecycle-optimization-halo-at-facebook/)
	* [RBEA: Real-time Analytics Platform at King](https://techblog.king.com/rbea-scalable-real-time-analytics-king/)
	* [AresDB: GPU-Powered Real-time Analytics Engine at Uber](https://eng.uber.com/aresdb/)
	* [AthenaX: Streaming Analytics Platform at Uber](https://eng.uber.com/athenax/)
	* [Jupiter: Config Driven Adtech Batch Ingestion Platform at Uber](https://www.uber.com/en-SG/blog/jupiter-batch-ingestion-platform/)
	* [Delta: Data Synchronization and Enrichment Platform at Netflix](https://medium.com/netflix-techblog/delta-a-data-synchronization-and-enrichment-platform-e82c36a79aee)
	* [Keystone: Real-time Stream Processing Platform at Netflix](https://medium.com/netflix-techblog/keystone-real-time-stream-processing-platform-a3ee651812a)
	* [Databook: Turning Big Data into Knowledge with Metadata at Uber](https://eng.uber.com/databook/)
	* [Amundsen: Data Discovery & Metadata Engine at Lyft](https://eng.lyft.com/amundsen-lyfts-data-discovery-metadata-engine-62d27254fbb9)
	* [Maze: Funnel Visualization Platform at Uber](https://eng.uber.com/maze/)
	* [Metacat: Making Big Data Discoverable and Meaningful at Netflix](https://medium.com/netflix-techblog/metacat-making-big-data-discoverable-and-meaningful-at-netflix-56fb36a53520)
	* [SpinalTap: Change Data Capture System at Airbnb](https://medium.com/airbnb-engineering/capturing-data-evolution-in-a-service-oriented-architecture-72f7c643ee6f)
	* [Accelerator: Fast Data Processing Framework at eBay](https://www.ebayinc.com/stories/blogs/tech/announcing-the-accelerator-processing-1-000-000-000-lines-per-second-on-a-single-computer/)
	* [Omid: Transaction Processing Platform at Yahoo](https://yahooeng.tumblr.com/post/180867271141/a-new-chapter-for-omid)
	* [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)
	* [Spark on Scala: Analytics Reference Architecture at Adobe](https://medium.com/adobetech/spark-on-scala-adobe-analytics-reference-architecture-7457f5614b4c)
	* [Experimentation Platform (2 parts) at Spotify](https://engineering.atspotify.com/2020/11/02/spotifys-new-experimentation-platform-part-2/)
	* [Experimentation Platform at Airbnb](https://medium.com/airbnb-engineering/https-medium-com-jonathan-parks-scaling-erf-23fd17c91166)
	* [Smart Product Platform at Zalando](https://engineering.zalando.com/posts/2017/10/zalando-smart-product-platform.html)
	* [Log Analysis Platform at LINE](https://www.slideshare.net/wyukawa/strata2017-sg)
	* [Data Visualisation Platform at Myntra](https://medium.com/myntra-engineering/universal-dashboarding-platform-udp-data-visualisation-platform-at-myntra-5f2522fcf72d)
	* [Building and Scaling Data Lineage at Netflix](https://medium.com/netflix-techblog/building-and-scaling-data-lineage-at-netflix-to-improve-data-infrastructure-reliability-and-1a52526a7977)
	* [Building a scalable data management system for computer vision tasks at Pinterest](https://medium.com/@Pinterest_Engineering/building-a-scalable-data-management-system-for-computer-vision-tasks-a6dee8f1c580)
	* [Structured Data at Etsy](https://codeascraft.com/2019/07/31/an-introduction-to-structured-data-at-etsy/)
	* [Scaling a Mature Data Pipeline - Managing Overhead at Airbnb](https://medium.com/airbnb-engineering/scaling-a-mature-data-pipeline-managing-overhead-f34835cbc866)
	* [Spark Partitioning Strategies at Airbnb](https://medium.com/airbnb-engineering/on-spark-hive-and-small-files-an-in-depth-look-at-spark-partitioning-strategies-a9a364f908)
	* [Scaling the Hadoop Distributed File System at LinkedIn](https://engineering.linkedin.com/blog/2021/the-exabyte-club--linkedin-s-journey-of-scaling-the-hadoop-distr)
