awesome-scalability/README.md

# The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

An organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users.

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

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

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

#### If you are building your dream team :ferris_wheel:
> The goal of scaling team is not growing team size but increasing team output and value. You can find out how tech companies reach that goal in various aspects: hiring, management, organization, culture, and communication in the [organization](#organization) section.

#### Community power :mountain_cableway::aerial_tramway::mountain_cableway:

> Contributions are greatly welcome! You may want to take a look at the [contribution guidelines](CONTRIBUTING.md). If you see a link here that is no longer maintained or is not a good fit, please submit a pull request!

## 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/)
* [Things to Keep in Mind When Building a Platform for the Enterprise - Heidi Williams, VP Platform at Box](https://blog.box.com/blog/4-things-to-keep-in-mind-when-building-a-platform-for-the-enterprise/)
* [Principles of Chaos Engineering](https://www.usenix.org/conference/srecon17americas/program/presentation/rosenthal)
* [Finding the Order in Chaos](https://www.usenix.org/conference/srecon16/program/presentation/lueder)
* [The Twelve-Factor App](https://12factor.net/)
* [Clean Architecture](https://8thlight.com/blog/uncle-bob/2012/08/13/the-clean-architecture.html)
* [High Cohesion and Low Coupling](http://www.math-cs.gordon.edu/courses/cs211/lectures-2009/Cohesion,Coupling,MVC.pdf)
* [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](https://www.brianjgraf.com/2013/05/17/scalability-scale-up-scale-out-care/)
* [Scale Up vs Scale Out: Hidden Costs](https://blog.codinghorror.com/scaling-up-vs-scaling-out-hidden-costs/)
* [Best Practices for Scaling Out](https://blog.openshift.com/best-practices-for-horizontal-application-scaling/)
* [Best Practices for Continuous Delivery](https://techblog.rakuten.co.jp/2018/02/06/cd-the-best-practice/)
* [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://jobs.zalando.com/tech/blog/simplicity-by-distributing-complexity/)
* [Why Over-Reusing is Bad](http://tech.transferwise.com/why-over-reusing-is-bad/)
* [Performance is a Feature](https://blog.codinghorror.com/performance-is-a-feature/)
* [Make Performance Part of Your Workflow](https://codeascraft.com/2014/12/11/make-performance-part-of-your-workflow/)
* [The Benefits of Server Side Rendering over Client Side Rendering](https://medium.com/walmartlabs/the-benefits-of-server-side-rendering-over-client-side-rendering-5d07ff2cefe8)
* [Writing Code that Scales](https://blog.rackspace.com/writing-code-that-scales)
* [Automate and Abstract: Lessons 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 Loose-coupling](http://bulgerpartners.com/how-loosely-coupled-architectures-are-helping-the-modernization-of-legacy-software/)
* [Design for Resiliency](http://highscalability.com/blog/2012/12/31/designing-for-resiliency-will-be-so-2013.html)
* [Design for Self-healing](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/self-healing)
* [Design for Scaling Out](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/scale-out)	
* [Design for Evolution](https://docs.microsoft.com/en-us/azure/architecture/guide/design-principles/design-for-evolution)
* [Learn from Mistakes](http://highscalability.com/blog/2013/8/26/reddit-lessons-learned-from-mistakes-made-scaling-to-1-billi.html)

