# Scalable, Available, Stable, Performant, and Intelligent System Design Patterns An updated and curated list of readings to illustrate best practices and patterns in building scalable, available, stable, performant, and intelligent 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 find this project helpful, please share on your chat groups, [on Twitter](https://ctt.ec/V8B2p), or [on Weibo](http://t.cn/RnjFLCB) so more people can be helped! Power is gained by sharing knowledge, not hoarding it. Thank you! :hibiscus: ## Contents - [Principle](#principle) - [Scalability](#scalability) - [Availability](#availability) - [Stability](#stability) - [Performance](#performance) - [Intelligence](#intelligence) - [Architecture](#architecture) - [Interview](#interview) - [Organization](#organization) - [Talk](#talk) - [Book](#book) ## Principle * [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 and 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) * [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, Chief Scientist at ThoughtWorks](https://martinfowler.com/microservices/) * [Microservices Patterns](http://microservices.io/patterns/) * [Advantages and Drawbacks of Microservices](https://cloudacademy.com/blog/microservices-architecture-challenge-advantage-drawback/) * [Microservices Scale Cube](http://microservices.io/articles/scalecube.html) * [Thinking Inside the Container (8 parts) at Riot Games](https://engineering.riotgames.com/news/thinking-inside-container) * [Containerization at Pinterest](https://medium.com/@Pinterest_Engineering/containerization-at-pinterest-92295347f2f3) * [Techniques for Splitting Up a Codebase into Microservices and Artifacts at LinkedIn](https://engineering.linkedin.com/blog/2016/02/q-a-with-jim-brikman--splitting-up-a-codebase-into-microservices) * [The Evolution of Container Usage at Netflix](https://medium.com/netflix-techblog/the-evolution-of-container-usage-at-netflix-3abfc096781b) * [Dockerizing MySQL at Uber](https://eng.uber.com/dockerizing-mysql/) * [Testing of Microservices at Spotify](https://labs.spotify.com/2018/01/11/testing-of-microservices/) * [Organize Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0) * [Lessons learned running Docker in production at Treehouse](https://medium.com/treehouse-engineering/lessons-learned-running-docker-in-production-5dce99ece770) * [Inside a SoundCloud Microservice](https://developers.soundcloud.com/blog/inside-a-soundcloud-microservice) * [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) * [Distributed Caching](https://www.wix.engineering/single-post/scaling-to-100m-to-cache-or-not-to-cache) * [Read-Through, Write-Through, Write-Behind, and Refresh-Ahead Caching](https://docs.oracle.com/cd/E15357_01/coh.360/e15723/cache_rtwtwbra.htm#COHDG5177) * [Eviction Policy and Expiration Policy](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html) * [EVCache: Caching for a Global Netflix](https://medium.com/netflix-techblog/caching-for-a-global-netflix-7bcc457012f1) * [Memsniff: Robust Memcache Traffic Analyzer at Box](https://blog.box.com/blog/introducing-memsniff-robust-memcache-traffic-analyzer/) * [Caching with Consistent Hashing and Cache Smearing at Etsy](https://codeascraft.com/2017/11/30/how-etsy-caches/) * [Analysis of Photo Caching at Facebook](https://code.facebook.com/posts/220956754772273/an-analysis-of-facebook-photo-caching/) * [Cache Efficiency Exercise at Facebook](https://code.facebook.com/posts/964122680272229/web-performance-cache-efficiency-exercise/) * [tCache: Scalable Data-aware Java Caching at Trivago](http://tech.trivago.com/2015/10/15/tcache/) * [Reduce Memcached Memory Usage by 50% at Trivago](http://tech.trivago.com/2017/12/19/how-trivago-reduced-memcached-memory-usage-by-50/) * [Caching Internal Service Calls at Yelp](https://engineeringblog.yelp.com/2018/03/caching-internal-service-calls-at-yelp.html) * [Scaling Live Streaming for Large Events (with Distributed Cache) at Hulu](https://medium.com/hulu-tech-blog/scaling-hulu-live-streaming-for-large-events-march-madness-and-beyond-bedd73874f2) * [Estimating the Cache Efficiency using Big Data at Allegro](https://allegro.tech/2017/01/estimating-the-cache-efficiency-using-big-data.html) * [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) * [Distributed Tracking and Tracing](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) * [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) * [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 Security (Monitoring, Authentication, etc)](https://msdn.microsoft.com/en-us/library/cc767123.aspx) * [Approach to Security at Scale at Dropbox](https://blogs.dropbox.com/tech/2018/02/security-at-scale-the-dropbox-approach/) * [Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix](https://medium.com/netflix-techblog/introducing-aardvark-and-repokid-53b081bf3a7e) * [LISA: