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인터넷에서 System Design을 공부하기 위한 최고의 리소스들입니다.

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# System Design Resources
인터넷에서 찾을 수 있는 최고의 System Design 관련 리소스 모음입니다.

# Table of Contents

- [Video Processing](#video-processing)
- [Cluster and Workflow Management](#cluster-and-workflow-management)
- [Intra-Service Messaging](#intra-service-messaging)
- [Message Queue Antipattern](#message-queue-antipattern)
- [Service Mesh](#service-mesh)
- [Practical System Design](#practical-system-design)
- [Distributed File System](#distributed-file-system)
- [Time Series Databases](#time-series-databases)
- [Rate Limiting](#rate-limiting)
- [In Memory Database - Redis](#in-memory-database---redis)
- [Network Protocols](#network-protocols)
- [Chess Engine Design](#chess-engine-design)
- [Subscription Management System](#subscription-management-system)
- [Google Docs](#google-docs)
- [API Design](#api-design)
- [NoSQL Database Internals](#nosql-database-internals)
- [NoSQL Database Algorithms](#nosql-database-algorithms)
- [Database Replication](#database-replication)
- [Containers and Docker](#containers-and-docker)
- [Capacity Estimation](#capacity-estimation)
- [Publisher Subscriber](#publisher-subscriber)
- [Event Driven Architectures](#event-driven-architectures)
- [Software Architectures](#software-architectures)
- [Microservices](#microservices)
- [Distributed Transactions consistency Patterns](#distributed-transactions-consistency-patterns)
- [Load Balancing](#load-balancing)
- [Alerts and Anomaly Detection](#alerts-and-anomaly-detection)
- [Distributed Logging](#distributed-logging)
- [Metrics and Text Search Engine](#metrics-and-text-search-engine)
- [Single Point of Failure](#single-point-of-failure)
- [Location Based Services](#location-based-services)
- [Batch Processing](#batch-processing)
- [Real Time Stream Processing](#real-time-stream-processing)
- [Caching](#caching)
- [Distributed Consensus](#distributed-consensus)
- [Authorization](#authorization)
- [Content Delivery Network](#content-delivery-network)
- [Testing Distributed Systems](#testing-distributed-systems)
- [System Design Resources](#system-design-resources)

##
## Video Processing
- [Transcoding Videos at Scale](https://www.egnyte.com/blog/post/transcoding-how-we-serve-videos-at-scale)
- [Facebook Video Broadcasting](https://engineering.fb.com/ios/under-the-hood-broadcasting-live-video-to-millions/)
- [Netflix Video Encoding at Scale](https://netflixtechblog.com/high-quality-video-encoding-at-scale-d159db052746)
- [Netflix Shot based encoding](https://netflixtechblog.com/optimized-shot-based-encodes-now-streaming-4b9464204830)

##
## Cluster and Workflow Management
- [Facebook Cluster Management](https://engineering.fb.com/data-center-engineering/twine/)
- [Google Autopilot - Autoscaling](https://dl.acm.org/doi/pdf/10.1145/3342195.3387524)
- [Netflix Workflow Orchestration](https://netflixtechblog.com/netflix-conductor-a-microservices-orchestrator-2e8d4771bf40)
- [Opensource Workflow Management](https://github.com/spotify/luigi)
- [Meta Hardware Management](https://engineering.fb.com/2020/12/09/data-center-engineering/how-facebook-keeps-its-large-scale-infrastructure-hardware-up-and-running/)
- [Meta Capacity Assignment](https://engineering.fb.com/2022/09/06/data-center-engineering/viewing-the-world-as-a-computer-global-capacity-management/)
- [Amazon EC2](https://www.allthingsdistributed.com/2015/07/under-the-hood-of-the-amazon-ec2-container-service.html)

##
## Intra-Service Messaging
- [What is a message queue](https://www.cloudamqp.com/blog/what-is-message-queuing.html)
- [AirBnb Idempotency](https://medium.com/airbnb-engineering/avoiding-double-payments-in-a-distributed-payments-system-2981f6b070bb)
- [Meta Async Task Computing](https://engineering.fb.com/2023/01/31/production-engineering/meta-asynchronous-computing/)