## Scalability
* [Microservices and Orchestration](https://hackernoon.com/microservices-are-hard-an-invaluable-guide-to-microservices-2d06bd7bcf5d)
	* [Microservices Resource Guide - Martin Fowler](https://martinfowler.com/microservices/)
	* [Microservices Patterns](http://microservices.io/patterns/)
	* [Advantages and Drawbacks of Microservices](https://cloudacademy.com/blog/microservices-architecture-challenge-advantage-drawback/)
	* [Microservices Scale Cube](http://microservices.io/articles/scalecube.html)
	* [Thinking Inside the Container (8 parts) at Riot Games](https://engineering.riotgames.com/news/thinking-inside-container)
	* [Containerization at Pinterest](https://medium.com/@Pinterest_Engineering/containerization-at-pinterest-92295347f2f3)
	* [Techniques for Splitting Up a Codebase into Microservices and Artifacts at LinkedIn](https://engineering.linkedin.com/blog/2016/02/q-a-with-jim-brikman--splitting-up-a-codebase-into-microservices)
	* [The Evolution of Container Usage at Netflix](https://medium.com/netflix-techblog/the-evolution-of-container-usage-at-netflix-3abfc096781b)
	* [Dockerizing MySQL at Uber](https://eng.uber.com/dockerizing-mysql/)
	* [Testing of Microservices at Spotify](https://labs.spotify.com/2018/01/11/testing-of-microservices/)
	* [Organize Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0)
	* [Lessons learned running Docker in production at Treehouse](https://medium.com/treehouse-engineering/lessons-learned-running-docker-in-production-5dce99ece770)
	* [Inside a SoundCloud Microservice](https://developers.soundcloud.com/blog/inside-a-soundcloud-microservice)
	* [Operate Kubernetes Reliably at Stripe](https://stripe.com/blog/operating-kubernetes)
	* [Kubernetes Traffic Routing (2 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/09/28/k8s-routing2/)
	* [Agrarian-Scale Kubernetes (3 parts) at New York Times](https://open.nytimes.com/agrarian-scale-kubernetes-part-3-ee459887ed7e)
	* [Nanoservices at BBC Online](https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b)
	* [PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg](https://www.techatbloomberg.com/blog/powerfulseal-testing-tool-kubernetes-clusters/)
	* [Conductor: Microservices Orchestrator at Netflix](https://medium.com/netflix-techblog/netflix-conductor-a-microservices-orchestrator-2e8d4771bf40)
	* [Making 10x Improvement in Release Times with Docker and Amazon ECS at Nextdoor](https://engblog.nextdoor.com/how-nextdoor-made-a-10x-improvement-in-release-times-with-docker-and-amazon-ecs-35aab52b726f)
	* [K8Guard: Auditing System for Kubernetes Clusters at Target.com](http://target.github.io/infrastructure/k8guard-the-guardian-angel-for-kuberentes)
	* [Deconstructing Monolithic Applications into (Kafka-driven) Services at Heroku](https://blog.heroku.com/monolithic-applications-into-services)
	* [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)
* [Distributed Caching](https://www.wix.engineering/single-post/scaling-to-100m-to-cache-or-not-to-cache)
	* [Read-Through, Write-Through, Write-Behind, and Refresh-Ahead Caching](https://docs.oracle.com/cd/E15357_01/coh.360/e15723/cache_rtwtwbra.htm#COHDG5177)
	* [Eviction Policy and Expiration Policy](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
	* [EVCache: 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/)
	* [Reduce Memcached Memory Usage by 50% at Trivago](http://tech.trivago.com/2017/12/19/how-trivago-reduced-memcached-memory-usage-by-50/)
	* [Caching Internal Service Calls at Yelp](https://engineeringblog.yelp.com/2018/03/caching-internal-service-calls-at-yelp.html)
	* [Scaling Live Streaming for Large Events (with Distributed Cache) at Hulu](https://medium.com/hulu-tech-blog/scaling-hulu-live-streaming-for-large-events-march-madness-and-beyond-bedd73874f2)
	* [Estimating the Cache Efficiency using Big Data at Allegro](https://allegro.tech/2017/01/estimating-the-cache-efficiency-using-big-data.html)
	* [Caching (with Hashing) at Zenefits](https://engineering.zenefits.com/2016/02/basic-infrastructure-patterns/)
	* [Distributed Cache (Akka, Kubernetes) at Zalando](https://jobs.zalando.com/tech/blog/distributed-cache-akka-kubernetes/)
	* [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)
	* [Avoiding Cache Stampede at DoorDash](https://blog.doordash.com/avoiding-cache-stampede-at-doordash-55bbf596d94b)
	* [Location Caching with Quadtrees at Yext](http://engblog.yext.com/post/geolocation-caching)
	* [Pycache: In-process Caching at Quora](https://engineering.quora.com/Pycache-lightning-fast-in-process-caching)
    * [HTTP Caching](https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching)
        * [Caching 404s Saved 66% On Server Time at The Onion](http://highscalability.com/blog/2010/3/26/strategy-caching-404s-saved-the-onion-66-on-server-time.html)
        * [Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga](https://www.zynga.com/blogs/engineering/zynga-geo-proxy-reducing-mobile-game-latency)
        * [Google AMP at Condé Nast](https://technology.condenast.com/story/the-why-and-how-of-google-amp-at-conde-nast)
        * [Running A/B Tests on Hosting Infrastructure (CDNs) at Deliveroo](https://deliveroo.engineering/2016/09/19/ab-testing-cdns.html)
        * [HAProxy with Kubernetes for User-facing Traffic at SoundCloud](https://developers.soundcloud.com/blog/how-soundcloud-uses-haproxy-with-kubernetes-for-user-facing-traffic)
        * [Bandaid: Service Proxy at Dropbox](https://blogs.dropbox.com/tech/2018/03/meet-bandaid-the-dropbox-service-proxy/)
        * [CDN in LIVE's Encoder Layer at LINE](https://engineering.linecorp.com/en/blog/detail/230)
* [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://blog.chartio.com/posts/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)
	* [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/)
	* [StatsD at DoorDash](https://blog.doordash.com/scaling-statsd-84d456a7cc2a)
* [Distributed Scheduling](https://www.csee.umbc.edu/courses/graduate/CMSC621/fall02/lectures/ch11.pdf)
    * [Building Cron at Google](https://landing.google.com/sre/sre-book/chapters/distributed-periodic-scheduling/)
    * [Distributed Cron Architecture at Quora](https://engineering.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 Management Platform at Airbnb](https://medium.com/airbnb-engineering/airflow-a-workflow-management-platform-46318b977fd8)
		* [Airflow at Pandora](https://engineering.pandora.com/apache-airflow-at-pandora-1d7a844d68ee)
        * [Airflow at Robinhood](https://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://codeascraft.com/2018/11/14/boundary-layer%e2%80%89-declarative-airflow-workflows/)
* [Distributed Logging](https://blog.treasuredata.com/blog/2016/08/03/distributed-logging-architecture-in-the-container-era/)
	* [The Problem with Logging - Jeff Atwood](https://blog.codinghorror.com/the-problem-with-logging/)