Distributed Firewall at LinkedIn](https://www.slideshare.net/MikeSvoboda/2017-lisa-linkedins-distributed-firewall-dfw) * [Distributed Security Alerting at Slack](https://slack.engineering/distributed-security-alerting-c89414c992d6) * [Secure Infrastructure To Store Bitcoin In The Cloud at Coinbase](https://engineering.coinbase.com/how-coinbase-builds-secure-infrastructure-to-store-bitcoin-in-the-cloud-30a6504e40ba) * [BinaryAlert: Real-time Serverless Malware Detection at Airbnb](https://medium.com/airbnb-engineering/binaryalert-real-time-serverless-malware-detection-ca44370c1b90) * [Scalable IAM Architecture to Secure Access to 100 AWS Accounts at Segment](https://segment.com/blog/secure-access-to-100-aws-accounts/) * [OAuth Audit Toolbox at Indeed](http://engineering.indeedblog.com/blog/2018/04/oaudit-toolbox/) * [Active Directory Password Blacklisting at Yelp](https://engineeringblog.yelp.com/2018/04/ad-password-blacklisting.html) * [Secure Infrastructure to Store Bitcoin in the Cloud at Coinbase](https://engineering.coinbase.com/how-coinbase-builds-secure-infrastructure-to-store-bitcoin-in-the-cloud-30a6504e40ba) * [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/) * [Job-based Forecasting Workflow for Observability Anomaly Detection at Uber](https://eng.uber.com/observability-anomaly-detection/) * [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) * [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/) * [Distributed Messaging, Queuing, and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf) * [Scaling Push Messaging for Millions of Devices at Netflix](https://www.infoq.com/presentations/neflix-push-messaging-scale) * [Samza: Stream Processing System for Latency Insighs at LinkedIn](https://engineering.linkedin.com/blog/2018/04/samza-aeon--latency-insights-for-asynchronous-one-way-flows) * [Delaying Asynchronous Message Processing with RabbitMQ at Indeed](http://engineering.indeedblog.com/blog/2017/06/delaying-messages/) * [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/) * [Benchmarking Streaming Computation Engines at Yahoo](https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at) * [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/) * [Qyu: Distributed Task Execution System for Complex Workflows at FindHotel](http://blog.findhotel.net/2018/03/qyu-a-distributed-task-execution-system-for-complex-workflows/) * [Messaging Service at Riot Games](https://engineering.riotgames.com/news/riot-messaging-service) * [Event Stream Analytics with Druid (Search Engine meet Column DB) at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7) * [Debugging Production with Event Logging at Zillow](https://www.zillow.com/engineering/debugging-production-event-logging/) * [Kafka the Message Broker](https://martin.kleppmann.com/papers/kafka-debull15.pdf) * [When to use RabbitMQ or Kafka](https://content.pivotal.io/blog/understanding-when-to-use-rabbitmq-or-apache-kafka) * [Kafka at Scale at LinkedIn](https://engineering.linkedin.com/kafka/running-kafka-scale) * [Real-time Data Pipeline with Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html) * [Building Reliable Reprocessing and Dead Letter Queues with Kafka at Uber](https://eng.uber.com/reliable-reprocessing/) * [Audit Kafka End-to-End at Uber](https://eng.uber.com/chaperone/) * [Kafka for PaaS at Rakuten](https://techblog.rakuten.co.jp/2016/01/28/rakuten-paas-kafka/) * [Publishing with Kafka at The New York Times](https://open.nytimes.com/publishing-with-apache-kafka-at-the-new-york-times-7f0e3b7d2077) * [Kafka Streams on Heroku](https://blog.heroku.com/kafka-streams-on-heroku) * [Kafka in Platform Events Architecture at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63) * [Kafka in Socket Architecture (with a Comprehensive Comparison Table) at Trello](https://tech.trello.com/why-we-chose-kafka/) * [Analytics Pipeline (Kafka, Dataflow, BigQuery) at Teads.tv](http://highscalability.com/blog/2018/4/9/give-meaning-to-100-billion-events-a-day-the-analytics-pipel.html) * [Data Deduplication Techniques](https://en.wikipedia.org/wiki/Data_deduplication) * [Exactly-once Semantics are Possible: How Kafka Does it](https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/) * [Real-time Deduping at Scale with Kafka-based Pipleline at Tapjoy](http://eng.tapjoy.com/blog-list/real-time-deduping-at-scale) * [Delivering Billions of Messages Exactly Once: Deduping at Segment](https://segment.com/blog/exactly-once-delivery/) * [Deduplication For Efficient Storage (From 50 PB To 32 PB) At Mail.Ru](https://medium.com/@andrewsumin/efficient-storage-how-we-went-down-from-50-pb-to-32-pb-99f9c61bf6b4) * [Distributed Searching](http://nwds.cs.washington.edu/files/nwds/pdf/Distributed-WR.pdf) * [Search Architecture of Instagram](https://engineering.instagram.com/search-architecture-eeb34a936d3a) * [Search Architecture of eBay](http://www.cs.otago.ac.nz/homepages/andrew/papers/2017-8.pdf) * [Improving Search Engine Efficiency by over 25% at eBay](https://www.ebayinc.com/stories/blogs/tech/making-e-commerce-search-faster/) * [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: Travel Search Engine of Expedia](http://blog.expedia.com/expedias-nautilus-travel-search-engine-overview-and-applications/) * [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/) * [Scaling Elasticsearch Clusters at Uber](https://www.infoq.com/presentations/uber-elasticsearch-clusters?