	* [Scaling Hadoop YARN cluster beyond 10,000 nodes at LinkedIn](https://engineering.linkedin.com/blog/2021/scaling-linkedin-s-hadoop-yarn-cluster-beyond-10-000-nodes)
	* [Scaling Big Data Access Controls at Pinterest](https://medium.com/pinterest-engineering/securely-scaling-big-data-access-controls-at-pinterest-bbc3406a1695)
* [Distributed Machine Learning](https://www.csie.ntu.edu.tw/~cjlin/talks/bigdata-bilbao.pdf)
	* [Machine Learning Platform at Yelp](https://engineeringblog.yelp.com/2020/07/ML-platform-overview.html)
	* [Machine Learning Platform at Etsy](https://codeascraft.com/2021/12/21/redesigning-etsys-machine-learning-platform/)
	* [Machine Learning Platform at Zalando](https://engineering.zalando.com/posts/2022/04/zalando-machine-learning-platform.html)
	* [Scaling AI/ML Infrastructure at Uber](https://www.uber.com/en-SG/blog/scaling-ai-ml-infrastructure-at-uber/)
	* [Recommendation System at Lyft](https://eng.lyft.com/the-recommendation-system-at-lyft-67bc9dcc1793)
	* [Reinforcement Learning Platform at Lyft](https://eng.lyft.com/lyfts-reinforcement-learning-platform-670f77ff46ec)
	* [Platform for Serving Recommendations at Etsy](https://www.etsy.com/sg-en/codeascraft/building-a-platform-for-serving-recommendations-at-etsy)
	* [Infrastructure to Run User Forecasts at Spotify](https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/)
	* [Aroma: Using ML for Code Recommendation at Facebook](https://code.fb.com/developer-tools/aroma/)
	* [Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft](https://eng.lyft.com/introducing-flyte-cloud-native-machine-learning-and-data-processing-platform-fb2bb3046a59)
	* [LyftLearn: ML Model Training Infrastructure built on Kubernetes at Lyft](https://eng.lyft.com/lyftlearn-ml-model-training-infrastructure-built-on-kubernetes-aef8218842bb)
	* [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/)
	* [Genie: Gen AI On-Call Copilot at Uber](https://www.uber.com/blog/genie-ubers-gen-ai-on-call-copilot/)
	* [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/)
	* [Manifold: Model-Agnostic Visual Debugging Tool for Machine Learning at Uber](https://eng.uber.com/manifold/)	
	* [Repo-Topix: Topic Extraction Framework at Github](https://githubengineering.com/topics/)
	* [Concourse: Generating Personalized Content Notifications in Near-Real-Time at LinkedIn](https://engineering.linkedin.com/blog/2018/05/concourse--generating-personalized-content-notifications-in-near)
	* [Altus Care: Applying a Chatbot to Platform Engineering at eBay](https://www.ebayinc.com/stories/blogs/tech/altus-care-apply-chatbot-to-ebay-platform-engineering/)
	* [PyKrylov: Accelerating Machine Learning Research at eBay](https://tech.ebayinc.com/engineering/pykrylov-accelerating-machine-learning-research-at-ebay/)
	* [Box Graph: Spontaneous Social Network at Box](https://blog.box.com/blog/box-graph-how-we-built-spontaneous-social-network/)
	* [PricingNet: Pricing Modelling with Neural Networks at Skyscanner](https://hackernoon.com/pricingnet-modelling-the-global-airline-industry-with-neural-networks-833844d20ea6)
	* [PinText: Multitask Text Embedding System at Pinterest](https://medium.com/pinterest-engineering/pintext-a-multitask-text-embedding-system-in-pinterest-b80ece364555)
	* [SearchSage: Learning Search Query Representations at Pinterest](https://medium.com/pinterest-engineering/searchsage-learning-search-query-representations-at-pinterest-654f2bb887fc)
	* [Cannes: ML saves $1.7M a year on document previews at Dropbox](https://dropbox.tech/machine-learning/cannes--how-ml-saves-us--1-7m-a-year-on-document-previews)
	* [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)
	* [Moderating Inappropriate Video Content at Yelp](https://engineeringblog.yelp.com/2024/03/moderating-inappropriate-video-content-at-yelp.html)