	* [The Log: What Every Software Engineer Should Know](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying)
	* [Using Logs to Build a Solid Data Infrastructure - Martin Kleppmann](https://www.confluent.io/blog/using-logs-to-build-a-solid-data-infrastructure-or-why-dual-writes-are-a-bad-idea/)
	* [Scalable and Reliable Log Ingestion at Pinterest](https://medium.com/@Pinterest_Engineering/scalable-and-reliable-data-ingestion-at-pinterest-b921c2ee8754)
	* [Building DistributedLog at Twitter: High-performance replicated log service](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2015/building-distributedlog-twitter-s-high-performance-replicated-log-servic.html)
	* [Logging Service with Spark at CERN Accelerator](https://databricks.com/blog/2017/12/14/the-architecture-of-the-next-cern-accelerator-logging-service.html)
	* [Logging and Aggregation at Quora](https://engineering.quora.com/Logging-and-Aggregation-at-Quora)
	* [BookKeeper: Distributed Log Storage at Yahoo](https://yahooeng.tumblr.com/post/109908973316/bookkeeper-yahoos-distributed-log-storage-is)
	* [LogDevice: Distributed Data Store for Logs at Facebook](https://code.facebook.com/posts/357056558062811/logdevice-a-distributed-data-store-for-logs/)
	* [LogFeeder: Log Collection System at Yelp](https://engineeringblog.yelp.com/2018/03/introducing-logfeeder.html)
	* [Collection and Analysis of Daemon Logs at Badoo](https://badoo.com/techblog/blog/2016/06/06/collection-and-analysis-of-daemon-logs-at-badoo/)
* [Distributed Monitoring and Alerting](https://www.oreilly.com/ideas/monitoring-distributed-systems)
    * [Alibaba Monitoring System](https://www.usenix.org/conference/srecon18asia/presentation/xinchi)
	* [Smart Monitoring System for Anomaly Detection on Business Trends at Alibaba](https://www.usenix.org/conference/srecon17asia/program/presentation/wang)
    * [Real User Monitoring at Dailymotion](https://medium.com/dailymotion/real-user-monitoring-1948375f8be5)
    * [Alerting Ecosystem at Uber](https://eng.uber.com/observability-at-scale/)
    * [Job-based Forecasting Workflow for Observability Anomaly Detection at Uber](https://eng.uber.com/observability-anomaly-detection/)
    * [Securitybot: Distributed Alerting Bot at Dropbox](https://blogs.dropbox.com/tech/2017/02/meet-securitybot-open-sourcing-automated-security-at-scale/)
    * [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)
	* [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://blogs.dropbox.com/tech/2019/05/athena-our-automated-build-health-management-system/)
	* [ThirdEye: Monitoring Platform at LinkedIn](https://engineering.linkedin.com/blog/2019/06/smart-alerts-in-thirdeye--linkedins-real-time-monitoring-platfor)
* [Distributed Security](https://msdn.microsoft.com/en-us/library/cc767123.aspx)
	* [Approach to Security at Scale at Dropbox](https://blogs.dropbox.com/tech/2018/02/security-at-scale-the-dropbox-approach/)
	* [Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix](https://medium.com/netflix-techblog/introducing-aardvark-and-repokid-53b081bf3a7e)	
	* [LISA: Distributed Firewall at LinkedIn](https://www.slideshare.net/MikeSvoboda/2017-lisa-linkedins-distributed-firewall-dfw)
	* [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)
	* [WebAuthn Support for Secure Sign In at Dropbox](https://blogs.dropbox.com/tech/2018/05/introducing-webauthn-support-for-secure-dropbox-sign-in/)
	* [Security Development Lifecycle (SDL) 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)	
* [Distributed Messaging, Queuing, and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
	* [Cape: Event Stream Processing Framework at Dropbox](https://blogs.dropbox.com/tech/2017/05/introducing-cape/)
	* [Druid: Event Stream Analytics at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)	
	* [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://engineering.quora.com/Qmessage-Handling-Billions-of-Tasks-Per-Day)
	* [Cherami: Message Queue System for Transporting Async Tasks at Uber](https://eng.uber.com/cherami/)
	* [Messaging Service at Riot Games](https://engineering.riotgames.com/news/riot-messaging-service)
	* [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)
	* [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)
    * [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 mytaxi](https://inside.mytaxi.com/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/)
		* [Pub-Sub in Chatting Architecture at LINE](https://engineering.linecorp.com/en/blog/detail/85)
	* [Kafka the 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 Rakuten](https://techblog.rakuten.co.jp/2016/01/28/rakuten-paas-kafka/)
		* [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)
		* [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://blogs.dropbox.com/tech/2019/01/finding-kafkas-throughput-limit-in-dropbox-infrastructure/)
	* [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)	
* [Distributed Searching](http://nwds.cs.washington.edu/files/nwds/pdf/Distributed-WR.pdf)
	* [Search Architecture of Instagram](https://engineering.instagram.com/search-architecture-eeb34a936d3a)
	* [Search Architecture of eBay](http://www.cs.otago.ac.nz/homepages/andrew/papers/2017-8.pdf)
	* [Improving Search Engine Efficiency by over 25% at eBay](https://www.ebayinc.com/stories/blogs/tech/making-e-commerce-search-faster/)	
	* [Indexing and Querying Telemetry Logs with Lucene at Palantir](https://medium.com/palantir/indexing-and-querying-telemetry-logs-with-lucene-234c5ce3e5f3)
	* [Search Federation Architecture at LinkedIn (2018)](https://engineering.linkedin.com/blog/2018/03/search-federation-architecture-at-linkedin)
	* [Search at Slack](https://slack.engineering/search-at-slack-431f8c80619e)
	* [Search and Recommendations at DoorDash](https://blog.doordash.com/powering-search-recommendations-at-doordash-8310c5cfd88c)
	* [Search Service at Twitter (2014)](https://blog.twitter.com/engineering/en_us/a/2014/building-a-complete-tweet-index.html)
	* [Autocomplete Search (2 parts) at Traveloka](https://medium.com/traveloka-engineering/high-quality-autocomplete-search-part-2-d5b15bb0dadf)
	* [Nautilus: Search Engine at Dropbox](https://blogs.dropbox.com/tech/2018/09/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://tech.flipkart.com/sherlock-near-real-time-search-indexing-95519783859d)
	* [Nebula: Storage Platform to Build Search Backends at Airbnb](https://medium.com/airbnb-engineering/nebula-as-a-storage-platform-to-build-airbnbs-search-backends-ecc577b05f06)
	* [ELK (Elasticsearch, Logstash, Kibana) Stack](https://logz.io/blog/15-tech-companies-chose-elk-stack/)
		* [Predictions in Real Time with ELK at Uber](https://eng.uber.com/elk/)
		* [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/)
		* [Elasticsearch at Kickstarter](https://kickstarter.engineering/elasticsearch-at-kickstarter-db3c487887fc)
		* [Elasticsearch at Target](https://tech.target.com/2017/05/25/elasticsearch-cloud.html)
		* [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)