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study) * [Elasticsearch Performance Tuning Practice at eBay](https://www.ebayinc.com/stories/blogs/tech/elasticsearch-performance-tuning-practice-at-ebay/) * [Elasticsearch at Kickstarter](https://kickstarter.engineering/elasticsearch-at-kickstarter-db3c487887fc) * [Distributed Troubleshooting Platform with ELK Stack at Target.com](http://target.github.io/infrastructure/distributed-troubleshooting) * [ELK at Robinhood](https://robinhood.engineering/taming-elk-4e1349f077c3) * [Log Parsing with Logstash and Google Protocol Buffers at Trivago](https://tech.trivago.com/2016/01/19/logstash_protobuf_codec/) * [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) * [Distributed Storage](http://highscalability.com/blog/2011/11/1/finding-the-right-data-solution-for-your-application-in-the.html) * [In-memory Storage](https://medium.com/@denisanikin/what-an-in-memory-database-is-and-how-it-persists-data-efficiently-f43868cff4c1) * [Introduction to In-memory Data - Viktor Gamov, Solutions Architect at Hazelcast](https://www.infoq.com/presentations/in-memory-data) * [MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)](http://highscalability.com/blog/2012/8/14/memsql-architecture-the-fast-mvcc-inmem-lockfree-codegen-and.html) * [Optimizing Memcached Efficiency at Quora](https://engineering.quora.com/Optimizing-Memcached-Efficiency) * [Real-Time Data Warehouse with MemSQL on Cisco UCS](https://blogs.cisco.com/datacenter/memsql) * [Moving to MemSQL (with Horizontally Scalable, ACID Compliant, MySQL Compatibility) at Tapjoy](http://eng.tapjoy.com/blog-list/moving-to-memsql) * [MemSQL and Kinesis for Real-time Insights at Disney-ABC TV](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/68131) * [Durable Storage (S3, HDFS)](http://www.datacenterknowledge.com/archives/2013/10/04/object-storage-the-future-of-scale-out) * [Scaling HDFS at Uber](https://eng.uber.com/scaling-hdfs/) * [Reasons for Choosing S3 over HDFS at Databricks](https://databricks.com/blog/2017/05/31/top-5-reasons-for-choosing-s3-over-hdfs.html) * [Quantcast File System on Amazon S3](https://www.quantcast.com/blog/quantcast-file-system-on-amazon-s3/) * [Data Sink with S3 at Deliveroo](https://deliveroo.engineering/2017/06/15/data-sink.html) * [Using S3 in Netflix Chukwa](https://medium.com/netflix-techblog/evolution-of-the-netflix-data-pipeline-da246ca36905) * [Yahoo Cloud Object Store - Object Storage at Exabyte Scale](https://yahooeng.tumblr.com/post/116391291701/yahoo-cloud-object-store-object-storage-at) * [Ambry: Distributed Immutable Object Store at LinkedIn](https://www.usenix.org/conference/srecon17americas/program/presentation/shenoy) * [Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb](https://medium.com/airbnb-engineering/hammerspace-persistent-concurrent-off-heap-storage-3db39bb04472) * [Relational Databases (MySQL, MSSQL, PostgreSQL)](https://www.mysql.com/products/cluster/scalability.html) * [Stop Using Shiny New Things and Love MySQL - Lesson at Pinterest](https://medium.com/@Pinterest_Engineering/learn-to-stop-using-shiny-new-things-and-love-mysql-3e1613c2ce14) * [Microsoft SQL versus MySQL](https://www.upwork.com/hiring/data/sql-vs-mysql-which-relational-database-is-right-for-you/) * [SQL Database Performance Tuning](https://www.toptal.com/sql-server/sql-database-tuning-for-developers) * [Scaling PostgreSQL Using CUDA](http://highscalability.com/blog/2009/5/28/scaling-postgresql-using-cuda.html) * [Scaling Distributed Joins](http://blog.memsql.com/scaling-distributed-joins/) * [MySQL System Design at Booking.com](https://www.percona.com/live/mysql-conference-2015/sessions/bookingcom-evolution-mysql-system-design) * [PostgreSQL at Twitch](https://blog.twitch.tv/how-twitch-uses-postgresql-c34aa9e56f58) * [Scaling MySQL-based Financial Reporting System at Airbnb](https://medium.com/airbnb-engineering/tracking-the-money-scaling-financial-reporting-at-airbnb-6d742b80f040) * [Scaling MySQL at Wix](https://www.wix.engineering/single-post/scaling-to-100m-mysql-is-a-better-nosql) * [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 MailChimp](https://devs.mailchimp.com/blog/using-shards-to-accommodate-millions-of-users/) * [Sharding MySQL at Twilio](https://www.twilio.com/engineering/2014/06/26/how-we-replaced-our-data-pipeline-with-zero-downtime) * [Sharding