	* [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/)
	* [Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor](https://www.tripadvisor.com/engineering/personalized-recommendations-for-experiences-using-deep-learning/)
	* [Personalised Recommender Systems at BBC](https://medium.com/bbc-design-engineering/developing-personalised-recommender-systems-at-the-bbc-e26c5e0c4216)
	* [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection)
	* [Natural Language Processing and Content Analysis (2 parts) at Condé Nast](https://technology.condenast.com/story/natural-language-processing-and-content-analysis-at-conde-nast-part-2-system-architecture)
	* [Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio](https://tech.iheart.com/mapping-the-world-of-music-using-machine-learning-part-2-aa50b6a0304c)
	* [Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f)
	* [Machine Learning to Match Drivers & Riders at GO-JEK](https://blog.gojekengineering.com/how-we-use-machine-learning-to-match-drivers-riders-b06d617b9e5)
	* [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://engineering.zalando.com/posts/2018/02/search-deep-neural-network.html)
	* [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://quoraengineering.quora.com/A-Machine-Learning-Approach-to-Ranking-Answers-on-Quora)
	* [Ranking Platform at Booking.com](https://medium.com/booking-com-development/the-engineering-behind-booking-coms-ranking-platform-a-system-overview-2fb222003ca6)
	* [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)
	* [Mapping Tags at Medium](https://medium.engineering/mapping-mediums-tags-1b9a78d77cf0)
	* [Clustering with the Dirichlet Process Mixture Model in Scala at Monsanto](http://engineering.monsanto.com/2015/11/23/chinese-restaurant-process/)
	* [Map Pins with DBSCAN & Random Forests at Foursquare](https://engineering.foursquare.com/you-are-probably-here-better-map-pins-with-dbscan-random-forests-9d51e8c1964d)
	* [Forecasting at Uber](https://eng.uber.com/forecasting-introduction/)
	* [Financial Forecasting at Uber](https://eng.uber.com/transforming-financial-forecasting-machine-learning/)
	* [Productionizing ML with Workflows at Twitter](https://blog.twitter.com/engineering/en_us/topics/insights/2018/ml-workflows.html)
	* [GUI Testing Powered by Deep Learning at eBay](https://www.ebayinc.com/stories/blogs/tech/gui-testing-powered-by-deep-learning/)
	* [Scaling Machine Learning to Recommend Driving Routes at Pivotal](http://engineering.pivotal.io/post/scaling-machine-learning-to-recommend-driving-routes/)
	* [Real-Time Predictions at DoorDash](https://www.infoq.com/presentations/doordash-real-time-predictions)
	* [Machine Learning for Indexing Text from Billions of Images at Dropbox](https://dropbox.tech/machine-learning/using-machine-learning-to-index-text-from-billions-of-images)
	* [Modeling User Journeys via Semantic Embeddings at Etsy](https://codeascraft.com/2018/07/12/modeling-user-journey-via-semantic-embeddings/)
	* [Automated Fake Account Detection at LinkedIn](https://engineering.linkedin.com/blog/2018/09/automated-fake-account-detection-at-linkedin)
	* [Building Knowledge Graph at Airbnb](https://medium.com/airbnb-engineering/contextualizing-airbnb-by-building-knowledge-graph-b7077e268d5a)
	* [Core Modeling at Instagram](https://instagram-engineering.com/core-modeling-at-instagram-a51e0158aa48)
	* [Neural Architecture Search (NAS) for Prohibited Item Detection at Mercari](https://tech.mercari.com/entry/2019/04/26/163000)
	* [Computer Vision at Airbnb](https://medium.com/airbnb-engineering/amenity-detection-and-beyond-new-frontiers-of-computer-vision-at-airbnb-144a4441b72e)