		* [Upgrading Elasticsearch (3 parts) at Redmart](http://geeks.redmart.com/2018/12/11/upgrading-elasticsearch-at-redmart-pt-3-testing-customer-reactions/)
		* [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)
		* [Introduction to In-memory Data - Viktor Gamov, Solutions Architect at Hazelcast](https://www.infoq.com/presentations/in-memory-data)
		* [MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)](http://highscalability.com/blog/2012/8/14/memsql-architecture-the-fast-mvcc-inmem-lockfree-codegen-and.html)
		* [Optimizing Memcached Efficiency at Quora](https://engineering.quora.com/Optimizing-Memcached-Efficiency)
		* [Real-Time Data Warehouse with MemSQL on Cisco UCS](https://blogs.cisco.com/datacenter/memsql)
		* [Moving to MemSQL (with Horizontally Scalable, ACID Compliant, MySQL Compatibility) at Tapjoy](http://eng.tapjoy.com/blog-list/moving-to-memsql)
		* [MemSQL and Kinesis for Real-time Insights at Disney-ABC TV](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/68131)
	* [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://blogs.dropbox.com/tech/2016/05/inside-the-magic-pocket/)
* [Relational Databases (MySQL, MSSQL, PostgreSQL)](https://www.mysql.com/products/cluster/scalability.html)
	* [MySQL for schema-less data at FriendFeed (Bret Taylor)](https://backchannel.org/blog/friendfeed-schemaless-mysql)
	* [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/how-twitch-uses-postgresql-c34aa9e56f58)
	* [Scaling MySQL-based Financial Reporting System at Airbnb](https://medium.com/airbnb-engineering/tracking-the-money-scaling-financial-reporting-at-airbnb-6d742b80f040)
	* [Scaling MySQL at Wix](https://www.wix.engineering/single-post/scaling-to-100m-mysql-is-a-better-nosql)
	* [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://eng.uber.com/mysql-migration/)
	* [Handling Growth with Postgres at Instagram](https://engineering.instagram.com/handling-growth-with-postgres-5-tips-from-instagram-d5d7e7ffdfcb)
	* [Scaling the Analytics Database (Postgres) at TransferWise](http://tech.transferwise.com/scaling-our-analytics-database/)
	* [Updating a 50 Terabyte PostgreSQL Database at Adyen](https://medium.com/adyen/updating-a-50-terabyte-postgresql-database-f64384b799e7)
	* [Replication](https://m.alphasights.com/a-primer-on-database-replication-381b319cd032)		
		* [MySQL Parallel Replication (4 parts) at Booking.com](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-4-annex-under-the-hood-eb456cf8b2fb)
		* [Mitigating MySQL Replication Lag and Reducing Read Load at Github](https://githubengineering.com/mitigating-replication-lag-and-reducing-read-load-with-freno/)
		* [Black-Box Auditing: Verifying End-to-End Replication Integrity between MySQL and Redshift at Yelp](https://engineeringblog.yelp.com/2018/04/black-box-auditing.html)
		* [Monitoring MySQL Delayed Replication at IMVU](https://engineering.imvu.com/2013/01/09/monitoring-delayed-replication-with-a-focus-on-mysql/)
		* [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 (Horizontal Partitioning)](https://www.educative.io/collection/page/5668639101419520/5649050225344512/5146118144917504)
		* [Sharding MySQL at Pinterest](https://medium.com/@Pinterest_Engineering/sharding-pinterest-how-we-scaled-our-mysql-fleet-3f341e96ca6f)
		* [Sharding MySQL at 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 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)
		* [Solr: Improving Performance for Batch Indexing at Box](https://blog.box.com/blog/solr-improving-performance-batch-indexing/)	
		* [Geosharded Recommendations (2 parts) at Tinder](https://medium.com/tinder-engineering/geosharded-recommendations-part-2-architecture-3396a8a7efb)				
* [NoSQL Databases](https://www.thoughtworks.com/insights/blog/nosql-databases-overview)
	* [Key-Value Databases (DynamoDB)](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/)
		* [zBase: High Performance, Elastic, Distributed Key-Value Store at Zynga](https://www.zynga.com/blogs/engineering/zbase-high-performance-elastic-distributed-key-value-store-2)
		* [Venice: Distributed Key-Value Database at Linkedin](https://engineering.linkedin.com/blog/2017/02/building-venice-with-apache-helix)
	* [Columnar Databases (Cassandra, HBase, Redshift)](https://aws.amazon.com/nosql/columnar/)
		* [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)
			* [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 (MongoDB, SimpleDB, CouchDB)](https://msdn.microsoft.com/en-us/magazine/hh547103.aspx)
		* [eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB](https://www.mongodb.com/blog/post/ebay-building-mission-critical-multi-data-center-applications-with-mongodb)
		* [MongoDB at Baidu: Multi-Tenant Cluster Storing 200+ Billion Documents across 160 Shards](https://www.mongodb.com/blog/post/mongodb-at-baidu-powering-100-apps-across-600-nodes-at-pb-scale)
		* [Migrating Mongo Data at Addepar](https://medium.com/build-addepar/migrating-mountains-of-mongo-data-63e530539952)
		* [The AWS and MongoDB Infrastructure of Parse (acquired by Facebook)](https://medium.baqend.com/parse-is-gone-a-few-secrets-about-their-infrastructure-91b3ab2fcf71)
		* [Migrating Mountains of Mongo Data at Addepar](https://medium.com/build-addepar/migrating-mountains-of-mongo-data-63e530539952)
		* [Couchbase Ecosystem at LinkedIn](https://engineering.linkedin.com/blog/2017/12/couchbase-ecosystem-at-linkedin)
		* [SimpleDB at Zendesk](https://medium.com/zendesk-engineering/resurrecting-amazon-simpledb-9404034ec506)
		* [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)
		* [Beam: Distributed Knowledge Graph Store at eBay](https://www.ebayinc.com/stories/blogs/tech/beam-a-distributed-knowledge-graph-store/)
	* [Datastructure Databases (Redis, Hazelcast)](https://db-engines.com/en/system/Hazelcast%3BMemcached%3BRedis)
		* [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 in Chat Architecture of Twitch (from 27:22)](https://www.infoq.com/presentations/twitch-pokemon)
		* [Learn Redis the hard way (in production) at Trivago](http://tech.trivago.com/2017/01/25/learn-redis-the-hard-way-in-production/)
		* [Optimizing Session Key Storage in Redis at Deliveroo](https://deliveroo.engineering/2016/10/07/optimising-session-key-storage.html)
		* [Optimizing Redis Storage at Deliveroo](https://deliveroo.engineering/2017/01/19/optimising-membership-queries.html)		
		* [Memory Optimization in Redis at Wattpad](http://engineering.wattpad.com/post/23244724794/store-more-stuff-memory-optimization-in-redis)
		* [Sending an e-mail to millions of users (with Redis) at Drivy](https://drivy.engineering/sending-mass-emails/)
		* [Redis Fleet at Heroku](https://blog.heroku.com/rolling-redis-fleet)
* [Time Series Databases](https://www.influxdata.com/time-series-database/)
	* [What is Time-Series Data & Why We Need a Time-Series Database](https://blog.timescale.com/what-the-heck-is-time-series-data-and-why-do-i-need-a-time-series-database-dcf3b1b18563)