MySQL (3 parts) at Evernote](https://blog.evernote.com/tech/2015/10/08/the-great-shard-migration-part-ii/) * [Sharding Layer of Schemaless Datastore at Uber](https://eng.uber.com/schemaless-rewrite/) * [Sharding & IDs at Instagram](https://instagram-engineering.com/sharding-ids-at-instagram-1cf5a71e5a5c) * [Solr: Improving Performance for Batch Indexing at Box](https://blog.box.com/blog/solr-improving-performance-batch-indexing/) * [Geosharded Recommendations (3 parts) at Tinder](https://tech.gotinder.com/geosharded-recommendations-part-3-consistency/) * [NoSQL Databases](https://www.thoughtworks.com/insights/blog/nosql-databases-overview) * [Key-Value Databases (DynamoDB, Voldemort, Manhattan)](http://highscalability.com/anti-rdbms-list-distributed-key-value-stores) * [Scaling Mapbox infrastructure with DynamoDB Streams](https://blog.mapbox.com/scaling-mapbox-infrastructure-with-dynamodb-streams-d53eabc5e972) * [Manhattan: 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) * [Riak in Chat Service Architecture at Riot Games](https://engineering.riotgames.com/news/chat-service-architecture-persistence) * [MPH: Fast and Compact Immutable Key-Value Stores at Indeed](http://engineering.indeedblog.com/blog/2018/02/indeed-mph/) * [zBase: High Performance, Elastic, Distributed Key-Value Store at Zynga](https://www.zynga.com/blogs/engineering/zbase-high-performance-elastic-distributed-key-value-store-2) * [Venice: Distributed Key-Value Database at Linkedin](https://engineering.linkedin.com/blog/2017/02/building-venice-with-apache-helix) * [DynamoDB Hot Shards at Segment](https://segment.com/blog/the-million-dollar-eng-problem/) * [Columnar Databases (Cassandra, HBase, Redshift)](https://aws.amazon.com/nosql/columnar/) * [Consistent Hashing in Cassandra](https://blog.imaginea.com/consistent-hashing-in-cassandra/) * [Understanding Gossip (Cassandra Internals)](https://www.youtube.com/watch?v=FuP1Fvrv6ZQ) * [When NOT to use Cassandra?](https://stackoverflow.com/questions/2634955/when-not-to-use-cassandra) * [Avoid Pitfalls in Scaling Cassandra Cluster at Walmart](https://medium.com/walmartlabs/avoid-pitfalls-in-scaling-your-cassandra-cluster-lessons-and-remedies-a71ca01f8c04) * [Storing Images in Cassandra at Walmart](https://medium.com/walmartlabs/building-object-store-storing-images-in-cassandra-walmart-scale-a6b9c02af593) * [Cassandra at Instagram](https://www.slideshare.net/DataStax/cassandra-at-instagram-2016) * [Scale Ad Analytics with Cassandra at Yelp](https://engineeringblog.yelp.com/2016/08/how-we-scaled-our-ad-analytics-with-cassandra.html) * [Store Billions of Messages with Cassandra at Discord](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7) * [Scale to 100+ Million Reads/Writes using Spark and Cassandra at Dream11](https://medium.com/dream11-tech-blog/leaderboard-dream11-4efc6f93c23e) * [Moving Food Feed from Redis to Cassandra at Zomato](https://www.zomato.com/blog/how-we-moved-our-food-feed-from-redis-to-cassandra) * [Benchmarking Cassandra Scalability on AWS at Netflix](https://medium.com/netflix-techblog/benchmarking-cassandra-scalability-on-aws-over-a-million-writes-per-second-39f45f066c9e) * [Imgur Notification: From MySQL to HBASE at Imgur](https://blog.imgur.com/2015/09/15/tech-tuesday-imgur-notifications-from-mysql-to-hbase/) * [Improving HBase Backup Efficiency at Pinterest](https://medium.com/@Pinterest_Engineering/improving-hbase-backup-efficiency-at-pinterest-86159da4b954) * [HBase Practice at Xiaomi](https://www.slideshare.net/HBaseCon/hbase-practice-at-xiaomi) * [ClickHouse - Open Source Distributed Column Database at Yandex](https://clickhouse.yandex/) * [Scaling Redshift without Scaling Costs at GIPHY](https://engineering.giphy.com/scaling-redshift-without-scaling-costs/) * [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/) * [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.ibm.com/developerworks/library/cl-graph-database-1/index.html) * [Handling Billions of Edges in a Graph Database](https://www.infoq.com/presentations/graph-database-scalability) * [Neo4j case studies with Walmart, eBay, AirBnB, NASA, etc](https://neo4j.com/customers/) * [FlockDB: Distributed Graph Database for Storing Adjancency Lists at Twitter](https://blog.twitter.com/engineering/en_us/a/2010/introducing-flockdb.html) * [JanusGraph: Scalable Graph Database backed by Google, IBM and Hortonworks](https://architecht.io/google-ibm-back-new-open-source-graph-database-project-janusgraph-1d74fb78db6b) * [Amazon Neptune](https://aws.amazon.com/neptune/) * [Datastructure Databases (Redis, Hazelcast)](https://db-engines.com/en/system/Hazelcast%3BMemcached%3BRedis) * [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 (TSDB)](https://www.influxdata.com/time-series-database/) * [What is Time-Series Data & Why We Need