## 메시지 큐 안티패턴
- [DB as queue Antipattern](https://en.wikipedia.org/wiki/Database-as-IPC)
- [Using a database as a message queue](https://softwareengineering.stackexchange.com/questions/231410/why-database-as-queue-so-bad)
- [Anti-pattern of DB as a queue](http://mikehadlow.blogspot.com/2012/04/database-as-queue-anti-pattern.html)
- [Drawbacks of DB as a queue](https://www.cloudamqp.com/blog/why-is-a-database-not-the-right-tool-for-a-queue-based-system.html)

##
## Service Mesh
- [Kubernetes Service Mesh](https://akomljen.com/kubernetes-service-mesh/)
- [Kubernetes Sidecar](https://www.weave.works/blog/introduction-to-service-meshes-on-kubernetes-and-progressive-delivery)
- [Service Mesh](https://www.weave.works/blog/introduction-to-service-meshes-on-kubernetes-and-progressive-delivery)
- [NginX Service Mesh](https://docs.nginx.com/nginx-service-mesh/about/what-is-nsm/)
- [Data Plane and Control Plane](https://blog.envoyproxy.io/service-mesh-data-plane-vs-control-plane-2774e720f7fc)

##
## 실용적인 시스템 디자인
- [Facebook Messenger Optimisations](https://spectrum.ieee.org/how-facebooks-software-engineers-prepare-messenger-for-new-years-eve)
- [YouTube Architecture](http://highscalability.com/youtube-architecture)
- [YouTube scalability 2012](https://www.youtube.com/watch?v=w5WVu624fY8)
- [Distributed Design Patterns](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html)
- [Monolith to Microservice](https://martinfowler.com/articles/break-monolith-into-microservices.html)
- [Zerodha Tech Stack](https://zerodha.tech/blog/hello-world/)

##
## 분산 파일 시스템
- [Open Source Distributed File System](https://docs.ceph.com/en/latest/architecture/)
- [Amazon S3 Performance hacks](https://aws.amazon.com/blogs/aws/amazon-s3-performance-tips-tricks-seattle-hiring-event/)
- [Amazon S3 object expiration](https://aws.amazon.com/blogs/aws/amazon-s3-object-expiration/)

##
## 시계열 데이터베이스
- [Pinterest Time Series Database](https://medium.com/pinterest-engineering/goku-building-a-scalable-and-high-performant-time-series-database-system-a8ff5758a181)
- [Uber Time Series DB](https://eng.uber.com/aresdb/)
- [TimeSeries Relational DB](https://blog.timescale.com/blog/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c)
- [Facebook Gorilla Time Series DB](http://www.vldb.org/pvldb/vol8/p1816-teller.pdf)

##
## 속도 제한 (Rate Limiting)
- [Circuit Breaker Algorithm](https://martinfowler.com/bliki/CircuitBreaker.html)
- [Uber Rate Limiter](https://github.com/uber-go/ratelimit/blob/master/ratelimit.go)

##
## 인메모리 데이터베이스 - Redis
- [Redis Official Documentation](https://redis.com/)
- [Learn Redis through Redis University](https://university.redis.com/)
- [Redis Open Source Repo](https://github.com/redis/redis)
- [Redis Architecture](https://medium.com/opstree-technology/redis-cluster-architecture-replication-sharding-and-failover-86871e783ac0)

##
## 네트워크 프로토콜
- [What is HTTP](https://engineering.cred.club/head-of-line-hol-blocking-in-http-1-and-http-2-50b24e9e3372)
- [QUIC Protocol](https://www.akamai.com/blog/performance/http3-and-quic-past-present-and-future)
- [TCP Protocol algorithms](https://ee.lbl.gov/papers/congavoid.pdf) (처음 10페이지가 중요함)
- [WebRTC](https://webrtc.github.io/webrtc-org/blog/2012/07/23/a-great-introduction-to-webrtc.html)
- [WebSockets](https://datatracker.ietf.org/doc/html/rfc6455#section-1.2)
- [Dynamic Source Routing using QUIC](https://fb.watch/fSEbI4KHlA/)

##
## 체스 엔진 디자인
- [Chess Engine Building](https://www.youtube.com/watch?v=U4ogK0MIzqk)

##
## 구독 관리 시스템
- [Subscription Manager](https://netflixtechblog.com/building-a-rule-based-platform-to-manage-netflix-membership-skus-at-scale-e3c0f82aa7bc)