	* [Time Series Data: Why and How to Use a Relational Database instead of NoSQL](https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c)
	* [Practical Guide to Monitoring and Alerting with Time Series at Scale](https://www.usenix.org/conference/srecon17americas/program/presentation/wilkinson)
	* [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)
	* [Building a Scalable Time Series Database on PostgreSQL](https://blog.timescale.com/when-boring-is-awesome-building-a-scalable-time-series-database-on-postgresql-2900ea453ee2)
	* [Scaling Time Series Data Storage (2 parts) at Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-ii-d67939655586)	
* [Distributed Repositories, Dependencies, and Configurations Management](https://betterexplained.com/articles/intro-to-distributed-version-control-illustrated/)
	* [Distributed Version Control Systems: A Not-So-Quick Guide Through](https://www.infoq.com/articles/dvcs-guide)
	* [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/)
	* [How Microsoft Solved Git’s Problem with Large Repositories](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)
	* [Dynamic Configuration at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/dynamic-configuration-at-twitter.html)
* [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)
	* [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://engineering.quora.com/Ensuring-Quoras-Resilience-to-Disaster)
	* [Resilience at Shopify](https://scaleyourcode.com/blog/article/23)
	* [Site Resiliency at Expedia](https://www.infoq.com/presentations/expedia-website-resiliency?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study)
* [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/)
* [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/)
	* [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://blogs.dropbox.com/tech/2018/10/dropbox-traffic-infrastructure-edge-network/)
	* [Monitor DNS systems at Stripe](https://stripe.com/en-sg/blog/secret-life-of-dns)
* [Rate Limiting](https://www.keycdn.com/support/rate-limiting/)
	* [Rate Limiting for Scaling to Millions of Domains at Cloudfare](https://blog.cloudflare.com/counting-things-a-lot-of-different-things/)
	* [Cloud Bouncer: Distributed Rate Limiting at Yahoo](https://yahooeng.tumblr.com/post/111288877956/cloud-bouncer-distributed-rate-limiting-at-yahoo)
	* [Scaling API with Rate Limiters at Stripe](https://stripe.com/blog/rate-limiters)
	* [Rate Limiting at Etsy](https://www.sans.org/summit-archives/file/summit-archive-1509593697.pdf)
	* [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)
* [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 Applications at PayPal](https://www.paypal-engineering.com/2017/08/16/autoscaling-applications-paypal/)
	* [Autoscaling Jenkins at Trivago](http://tech.trivago.com/2017/02/17/your-definite-guide-for-autoscaling-jenkins/)
	* [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/)
	* [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)
* [Automating Datacenter Operations at Dropbox](https://blogs.dropbox.com/tech/2019/01/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 Breakers for Distributed Services at LINE](https://engineering.linecorp.com/en/blog/detail/76)
	* [Applying Circuit Breaker to Channel Gateway at LINE](https://engineering.linecorp.com/en/blog/detail/78)
	* [Lessons in Resilience at SoundCloud](https://developers.soundcloud.com/blog/lessons-in-resilience-at-SoundCloud)
	* [Circuit Breaker for Scaling Containers](https://f5.com/about-us/blog/articles/the-art-of-scaling-containers-circuit-breakers-28919)
	* [Protector: Circuit Breaker for Time Series Databases at Trivago](http://tech.trivago.com/2016/02/23/protector/)
	* [Improved Production Stability with Circuit Breakers at Heroku](https://blog.heroku.com/improved-production-stability-with-circuit-breakers)
	* [Circuit Breakers at Zendesk](https://medium.com/zendesk-engineering/the-joys-of-circuit-breaking-ee6584acd687)
	* [Circuit Breakers at Traveloka](https://medium.com/traveloka-engineering/circuit-breakers-dont-let-your-dependencies-bring-you-down-5ba1c5cf1eec)
* [Always Use Timeouts If Possible](https://www.javaworld.com/article/2824163/application-performance/stability-patterns-applied-in-a-restful-architecture.html)
* [Crash Early: Better Error Now Than Response Tomorrow](http://odino.org/better-performance-the-case-for-timeouts/)
* [Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Neflix](https://medium.com/netflix-techblog/fault-tolerance-in-a-high-volume-distributed-system-91ab4faae74a)
* [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)
	* [Compression Techniques to Solve Network I/O Bottlenecks at eBay](https://www.ebayinc.com/stories/blogs/tech/how-ebays-shopping-cart-used-compression-techniques-to-solve-network-io-bottlenecks/)
	* [Optimizing Web Servers for High Throughput and Low Latency at Dropbox](https://blogs.dropbox.com/tech/2017/09/optimizing-web-servers-for-high-throughput-and-low-latency/)
	* [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)
	* [Performance Improvements at Pinterest](https://medium.com/@Pinterest_Engineering/driving-user-growth-with-performance-improvements-cfc50dafadd7)
	* [Server Side Rendering at Wix](https://www.youtube.com/watch?v=f9xI2jR71Ms)
	* [30x Performance Improvements on MySQLStreamer at Yelp](https://engineeringblog.yelp.com/2018/02/making-30x-performance-improvements-on-yelps-mysqlstreamer.html)
	* [Optimizing APIs through Dynamic Polyglot Runtime, Fully Asynchronous, and Reactive Programming at Netflix](https://medium.com/netflix-techblog/optimizing-the-netflix-api-5c9ac715cf19)
	* [Performance Monitoring with Riemann and Clojure at Walmart](https://medium.com/walmartlabs/performance-monitoring-with-riemann-and-clojure-eafc07fcd375)
	* [Performance Tracking Dashboard for Live Games at Zynga](https://www.zynga.com/blogs/engineering/live-games-have-evolving-performance)
	* [Optimizing CAL Report Hadoop MapReduce Jobs at eBay](https://www.ebayinc.com/stories/blogs/tech/optimization-of-cal-report-hadoop-mapreduce-job/)
	* [Performance Tuning on Quartz Scheduler at eBay](https://www.ebayinc.com/stories/blogs/tech/performance-tuning-on-quartz-scheduler/)
	* [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)
	* [Diagnosing Networking Issues in the Linux Kernel at Mixpanel](https://code.mixpanel.com/2015/03/26/diagnosing-networking-issues-in-the-linux-kernel/)
	* [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://blogs.dropbox.com/tech/2018/11/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)
* [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)
* [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)
	* [Boosting Site Speed Using Brotli Compression at LinkedIn](https://engineering.linkedin.com/blog/2017/05/boosting-site-speed-using-brotli-compression)
	* [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)
    