	* [3D Home Backend Algorithms at Zillow](https://www.zillow.com/engineering/behind-zillow-3d-home-backend-algorithms/)
	* [Long-term Forecasts at Lyft](https://eng.lyft.com/making-long-term-forecasts-at-lyft-fac475b3ba52)
	* [Discovering Popular Dishes with Deep Learning at Yelp](https://engineeringblog.yelp.com/2019/10/discovering-popular-dishes-with-deep-learning.html)
	* [SplitNet Architecture for Ad Candidate Ranking at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/splitnet-architecture-for-ad-candidate-ranking.html)
	* [Jobs Filter at Indeed](https://engineering.indeedblog.com/blog/2019/09/jobs-filter/)
	* [Architecting Restaurant Wait Time Predictions at Yelp](https://engineeringblog.yelp.com/2019/12/architecting-wait-time-estimations.html)
	* [Music Personalization at Spotify](https://labs.spotify.com/2016/08/07/commodity-music-ml-services/)
	* [Deep Learning for Domain Name Valuation at GoDaddy](https://sg.godaddy.com/engineering/2019/07/26/domain-name-valuation/)
	* [Similarity Clustering to Catch Fraud Rings at Stripe](https://stripe.com/blog/similarity-clustering)
	* [Personalized Search at Etsy](https://codeascraft.com/2020/10/29/bringing-personalized-search-to-etsy/)
	* [ML Feature Serving Infrastructure at Lyft](https://eng.lyft.com/ml-feature-serving-infrastructure-at-lyft-d30bf2d3c32a)
	* [Context-Specific Bidding System at Etsy](https://codeascraft.com/2021/03/23/how-we-built-a-context-specific-bidding-system-for-etsy-ads/)
	* [Moderating Promotional Spam and Inappropriate Content in Photos at Scale at Yelp](https://engineeringblog.yelp.com/2021/05/moderating-promotional-spam-and-inappropriate-content-in-photos-at-scale-at-yelp.html)
	* [Optimizing Payments with Machine Learning at Dropbox](https://dropbox.tech/machine-learning/optimizing-payments-with-machine-learning)
	* [Scaling Media Machine Learning at Netflix](https://netflixtechblog.com/scaling-media-machine-learning-at-netflix-f19b400243)
	* [Similarity Engine at eBay](https://tech.ebayinc.com/engineering/ebays-blazingly-fast-billion-scale-vector-similarity-engine/)
	* [Machine Learning in Content Moderation at Etsy](https://www.etsy.com/codeascraft/machine-learning-in-content-moderation-at-etsy)

## Architecture
* [Tech Stack at Medium](https://medium.engineering/the-stack-that-helped-medium-drive-2-6-millennia-of-reading-time-e56801f7c492)
* [Tech Stack at Shopify](https://engineering.shopify.com/blogs/engineering/e-commerce-at-scale-inside-shopifys-tech-stack)
* [Building Services (4 parts) at Airbnb](https://medium.com/airbnb-engineering/building-services-at-airbnb-part-4-23c95e428064)
* [Architecture of Evernote](https://evernote.com/blog/a-digest-of-evernotes-architecture/)
* [Architecture of Chat Service (3 parts) at Riot Games](https://engineering.riotgames.com/news/chat-service-architecture-persistence)
* [Architecture of League of Legends Client Update](https://technology.riotgames.com/news/architecture-league-client-update)
* [Architecture of Ad Platform at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2020/building-twitters-ad-platform-architecture-for-the-future.html)
* [Architecture of API Gateway at Uber](https://eng.uber.com/architecture-api-gateway/)
* [Architecture of API Gateway at Tinder](https://medium.com/tinder/how-we-built-the-tinder-api-gateway-831c6ca5ceca)
* [Basic Architecture of Slack](https://slack.engineering/how-slack-built-shared-channels-8d42c895b19f)
* [Lightweight Distributed Architecture to Handle Thousands of Library Releases at eBay](https://tech.ebayinc.com/engineering/a-lightweight-distributed-architecture-to-handle-thousands-of-library-releases-at-ebay/)
* [Back-end 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)