##
## Google Docs
- [Operational Transform](http://www.codecommit.com/blog/java/understanding-and-applying-operational-transformation)
- [Google Docs](https://www.youtube.com/watch?v=uOFzWZrsPV0&list=PLX)
- [Lumiere](https://www.arxiv.org/abs/2401.12945)

## 
## API Design

- [API Design at Airbnb](https://medium.com/airbnb-engineering/building-services-at-airbnb-part-1-c4c1d8fa811b)
- [Swagger APIs](https://swagger.io/docs/specification/about/)

##
## NoSQL Database Internals

- [Cassandra Architecture](https://docs.datastax.com/en/archived/cassandra/3.0/cassandra/architecture/archIntro.html)
- [Google BigTable Architecture](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
- [Amazon Dynamo DB Internals](https://www.allthingsdistributed.com/2007/10/amazons_dynamo.html)
- [Design Patterns in Amazon Dynamo DB](https://www.youtube.com/watch?v=HaEPXoXVf2k)
- [Internals of Amazon Dynamo DB](https://www.youtube.com/watch?v=yvBR71D0nAQ)

##
## NoSQL Database Algorithms

- [Hyperloglog Algorithm](https://odino.org/my-favorite-data-structure-hyperloglog/)
- [Log Structured Merge Tree](https://www.cs.umb.edu/~poneil/lsmtree.pdf)
- [Sorted String Tables and Compaction Strategies](https://github.com/scylladb/scylla/wiki/SSTable-compaction-and-compaction-strategies)
- [Leveled Compaction Cassandra](https://www.datastax.com/blog/leveled-compaction-apache-cassandra)
- [Scylla DB Compaction](https://github.com/scylladb/scylla/wiki/SSTable-compaction-and-compaction-strategies)
- [Indexing in Cassandra](https://www.bmc.com/blogs/cassandra-clustering-columns-partition-composite-key/)

##
## Database Replication

- [Database replication](https://dev.mysql.com/doc/refman/8.0/en/replication.html)
- [Netflix Data replication - Change Data Capture](https://netflixtechblog.com/dblog-a-generic-change-data-capture-framework-69351fb9099b)
- [LinkedIn Logging Usecases](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying)
- [Uber Trillions of indexes in LedgerStore](https://www.uber.com/en-IN/blog/how-ledgerstore-supports-trillions-of-indexes)

##
## Containers and Docker

- [Facebook Twine Containerization](https://engineering.fb.com/developer-tools/zookeeper-twine/)
- [CloudFlare Containerization](https://blog.cloudflare.com/cloud-computing-without-containers/)
- [Docker Architecture](https://docs.docker.com/get-started/overview/#docker-architecture)

##
## Capacity Estimation

- [Google Capacity Estimation](https://www.youtube.com/watch?v=modXC5IWTJI)
- [Scalability at YouTube 2012](https://www.youtube.com/watch?v=G-lGCC4KKok)
- [Back of envelope Calculations at AWS](https://www.youtube.com/watch?v=-3qetLv2Yp0)
- [Capacity Estimation](http://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf)

##
## Publisher Subscriber

- [Oracle Publisher Subscriber](https://docs.oracle.com/cd/B10501_01/appdev.920/a96590/adg15pub.htm)
- [Amazon Pub Sub Messaging](https://aws.amazon.com/pub-sub-messaging/)
- [Asynchronous processing](http://blog.codepath.com/2013/01/06/asynchronous-processing-in-web-applications-part-2-developers-need-to-understand-message-queues/)
- [Async Request Response](https://www.enterpriseintegrationpatterns.com/patterns/conversation/RequestResponse.html)

##
## Event Driven Architectures

- [Martin Fowler- Event Driven Architecture](https://www.youtube.com/watch?v=STKCRSUsyP0)
- [Event Driven Architecture](https://martinfowler.com/articles/201701-event-driven.html)

##
## Software Architectures

- [Hexagonal Architecture](https://netflixtechblog.com/ready-for-changes-with-hexagonal-architecture-b315ec967749)
- [Hexagonal architecture (Alistair Cockburn)](https://alistair.cockburn.us/hexagonal-architecture/)
- [The Clean Code by Robert C. Martin (Uncle Bob)](https://blog.cleancoder.com/uncle-bob/2012/08/13/the-clean-architecture.html)
- [CQRS](https://martinfowler.com/bliki/CQRS.html)
- [DomainDrivenDesign](https://martinfowler.com/bliki/DomainDrivenDesign.html)