## 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 Netflix](https://www.youtube.com/watch?v=CSDIThSwA7s)
	* [Data Platform at Flipkart](https://tech.flipkart.com/overview-of-flipkart-data-platform-20c6d3e9a196)
	* [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)
	* [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)
	* [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/)
	* [Gimel: Analytics Data Processing Platform at PayPal](https://www.paypal-engineering.com/2018/04/17/gimel/)
	* [AthenaX: Streaming Analytics Platform at Uber](https://eng.uber.com/athenax/)
	* [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 at Airbnb](https://medium.com/airbnb-engineering/https-medium-com-jonathan-parks-scaling-erf-23fd17c91166)
	* [Smart Product Platform at Zalando](https://jobs.zalando.com/tech/blog/zalando-smart-product-platform/?gh_src=4n3gxh1)
	* [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)
* [Distributed Machine Learning](https://www.csie.ntu.edu.tw/~cjlin/talks/bigdata-bilbao.pdf)
	* [Aroma: Using ML for Code Recommendation at Facebook](https://code.fb.com/developer-tools/aroma/)
	* [Michelangelo: Machine Learning Platform at Uber](https://eng.uber.com/michelangelo/)
	* [Scaling Michelangelo](https://eng.uber.com/scaling-michelangelo/)
	* [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/)
	* [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/)
	* [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/)
	* [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)
	* [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)
	* [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/)
	* [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)
	* [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/)
	* [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)
	* [Venue Rating System at Foursquare](https://engineering.foursquare.com/finding-the-perfect-10-how-we-developed-the-foursquare-venue-rating-system-c76b08f7b9b3)
	* [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://jobs.zalando.com/tech/blog/search-deep-neural-network/)
	* [Machine Learning at Jane Street](https://blog.janestreet.com/real-world-machine-learning-part-1/)
	* [Machine Learning for Ranking Answers End-to-End at Quora](https://engineering.quora.com/A-Machine-Learning-Approach-to-Ranking-Answers-on-Quora)
	* [Clustering Similar Stories Using LDA at Flipboard](http://engineering.flipboard.com/2017/02/storyclustering)
	* [Similarity Search at Flickr](https://code.flickr.net/2017/03/07/introducing-similarity-search-at-flickr/)
	* [Large-Scale Machine Learning Pipeline for Job Recommendations at Indeed](http://engineering.indeedblog.com/blog/2016/04/building-a-large-scale-machine-learning-pipeline-for-job-recommendations/)
	* [Deep Learning from Prototype to Production at Taboola](http://engineering.taboola.com/deep-learning-from-prototype-to-production/)
	* [Atom Smashing using Machine Learning at CERN](https://cdn.oreillystatic.com/en/assets/1/event/144/Atom%20smashing%20using%20machine%20learning%20at%20CERN%20Presentation.pdf)
	* [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)
	* [Detecting and Preventing Fraud at Uber](https://eng.uber.com/advanced-technologies-detecting-preventing-fraud-uber/)
	* [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 Intelligence at Dropbox](https://blogs.dropbox.com/tech/2018/09/machine-intelligence-at-dropbox-an-update-from-our-dbxi-team/)
	* [Machine Learning for Indexing Text from Billions of Images at Dropbox](https://blogs.dropbox.com/tech/2018/10/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)