* [Infrastructure (3 parts) at Zendesk](https://medium.com/zendesk-engineering/the-history-of-infrastructure-at-zendesk-part-3-foundation-team-forming-and-evolving-9859e40f5390)
* [Cloud Infrastructure at Grubhub](https://bytes.grubhub.com/cloud-infrastructure-at-grubhub-94db998a898a)
* [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)
* [Settings Platform at LinkedIn](https://engineering.linkedin.com/blog/2019/05/building-member-trust-through-a-centralized-and-scalable-setting)
* [Nearline System for Scale and Performance (2 parts) at Glassdoor](https://medium.com/glassdoor-engineering/building-a-nearline-system-for-scale-and-performance-part-ii-9e01bf51b23d)
* [Real-time User Action Counting System for Ads at Pinterest](https://medium.com/@Pinterest_Engineering/building-a-real-time-user-action-counting-system-for-ads-88a60d9c9a)
* [API Platform at Riot Games](https://engineering.riotgames.com/news/riot-games-api-deep-dive)
* [Games Platform at The New York Times](https://open.nytimes.com/play-by-play-moving-the-nyt-games-platform-to-gcp-with-zero-downtime-cf425898d569)
* [Kabootar: Communication Platform at Swiggy](https://bytes.swiggy.com/kabootar-swiggys-communication-platform-e5a43cc25629)
* [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)
* [PriceAggregator: Intelligent System for Hotel Price Fetching (3 parts) at Agoda](https://medium.com/agoda-engineering/priceaggregator-an-intelligent-system-for-hotel-price-fetching-part-3-52acfc705081)
* [Phoenix: Testing Platform (3 parts) at Tinder](https://medium.com/tinder-engineering/phoenix-tinders-testing-platform-part-iii-520728b9537)
* [Hexagonal Architecture at Netflix](https://netflixtechblog.com/ready-for-changes-with-hexagonal-architecture-b315ec967749)
* [Architecture of Sticker Services at LINE](https://www.slideshare.net/linecorp/architecture-sustaining-line-sticker-services)
* [Stack Overflow Enterprise at Palantir](https://medium.com/@palantir/terraforming-stack-overflow-enterprise-in-aws-47ee431e6be7)
* [Architecture of Following Feed, Interest Feed, and Picked For You at Pinterest](https://medium.com/@Pinterest_Engineering/building-a-dynamic-and-responsive-pinterest-7d410e99f0a9)
* [API Specification Workflow at WeWork](https://engineering.wework.com/our-api-specification-workflow-9337448d6ee6)
* [Media Database at Netflix](https://medium.com/netflix-techblog/implementing-the-netflix-media-database-53b5a840b42a)
* [Member Transaction History Architecture at Walmart](https://medium.com/walmartlabs/member-transaction-history-architecture-8b6e34b87c21)
* [Sync Engine (2 parts) at Dropbox](https://dropbox.tech/infrastructure/-testing-our-new-sync-engine)
* [Ads Pacing Service at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2021/how-we-built-twitter-s-highly-reliable-ads-pacing-service)
* [Rapid Event Notification System at Netflix](https://netflixtechblog.com/rapid-event-notification-system-at-netflix-6deb1d2b57d1)
* [Architectures of Finance, Banking, and Payment Systems](https://www.redhat.com/architect/portfolio/detail/12-integrating-a-modern-payments-architecture)
	* [Bank Backend at Monzo](https://monzo.com/blog/2016/09/19/building-a-modern-bank-backend/)
	* [Trading Platform for Scale at Wealthsimple](https://medium.com/@Wealthsimple/engineering-at-wealthsimple-reinventing-our-trading-platform-for-scale-17e332241b6c)
	* [Core Banking System at Margo Bank](https://medium.com/margobank/choosing-an-architecture-85750e1e5a03)
	* [Architecture of Nubank](https://www.infoq.com/presentations/nubank-architecture)
	* [Tech Stack at TransferWise](http://tech.transferwise.com/the-transferwise-stack-heartbeat-of-our-little-revolution/)
	* [Tech Stack at Addepar](https://medium.com/build-addepar/our-tech-stack-a4f55dab4b0d)