##
## 마이크로서비스 (Microservices)

- [Monolith Architecture](https://buttercms.com/books/microservices-for-startups/should-you-always-start-with-a-monolith/)
- [Monoliths vs Microservices](https://articles.microservices.com/monolithic-vs-microservices-architecture-5c4848858f59)
- [Microservices](http://highscalability.com/blog/2018/4/5/do-you-have-too-many-microservices-five-design-attributes-th.html)
- [Uber Nanoservices antipattern](https://www.youtube.com/watch?v=kb-m2fasdDY)
- [Uber Domain oriented microservice](https://eng.uber.com/microservice-architecture/)

##
## 분산 트랜잭션 일관성 패턴 (Distributed Transactions consistency Patterns)

- [Transactional outbox](https://microservices.io/patterns/data/transactional-outbox.html)
- [SAGAS Long lived transactions (LLTs)](https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf)

##
## 로드 밸런싱 (Load Balancing)

- [Load Balancer with Sticky Sessions](https://stackoverflow.com/questions/10494431/sticky-and-non-sticky-sessions)
- [NetScaler what is load balancing](https://www.netscaler.com/articles/what-is-load-balancing)
- [Nginx Load Balancing](https://www.nginx.com/resources/glossary/load-balancing/)
- [Consistent hashing](https://michaelnielsen.org/blog/consistent-hashing/)
- [Minimizing connection churn](https://netflixtechblog.com/curbing-connection-churn-in-zuul-2feb273a3598#5e4d)
- [Google Subsetting Algorithm](https://queue.acm.org/detail.cfm?id=3570937)

##
## 경고 및 이상 탐지 (Alerts and Anomaly Detection)

- [Outlier Detection](https://towardsdatascience.com/outlier-detection-with-isolation-forest-3d190448d45e)
- [Anomaly Detection](https://towardsdatascience.com/machine-learning-for-anomaly-detection-and-condition-monitoring-d4614e7de770)
- [Uber Real Time Monitoring and Root Cause Analysis Argos](https://eng.uber.com/argos-real-time-alerts/)
- [Microsoft Anomaly Detection](https://www.youtube.com/watch?v=12Xq9OLdQwQ&t=0s)
- [Facebook Data Engineering](https://engineering.fb.com/2016/05/09/core-data/introducing-fblearner-flow-facebook-s-ai-backbone/)
- [LinkedIn Real Time Alerting](https://engineering.linkedin.com/blog/2019/06/smart-alerts-in-thirdeye--linkedins-real-time-monitoring-platfor)
- [LinkedIn Isolation Forests](https://engineering.linkedin.com/blog/2019/isolation-forest)

##
## 분산 로깅 (Distributed Logging)

- [Uber Distributed Request Tracing](https://eng.uber.com/distributed-tracing/)
- [Pintrest Logging](https://medium.com/@Pinterest_Engineering/open-sourcing-singer-pinterests-performant-and-reliable-logging-agent-610fecf35566)
- [Google Monitoring Infrastructure](https://www.facebook.com/atscaleevents/videos/959344524420015/)

##
## 메트릭 및 텍스트 검색 엔진 (Metrics and Text Search Engine)

- [Facebook real-time text search engine](https://www.facebook.com/watch/?v=432864835468)
- [Elastic Search Time Based Querying](https://www.elastic.co/guide/en/elasticsearch/guide/current/time-based.html)
- [Elastic Search Aggregation](https://www.elastic.co/guide/en/elasticsearch/guide/current/aggregations.html)

##
## 단일 장애점 (Single Point of Failure)

- [단일 장애점 피하기 (Avoiding Single Points of Failure)](https://medium.com/the-cloud-architect/patterns-for-resilient-architecture-part-3-16e8601c488e)
- [Netflix 다중 리전 가용성 (Netflix Multi-Region Availability)](https://netflixtechblog.com/active-active-for-multi-regional-resiliency-c47719f6685b)
- [Oracle 단일 장애점 (Oracle Single Points of failure)](https://docs.oracle.com/cd/E19693-01/819-0992/fjdch/index.html)
- [DNS 단일 장애점 2004 (DNS single point of failure 2004)](http://www.tenereillo.com/GSLBPageOfShame.htm)
- [Shopify의 DNS 트래픽 관리 (DNS traffic management by Shopify)](https://shopify.engineering/introduction-dns-traffic-management)
- [샤딩 (Sharding)](https://medium.com/@jeeyoungk/how-sharding-works-b4dec46b3f6)