a Time-Series Database](https://blog.timescale.com/what-the-heck-is-time-series-data-and-why-do-i-need-a-time-series-database-dcf3b1b18563) * [Time Series Data: Why and How to Use a Relational Database instead of NoSQL](https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c) * [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/) * [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) * [HTTP Caching (Reverse Proxy, CDN)](https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching) * [Reverse Proxy (Nginx, Varnish, Squid, rack-cache)](https://www.mertech.com/overview-reverse-proxying/) * [Stop Worrying and Love the Proxy](https://blog.turbinelabs.io/how-we-learned-to-stop-worrying-and-love-the-proxy-89af98fabaf8) * [Playing HTTP Tricks with Nginx](https://www.elastic.co/blog/playing-http-tricks-nginx) * [Using CDN to Improve Site Performance at Coursera](https://building.coursera.org/blog/2015/07/09/improving-coursera-global-site-performance-a-head-to-head-cdn-battle-with-production-traffic/) * [Strategy: Caching 404s Saved 66% On Server Time at The Onion](http://highscalability.com/blog/2010/3/26/strategy-caching-404s-saved-the-onion-66-on-server-time.html) * [Increasing Application Performance with HTTP Cache Headers](https://devcenter.heroku.com/articles/increasing-application-performance-with-http-cache-headers) * [Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga](https://www.zynga.com/blogs/engineering/zynga-geo-proxy-reducing-mobile-game-latency) * [Google AMP at Condé Nast](https://technology.condenast.com/story/the-why-and-how-of-google-amp-at-conde-nast) * [Running A/B Tests on Hosting Infrastructure (CDNs) at Deliveroo](https://deliveroo.engineering/2016/09/19/ab-testing-cdns.html) * [HAProxy with Kubernetes for User-facing Traffic at SoundCloud](https://developers.soundcloud.com/blog/how-soundcloud-uses-haproxy-with-kubernetes-for-user-facing-traffic) * [Bandaid: Service Proxy at Dropbox](https://blogs.dropbox.com/tech/2018/03/meet-bandaid-the-dropbox-service-proxy/) * [CDN in LIVE's Encoder Layer at LINE](https://engineering.linecorp.com/en/blog/detail/230) * [Load Balancing](https://blog.vivekpanyam.com/scaling-a-web-service-load-balancing/) * [Introduction to Modern Network Load Balancing and Proxying](https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236) * [Load Balancing infrastructure to support more than 1.3 billion users at Facebook](https://www.usenix.org/conference/srecon15europe/program/presentation/shuff) * [DHCPLB: 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/) * [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) * [Autoscaling](https://medium.com/@BotmetricHQ/top-11-hard-won-lessons-learned-about-aws-auto-scaling-5bfe56da755f) * [A Horror Movie Featuring Auto Scaling Groups, EBS Volumes, Terraform, and Bash](https://blog.gruntwork.io/yak-shaving-series-1-all-i-need-is-a-little-bit-of-disk-space-6e5ef1644f67) * [Autoscaling Pinterest](https://medium.com/@Pinterest_Engineering/auto-scaling-pinterest-df1d2beb4d64) * [Autoscaling Based on Request Queuing at Square](https://medium.com/square-corner-blog/autoscaling-based-on-request-queuing-c4c0f57f860f) * [Autoscaling Applications at PayPal](https://www.paypal-engineering.com/2017/08/16/autoscaling-applications-paypal/) * [Autoscaling Jenkins at Trivago](http://tech.trivago.com/2017/02/17/your-definite-guide-for-autoscaling-jenkins/) * [Automated Infrastructure Cost Optimization at Scale with AWS EC2 RI at Quora](https://engineering.quora.com/Automated-Infrastructure-Cost-Optimization-at-Scale-with-AWS-EC2-Reserved-Instances) * [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) * [Concurrency](http://joeduffyblog.com/2016/11/30/15-years-of-concurrency/) * [Message-Passing Concurrency](https://link.springer.com/chapter/10.1007/978-3-642-35170-9_11) * [Software Transactional Memory](https://dl.acm.org/citation.cfm?id=3037750) * [Dataflow Concurrency](http://www.marketwired.com/press-release/java-concurrency-and-scalability-platform-akka-celebrates-fifth-anniversary-1928674.htm) * [Shared-State Concurrency](https://doc.rust-lang.org/book/second-edition/ch16-03-shared-state.html) * [Concurrency series by Larry Osterman (Principal SDE at Microsoft)](https://social.msdn.microsoft.com/Profile/Larry%2bOsterman%2b%5BMSFT%5D/activity) * [Part 8 – Concurrency for scalability](https://blogs.msdn.microsoft.com/larryosterman/2005/02/28/concurrency-part-8-concurrency-for-scalability/) * [Part 9 - APIs that enable scalable programming](https://blogs.msdn.microsoft.com/larryosterman/2005/03/02/concurrency-part-9-apis-that-enable-scalable-programming/) * [Part 10 - How do you know if you’ve got a scalability issue?](https://blogs.msdn.microsoft.com/larryosterman/2005/03/03/concurrency-part-10-how-do-you-know-if-youve-got-a-scalability-issue/) * [Part 11 – Hidden scalability