## Architecture
* [Systems We Make](https://systemswemake.com/)
* [Tech Stack (2 parts) at Uber](https://eng.uber.com/tech-stack-part-two/)
* [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)
* [Services (2 parts) at Airbnb](https://medium.com/airbnb-engineering/building-services-at-airbnb-part-2-142be1c5d506)
* [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)
* [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)
* [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)
* [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)
* [Architecture of Play API Service at Netflix](https://qconsf.com/system/files/presentation-slides/qcon_netflix_play_api.pdf)
* [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)
* [Architectures of Finance and Banking Systems](https://www.sesameindia.com/images/core-banking-system-architecture)
	* [Reference Architecture For The Open Banking Standard](https://hortonworks.com/blog/reference-architecture-open-banking-standard/)
	* [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)

## 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.palantir.com/how-to-ace-a-systems-design-interview/)	
	* [OSI and TCP/IP Cheat Sheet](http://jaredheinrichs.com/mastering-the-osi-tcpip-models.html)
	* [The Precise Meaning of I/O Wait Time in Linux](http://veithen.github.io/2013/11/18/iowait-linux.html)
	* [Paxos Made Live – An Engineering Perspective](https://research.google.com/archive/paxos_made_live.html)
	* [How to do Distributed Locking](https://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html)
	* [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)
	* [What Happens When You Type google.com into Browser and Press Enter?](https://github.com/alex/what-happens-when)
	* [Netflix: What Happens When You Press Play?](http://highscalability.com/blog/2017/12/11/netflix-what-happens-when-you-press-play.html)
	* [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)
* [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://jobs.zalando.com/tech/blog/scaling-agile-zalando/?gh_src=4n3gxh1)
* [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://jobs.zalando.com/tech/blog/four-pillars-leadership/)
* [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/)
* [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://jobs.zalando.com/tech/blog/rotating-engineers-at-zalando/)