	* [Avoiding Double Payments in a Distributed Payments System at Airbnb](https://medium.com/airbnb-engineering/avoiding-double-payments-in-a-distributed-payments-system-2981f6b070bb)
	* [Scaling Payments (3 parts) at Etsy](https://www.etsy.com/sg-en/codeascraft/scaling-etsy-payments-with-vitess-part-3--reducing-cutover-risk)
	* [Handles Millions of Digital Transactions Safely Everyday at Paytm](https://paytm.com/blog/engineering/how-paytm-handles-millions-of-digital-transactions-safely-everyday/)
	* [Billing and Payment Platform at Grammarly](https://www.grammarly.com/blog/engineering/billing-and-payments-platform/)

## 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)
	* [Cloud Big Data Design Patterns - Lynn Langit](https://lynnlangit.com/2017/03/14/beyond-relational/)	
	* [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)
	* [API Best Practices: Webhooks, Deprecation, and Design](https://zapier.com/engineering/api-best-practices/)
* [Explaining Low-Level Systems (OS, Network/Protocol, Database, Storage)](https://www.cse.wustl.edu/~jain/cse567-06/ftp/os_monitors/index.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)
	* [SQL Transaction Isolation Levels Explained](http://elliot.land/post/sql-transaction-isolation-levels-explained)
* ["What Happens When... and How" Questions](https://www.glassdoor.com/Interview/What-happens-when-you-type-www-google-com-in-your-browser-QTN_56396.htm)
	* [Netflix: What Happens When You Press Play?](http://highscalability.com/blog/2017/12/11/netflix-what-happens-when-you-press-play.html)
	* [Monzo: How Peer-To-Peer Payments Work](https://monzo.com/blog/2018/04/05/how-monzo-to-monzo-payments-work/)
	* [Transit and Peering: How Your Requests Reach GitHub](https://githubengineering.com/transit-and-peering-how-your-requests-reach-github/)
	* [How Spotify Streams Music](https://labs.spotify.com/2018/08/31/smoother-streaming-with-bbr/)

## Organization
* [Engineering Levels at SoundCloud](https://developers.soundcloud.com/blog/engineering-levels)
* [Engineering Roles at Palantir](https://medium.com/palantir/dev-versus-delta-demystifying-engineering-roles-at-palantir-ad44c2a6e87)
* [Engineering Career Framework at Dropbox](https://dropbox.tech/culture/our-updated-engineering-career-framework)
* [Scaling Engineering Teams at Twitter](https://www.youtube.com/watch?v=-PXi_7Ld5kU)
* [Scaling Decision-Making Across Teams at LinkedIn](https://engineering.linkedin.com/blog/2018/03/scaling-decision-making-across-teams-within-linkedin-engineering)
* [Scaling Data Science Team at GOJEK](https://blog.gojekengineering.com/the-dynamics-of-scaling-an-organisation-cb96dbe8aecd)
* [Scaling Agile at Zalando](https://engineering.zalando.com/posts/2018/05/scaling-agile-zalando.html)
* [Scaling Agile at bol.com](https://hackernoon.com/how-we-run-bol-com-with-60-autonomous-teams-fe7a98c0759)
* [Lessons Learned from Scaling a Product Team at Intercom](https://blog.intercom.com/how-we-build-software/)
* [Hiring, Managing, and Scaling Engineering Teams at Typeform](https://medium.com/@eleonorazucconi/toby-oliver-cto-typeform-on-hiring-managing-and-scaling-engineering-teams-86bef9e5a708)	
* [Scaling the Datagram Team at Instagram](https://instagram-engineering.com/scaling-the-datagram-team-fc67bcf9b721)
* [Scaling the Design Team at Flexport](https://medium.com/flexport-design/designing-a-design-team-a9a066bc48a5)
* [Team Model for Scaling a Design System at Salesforce](https://medium.com/salesforce-ux/the-salesforce-team-model-for-scaling-a-design-system-d89c2a2d404b)
* [Building Analytics Team (4 parts) at Wish](https://medium.com/wish-engineering/scaling-the-analytics-team-at-wish-part-4-recruiting-2a9823b9f5a)