issues](https://blogs.msdn.microsoft.com/larryosterman/2005/03/04/concurrency-part-11-hidden-scalability-issues/) * [Part 12 – Hidden scalability issues (cont)](https://blogs.msdn.microsoft.com/larryosterman/2005/03/07/concurrency-part-12-hidden-scalability-issues-part-2/) * [Concurrency with Erlang](http://learnyousomeerlang.com/the-hitchhikers-guide-to-concurrency) * [Erlang in WhatsApp](https://blog.whatsapp.com/196/1-million-is-so-2011) * [Erlang in Riot Chat Server](https://engineering.riotgames.com/news/chat-service-architecture-servers) * [How Discord Scaled Elixir to Five Millions Concurrent Users](https://blog.discordapp.com/scaling-elixir-f9b8e1e7c29b) * [Mnesia: A Distributed DBMS Rooted in Concurrency](https://www.developer.com/db/article.php/3864331/Mnesia-A-Distributed-DBMS-Rooted-in-Concurrency.htm) * [Mesia and CAP](https://medium.com/@jlouis666/mnesia-and-cap-d2673a92850) * [Running Concurrent Queries in GoSocial (Go and Neo4j) at Medium](https://medium.engineering/running-concurrent-queries-in-gosocial-28e5841b05b5) * [The Secret To 10 Million Concurrent Connections](http://highscalability.com/blog/2013/5/13/the-secret-to-10-million-concurrent-connections-the-kernel-i.html) * [Parallel Computing](https://blogs.msdn.microsoft.com/ddperf/2009/05/02/are-we-taking-advantage-of-parallelism/) * [SPMD (Single Program Multiple Data): The Genetic Pattern](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-186.html) * [Master/Worker Pattern](https://docs.gigaspaces.com/sbp/master-worker-pattern.html) * [Loop Parallelism Pattern: Extracting parallel tasks from loops](https://www.cs.umd.edu/class/fall2001/cmsc411/projects/unroll/main.htm) * [Fork/Join Pattern: Good for recursive data processing](http://highscalability.com/learn-how-exploit-multiple-cores-better-performance-and-scalability) * [Map-Reduce: Born for Simplified Data Processing on Large Clusters](http://static.googleusercontent.com/media/research.google.com/en/us/archive/mapreduce-osdi04.pdf) * [On the Death of Map-Reduce - Henry Robinson, Cloudera](https://www.the-paper-trail.org/post/2014-06-25-the-elephant-was-a-trojan-horse-on-the-death-of-map-reduce-at-google/) * [Server-side Optimization to Parallelize the Rendering of Web Pages at Yelp](https://engineeringblog.yelp.com/2017/07/generating-web-pages-in-parallel-with-pagelets.html) * [Accelerator: Data Processing Framework with Fast Data Access and Parallel Execution at eBay](https://www.ebayinc.com/stories/blogs/tech/announcing-the-accelerator-processing-1-000-000-000-lines-per-second-on-a-single-computer/) * [Event-Driven Architecture](https://martinfowler.com/articles/201701-event-driven.html) * [Pub-Sub Messaging](https://aws.amazon.com/pub-sub-messaging/) * [Autoscaling Pub-Sub Consumers at Spotify](https://labs.spotify.com/2017/11/20/autoscaling-pub-sub-consumers/) * [Pulsar: Pub-Sub Messaging at Scale at Yahoo](https://yahooeng.tumblr.com/post/150078336821/open-sourcing-pulsar-pub-sub-messaging-at-scale) * [Wormhole: Pub-Sub system at Facebook (2013)](https://code.facebook.com/posts/188966771280871/wormhole-pub-sub-system-moving-data-through-space-and-time/) * [Pub-Sub in Chatting Architecture at LINE](https://engineering.linecorp.com/en/blog/detail/85) * [Domain Events](https://martinfowler.com/eaaDev/DomainEvent.html) * [Domain Events: Simple and Reliable Solution](http://enterprisecraftsmanship.com/2017/10/03/domain-events-simple-and-reliable-solution/) * [Domain-Driven Design in Organizing Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0) * [Modelling for Domain Driven Design at Moonpig](https://engineering.moonpig.com/development/modelling-for-domain-driven-design) * [Event Sourcing](https://martinfowler.com/eaaDev/EventSourcing.html) * [Event Sourced Architectures for High Availability](https://www.infoq.com/presentations/Event-Sourced-Architectures-for-High-Availability) * [Event Sourcing and Stream Processing at Scale](https://martin.kleppmann.com/2016/01/29/event-sourcing-stream-processing-at-ddd-europe.html) * [Scaling Event Sourcing for Netflix Downloads](https://www.infoq.com/presentations/netflix-scale-event-sourcing) * [Scaling Event-Sourcing at Jet.com](https://medium.com/@eulerfx/scaling-event-sourcing-at-jet-9c873cac33b8) * [Event Sourcing (2 parts) at eBay](https://www.ebayinc.com/stories/blogs/tech/event-sourcing-in-action-with-ebays-continuous-delivery-team/) * [Command & Query Responsibility Segregation (CQRS)](https://docs.microsoft.com/en-us/azure/architecture/patterns/cqrs) * [Exploring CQRS and Event Sourcing - MSDN (with free ebook)](https://msdn.microsoft.com/en-us/library/jj554200.aspx) * [CQRS Simple Architecture](https://www.future-processing.pl/blog/cqrs-simple-architecture/) * [Building Scalable Applications Using Event Sourcing and CQRS with Kafka](https://initiate.andela.com/event-sourcing-and-cqrs-a-look-at-kafka-e0c1b90d17d8) * [Stream