## 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 Reliability at Dropbox - Sat Kriya Khalsa, SRE at Dropbox](https://www.youtube.com/watch?v=IhGWOaD5BYQ)
* [Scaling with Performance at Facebook - Bill Jia, VP of Infrastructure at Facebook](https://atscaleconference.com/videos/performance-scale-2018-opening-remarks/)
* [Scaling Live Videos to a Billion Users at Facebook - Sachin Kulkarni, Director of Engineering at Facebook](https://www.youtube.com/watch?v=IO4teCbHvZw)
* [Scaling Low-latency Live Streams at Facebook (Latencies for Real-time Interactions) - Saral Shodhan, SDE at Facebook](https://atscaleconference.com/videos/scaling-low-latency-live-streams/)
* [Scaling Low-latency Live Streams at Facebook (End-to-End Considerations) - Federico Larumbe, SDE at Facebook](https://atscaleconference.com/videos/scaling-low-latency-live-streams-2-of-2/)
* [Scaling Infrastructure at Instagram - Lisa Guo, Instagram Engineering](https://www.youtube.com/watch?v=hnpzNAPiC0E)
* [Scaling Infrastructure at Twitter - Yao Yue, Staff Software Engineer at Twitter](https://www.youtube.com/watch?v=6OvrFkLSoZ0)
* [Scaling Infrastructure at Etsy - Bethany Macri, Engineering Manager at Etsy](https://www.youtube.com/watch?v=LfqyhM1LeIU)
* [Scaling Real-time Infrastructure at Alibaba for Global Shopping Holiday - Xiaowei Jiang, Senior Director at Alibaba](https://atscaleconference.com/videos/scaling-alibabas-real-time-infrastructure-for-global-shopping-holiday/)
* [Scaling Data Infrastructure at Spotify - Matti (Lepistö) Pehrs, Spotify](https://www.youtube.com/watch?v=cdsfRXr9pJU)
* [Scaling Pinterest - Marty Weiner, Pinterest’s founding engineer](https://www.youtube.com/watch?v=jQNCuD_hxdQ&list=RDhnpzNAPiC0E&index=11)
* [Scaling Slack - Bing Wei, Software Engineer (Infrastructure) at Slack](https://www.infoq.com/presentations/slack-scalability)
* [Scaling Backend at Youtube - Sugu Sougoumarane, SDE at Youtube](https://www.youtube.com/watch?v=5yDO-tmIoXY&feature=youtu.be)
* [Scaling Backend at Uber - Matt Ranney, Chief Systems Architect at Uber](https://www.youtube.com/watch?v=nuiLcWE8sPA)
* [Scaling Global CDN at Netflix - Dave Temkin, Director of Global Networks at Netflix](https://www.youtube.com/watch?v=tbqcsHg-Q_o)
* [Scaling Load Balancing Infra to Support 1.3 Billion Users at Facebook - Patrick Shuff, Production Engineer at Facebook](https://www.youtube.com/watch?v=bxhYNfFeVF4)
* [Scaling (a NSFW site) to 200 Million Views A Day And Beyond - Eric Pickup, Lead Platform Developer at MindGeek](https://www.youtube.com/watch?v=RlkCdM_f3p4)
* [Scaling Counting Infrastructure at Quora - Chun-Ho Hung and Nikhil Gar, SEs at Quora](https://www.infoq.com/presentations/quora-analytics)
* [Scaling Git at Microsoft - Saeed Noursalehi, Principal Program Manager at Microsoft](https://www.youtube.com/watch?v=g_MPGU_m01s)
* [Scaling Multitenant Architecture Across Multiple Data Centres at Shopify - Weingarten, Engineering Lead at Shopify](https://www.youtube.com/watch?v=F-f0-k46WVk)

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

#### *This project is created by [Binh Nguyen](https://www.linkedin.com/in/binhnguyennus/) in [2017 Christmas Eve](https://github.com/binhnguyennus/awesome-scalability/graphs/contributors) and is dedicated to late-night programmers who sacrifice their personal life at work! Many long hours of hard work have gone into this project. If you find it helpful, please share on Facebook, [on Twitter](https://ctt.ec/V8B2p), [on Weibo](http://t.cn/RnjFLCB), or on your chat groups! Knowledge is power, knowledge shared is power multiplied. Thank you and all the best :heart:*