* [From 2 Founders to 1000 Employees at Transferwise](https://medium.com/transferwise-ideas/from-2-founders-to-1000-employees-how-a-small-scale-startup-grew-into-a-global-community-9f26371a551b)
* [Lessons Learned Growing a UX Team from 10 to 170 at Adobe](https://medium.com/thinking-design/lessons-learned-growing-a-ux-team-from-10-to-170-f7b47be02262)
* [Five Lessons from Scaling at Pinterest](https://medium.com/@sarahtavel/five-lessons-from-scaling-pinterest-6a699a889b08)
* [Approach Engineering at Vinted](http://engineering.vinted.com/2018/09/04/how-we-approach-engineering-at-vinted/)
* [Using Metrics to Improve the Development Process (and Coach People) at Indeed](https://engineering.indeedblog.com/blog/2018/10/using-metrics-to-improve-the-development-process-and-coach-people/)
* [Mistakes to Avoid while Creating an Internal Product at Skyscanner](https://medium.com/@SkyscannerEng/9-mistakes-to-avoid-while-creating-an-internal-product-63d579b00b1a)
* [RACI (Responsible, Accountable, Consulted, Informed) at Etsy](https://codeascraft.com/2018/01/04/selecting-a-cloud-provider/)
* [Four Pillars of Leading People (Empathy, Inspiration, Trust, Honesty) at Zalando](https://engineering.zalando.com/posts/2018/10/four-pillars-leadership.html)
* [Pair Programming at Shopify](https://engineering.shopify.com/blogs/engineering/pair-programming-explained)
* [Distributed Responsibility at Asana](https://blog.asana.com/2017/12/distributed-responsibility-engineering-manager/)
* [Rotating Engineers at Zalando](https://engineering.zalando.com/posts/2019/03/rotating-engineers-at-zalando.html)
* [Experiment Idea Review at Pinterest](https://medium.com/pinterest-engineering/how-pinterest-supercharged-its-growth-team-with-experiment-idea-review-fd6571a02fb8)
* [Tech Migrations at Spotify](https://engineering.atspotify.com/2020/06/25/tech-migrations-the-spotify-way/)
* [Improving Code Ownership at Yelp](https://engineeringblog.yelp.com/2021/01/whose-code-is-it-anyway.html)
* [Agile Code Base at eBay](https://tech.ebayinc.com/engineering/how-creating-an-agile-code-base-helped-ebay-pivot-for-apple-silicon/)
* [Agile Data Engineering at Miro](https://medium.com/miro-engineering/agile-data-engineering-at-miro-ec2dcc8a3fcb)
* [Automated Incident Management through Slack at Airbnb](https://medium.com/airbnb-engineering/incident-management-ae863dc5d47f)
* [Refactor Organization at BBC](https://medium.com/bbc-product-technology/refactor-organisation-80e4e171d922)
* [Code Review](https://ai.google/research/pubs/pub47025)
	* [Code Review at Palantir](https://medium.com/@palantir/code-review-best-practices-19e02780015f)
	* [Code Review at LINE](https://engineering.linecorp.com/en/blog/effective-code-review/)
	* [Code Reviews at Medium](https://medium.engineering/code-reviews-at-medium-bed2c0dce13a)
	* [Code Review at LinkedIn](https://engineering.linkedin.com/blog/2018/06/scaling-collective-code-ownership-with-code-reviews)
	* [Code Review at Disney](https://medium.com/disney-streaming/the-secret-to-better-code-reviews-c14c7884b9ac)
	* [Code Review at Netlify](https://www.netlify.com/blog/2020/03/05/feedback-ladders-how-we-encode-code-reviews-at-netlify/)

## Talk
* [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 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 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)
* [Scaling Multitenant Architecture Across Multiple Data Centres at Shopify - Weingarten, Engineering Lead at Shopify](https://www.youtube.com/watch?v=F-f0-k46WVk)

## A Piece of Cake
Roses are red. Violets are blue. [Binh](https://nguyenquocbinh.org/) likes sweet. [Treat Binh a tiramisu?](https://paypal.me/binhnguyennus) :cake:

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