Processing, Event Sourcing, Reactive, CEP, etc - Martin Kleppmann](https://www.confluent.io/blog/making-sense-of-stream-processing/) * [Point-To-Point and Its Differences from Pub-Sub](https://www.journaldev.com/9743/jms-messaging-models) * [Store-Forward](https://docs.oracle.com/cd/E13222_01/wls/docs91/saf_admin/overview.html) * [Request-Reply](https://docs.tibco.com/pub/ftl/4.3.0/doc/html/GUID-A64ABED1-682E-4E1D-A94A-5590CB91B9BB.html) * [Enterprise Service Bus](http://www.oracle.com/technetwork/articles/soa/ind-soa-esb-1967705.html) * [Distributed Source Code, 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) * [ZooKeeper at Twitter](https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/zookeeper-at-twitter.html) ## 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/) * [Availability in Globally Distributed Storage Systems](http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36737.pdf) * [NodeJS High Availability at Yahoo](https://yahooeng.tumblr.com/post/68823943185/nodejs-high-availability) * [Every Day is Monday in Operations (11 parts) at LinkedIn ](https://www.linkedin.com/pulse/introduction-every-day-monday-operations-benjamin-purgason) * [How Robust Monitoring Powers High Availability for LinkedIn Feed](https://www.usenix.org/conference/srecon17americas/program/presentation/barot) * [Architectural Patterns for High Availability - Adrian Cockcroft, Director of Architecture at Netflix](https://www.infoq.com/presentations/Netflix-Architecture) * [Supporting Global Events at Facebook](https://code.facebook.com/posts/166966743929963/how-production-engineers-support-global-events-on-facebook/) * [Backends High Availability at BlaBlaCar](https://medium.com/blablacar-tech/the-expendables-backends-high-availability-at-blablacar-8cea3b95b26b) * [Chubby: Lock Service for Loosely Coupled Distributed Systems at Google](https://blog.acolyer.org/2015/02/13/the-chubby-lock-service-for-loosely-coupled-distributed-systems/) * [Tips for High Availability at Netflix](https://medium.com/@NetflixTechBlog/tips-for-high-availability-be0472f2599c) * [Scaling High-Availability Infrastructure in the Cloud at Twilio](https://www.twilio.com/engineering/2011/12/12/scaling-high-availablity-infrastructure-in-cloud) ## Stability * [Circuit Breaker](https://martinfowler.com/bliki/CircuitBreaker.html) * [Circuit Breaking in Distributed Systems](https://www.infoq.com/presentations/circuit-breaking-distributed-systems) * [Circuit Breakers for Distributed Services at LINE](https://engineering.linecorp.com/en/blog/detail/76) * [Applying Circuit Breaker to Channel Gateway at LINE](https://engineering.linecorp.com/en/blog/detail/78) * [Lessons in Resilience at SoundCloud](https://developers.soundcloud.com/blog/lessons-in-resilience-at-SoundCloud) * [Circuit Breaker for Scaling Containers](https://f5.com/about-us/blog/articles/the-art-of-scaling-containers-circuit-breakers-28919) * [Protector: Circuit Breaker for Time Series Databases at Trivago](http://tech.trivago.com/2016/02/23/protector/) * [Improved Production Stability with Circuit Breakers at Heroku](https://blog.heroku.com/improved-production-stability-with-circuit-breakers) * [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) * [Performance Testing with SSDs (2 parts) at MailChimp](https://devs.mailchimp.com/blog/performance-testing-with-ssds-pt-2/) * [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) * [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) * [Performance Optimization by Tuning Garbage Collection](https://confluence.atlassian.com/enterprise/garbage-collection-gc-tuning-guide-461504616.html) * [Garbage Collection Optimization for High-Throughput and Low-Latency Java Applications at LinkedIn](https://engineering.linkedin.com/garbage-collection/garbage-collection-optimization-high-throughput-and-low-latency-java-applications) * [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/) * [Using Java Large Heap (110 GB) at Expedia](https://techblog.expedia.com/2015/09/25/solving-problems-with-very-large-java-heaps/) * [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 Video, Image, Page Load](https://developers.google.com/web/fundamentals/performance/why-performance-matters/) * [Optimizing 360 Photos at Scale at Facebook](https://code.facebook.com/posts/129055711052260/optimizing-360-photos-at-scale/) * [Reducing Image File Size in the Photos Infrastructure at Etsy](https://codeascraft.com/2017/05/30/reducing-image-file-size-at-etsy/) * [Improving GIF Performance at Pinterest](https://medium.com/@Pinterest_Engineering/improving-gif-performance-on-pinterest-8dad74bf92f1) * [Optimizing Video Playback Performance at Pinterest](https://medium.com/@Pinterest_Engineering/optimizing-video-playback-performance-caf55ce310d1) * [Optimizing Video Stream for Low Bandwidth with Dynamic Optimizer