##
## 위치 기반 서비스 (Location Based Services)

- [Google S2 라이브러리 (Google S2 library)](https://blog.christianperone.com/2015/08/googles-s2-geometry-on-the-sphere-cells-and-hilbert-curve/)

##
## 배치 처리 (Batch Processing)

- [Map Reduce 아키텍처 (Map Reduce Architecture)](https://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)

##
## 실시간 스트림 처리 (Real Time Stream Processing)

- [LinkedIn Brooklin - 실시간 데이터 스트리밍 (LinkedIn Brooklin- Real-time data streaming)](https://engineering.linkedin.com/blog/2019/brooklin-open-source)
- [Netflix 실시간 스트림 처리 (Netflix Real Time Stream Processing)](https://netflixtechblog.com/keystone-real-time-stream-processing-platform-a3ee651812a)
- [Kafka용 KSQLDB (KSQLDB for Kafka)](https://docs.ksqldb.io/en/latest/operate-and-deploy/how-it-works/)
- [Netflix Psyberg (Netflix Psyberg)](https://netflixtechblog.com/1-streamlining-membership-data-engineering-at-netflix-with-psyberg-f68830617dd1)

##
## 캐싱 (Caching)

- [Google Guava Cache (Google Guava Cache)](https://github.com/google/guava/wiki/CachesExplained)
- [캐싱 (README 참고) (Caching (See the README))](https://github.com/ben-manes/caffeine/)
- [캐싱 (Caching)](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
- [Microsoft 캐싱 가이드 (Microsoft Caching Guide)](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn589802(v%3dpandp.10))
- [캐싱 패턴 (Caching patterns)](https://hazelcast.com/blog/a-hitchhikers-guide-to-caching-patterns/)
- [초당 4,000만 건의 읽기를 위한 Uber의 통합 캐시 (Uber's Integrated Cache for 40M RPS)](https://www.uber.com/en-IN/blog/how-uber-serves-over-40-million-reads-per-second-using-an-integrated-cache)

##
## 분산 합의 (Distributed consensus)

- [Paxos (Paxos)](http://ifeanyi.co/posts/understanding-consensus/)
- [Raft (Raft)](https://raft.github.io/)

##
## 권한 부여 (Authorization)

- [엔터프라이즈를 위한 권한 부여 모델 설계 (Designing an Authorization Model for an Enterprise)](https://cerbos.dev/blog/designing-an-authorization-model-for-an-enterprise)
- [클라우드 네이티브 권한 부여 시스템의 아키텍처 패턴 (The Architectural Patterns of Cloud-native Authorization Systems)](https://www.aserto.com/blog/5-laws-cloud-native-authorization)

##
## 콘텐츠 전송 네트워크 (Content Delivery Network)

- [S3를 활용한 AWS CloudFront CDN (AWS CloudFront CDN with S3)](https://aws.amazon.com/blogs/networking-and-content-delivery/amazon-s3-amazon-cloudfront-a-match-made-in-the-cloud/)

##
## 분산 시스템 테스트 (Testing Distributed Systems)

- [결정론적 테스트 (Deterministic Testing)](https://www.youtube.com/watch?v=4fFDFbi3toc)
- [Leslie Lamport의 TLA+ (TLA+ by Leslie Lamport)](https://lamport.azurewebsites.net/tla/tla.html)
- [Jepsen (Jepsen)](https://jenpsen.io)

##
## 시스템 디자인 리소스 (System Design Resources)

- [데이터 중심 애플리케이션 설계 도서 (Designing Data-Intensive Applications Book)](https://amzn.to/3SyNAOy)
- [백서 (WhitePapers)](https://interviewready.io/blog/white-papers-worth-reading-for-software-engineers)
- [InterviewReady 비디오 (InterviewReady Videos)](https://interviewready.io?source=github)
- [시스템 디자인 온라인 저지 (System Design Online Judge)](https://interviewready.io/question-list/system-design-judge)

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