at Netflix](https://medium.com/netflix-techblog/optimized-shot-based-encodes-now-streaming-4b9464204830) * [Adaptive Video Streaming at YouTube](https://youtube-eng.googleblog.com/2018/04/making-high-quality-video-efficient.html) * [Reducing Video Loading Time by Prefetching during Preroll at Dailymotion](http://engineering.dailymotion.com/reducing-video-loading-time-prefetching-video-during-preroll/) * [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://techblog.expedia.com/2018/03/09/go-fast-or-go-home-the-process-of-optimizing-for-client-performance/) ## Intelligence * [Big Data](https://insights.sei.cmu.edu/sei_blog/2017/05/reference-architectures-for-big-data-systems.html) * [Data Platform at 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) * [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) * [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/) * [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/) * [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) * [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) * [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) * [Distributed Machine Learning](https://www.csie.ntu.edu.tw/~cjlin/talks/bigdata-bilbao.pdf) * [Michelangelo: Machine Learning Platform at Uber](https://eng.uber.com/michelangelo/) * [Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber](https://eng.uber.com/horovod/) * [COTA: Improving Customer Care with NLP & Machine Learning at Uber](https://eng.uber.com/cota/) * [Repo-Topix: Topic Extraction Framework at Github](https://githubengineering.com/topics/) * [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) * [Training ML Models with Airflow and BigQuery at WePay](https://wecode.wepay.com/posts/training-machine-learning-models-with-airflow-and-bigquery) * [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/) * [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection) * [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/) * [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) * [Using Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) * [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) * [Real-Time News Alerting at Bloomberg](https://www.infoq.com/presentations/news-alerting-bloomberg) * [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) ## 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) * [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) * [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) * [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) * [Simone: Distributed Simulation Service at Netflix](https://medium.com/netflix-techblog/https-medium-com-netflix-techblog-simone-a-distributed-simulation-service-b2c85131ca1b) * [Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp](https://engineeringblog.yelp.com/2017/04/how-yelp-runs-millions-of-tests-every-day.html) * [MySQL Realtime Traffic Emulator at KakaoTalk](http://tech.kakao.com/2016/02/16/opensource-2-mtre/) * [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) * [Distributed Cron at Quora](https://engineering.quora.com/Quoras-Distributed-Cron-Architecture) * [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) * [Architectures of Finance and Banking Systems](https://www.sesameindia.com/images/core-banking-system-architecture) * [Reference Architecture For The Open Banking Standard](https://hortonworks.com/blog/reference-architecture-open-banking-standard/) * [Building a Modern Bank Backend at Monzo](https://monzo.com/blog/2016/09/19/building-a-modern-bank-backend/) * [Reinventing the Trading Platform for Scale at Wealthsimple](https://medium.com/@Wealthsimple/engineering-at-wealthsimple-reinventing-our-trading-platform-for-scale-17e332241b6c) * [Architecture for 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) ## 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 Expedia Finds your Flights: A Detailed View](https://techblog.expedia.com/2016/03/07/how-expedia-finds-flights-a-detailed-view/) * [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) * [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) * [Code Review Best Practices at Palantir](https://medium.com/@palantir/code-review-best-practices-19e02780015f) * [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/) ## 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/) ## Special Thanks * Jonas Bonér, CTO at Lightbend, for the [original inspiration](https://www.slideshare.net/jboner/scalability-availability-stability-patterns) ## License [![CC-BY](https://mirrors.creativecommons.org/presskit/buttons/88x31/svg/by.svg)](https://creativecommons.org/licenses/by/4.0/) This project is created and maintained by [Quoc-Binh Nguyen](https://www.linkedin.com/in/binhnguyennus/), R&D Software Engineer at The Agency for Science, Technology and Research of Singapore (A*Star). Thank You & Happy Coding :heart: