These are the best resources for System Design on the Internet.
Transcoding Videos at Scale: https://www.egnyte.com/blog/2018/12/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
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://netflix.github.io/conductor/
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/
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
Nginx Service Mesh: https://www.nginx.com/learn/service-mesh/
DB as queue Antipattern: http://blog.codepath.com/2012/11/15/asynchronous-processing-in-web-applications-part-1-a-database-is-not-a-queue/
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
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://www.nginx.com/learn/service-mesh/
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
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/
Pintrest 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
Circuit Breaker Algorithm: https://martinfowler.com/bliki/CircuitBreaker.html
Uber Rate Limiter: https://github.com/uber-go/ratelimit/blob/master/ratelimit.go
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
Chess Engine Building: https://www.youtube.com/watch?v=U4ogK0MIzqk
Subscription Manager: https://netflixtechblog.com/building-a-rule-based-platform-to-manage-netflix-membership-skus-at-scale-e3c0f82aa7bc
Operational Transform: http://www.codecommit.com/blog/java/understanding-and-applying-operational-transformation
Google Docs: https://www.youtube.com/watch?v=uOFzWZrsPV0&list=PLXDe3d8o9VFtydBV5biyz9iS3WqKsBMD5&index=3
API Design: https://medium.com/airbnb-engineering/building-services-at-airbnb-part-1-c4c1d8fa811b
Swagger APIs: https://swagger.io/docs/specification/about/
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
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: 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
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
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
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
Martin Fowler- Event Driven Architecture: https://www.youtube.com/watch?v=STKCRSUsyP0
Event Driven Architecture: https://martinfowler.com/articles/201701-event-driven.html
Hexagonal Architecture: https://netflixtechblog.com/ready-for-changes-with-hexagonal-architecture-b315ec967749
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/
Load Balancer with Sticky Sessions: https://stackoverflow.com/questions/10494431/sticky-and-non-sticky-sessions
Citrix what is load balancing: https://www.citrix.com/en-in/solutions/app-delivery-and-security/load-balancing/what-is-load-balancing.html
Nginx Load Balancing: https://www.nginx.com/resources/glossary/load-balancing/
Consistent hashing: https://michaelnielsen.org/blog/consistent-hashing/
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
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/
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
Avoiding Single Points of Failure: https://medium.com/the-cloud-architect/patterns-for-resilient-architecture-part-3-16e8601c488e
Netflix Multi-Region Availability: https://netflixtechblog.com/active-active-for-multi-regional-resiliency-c47719f6685b
Oracle Single Points of failure: https://docs.oracle.com/cd/E19693-01/819-0992/fjdch/index.html
DNS single point of failure 2004: http://www.tenereillo.com/GSLBPageOfShame.htm
Sharding: https://medium.com/@jeeyoungk/how-sharding-works-b4dec46b3f6
Google S2 library: https://blog.christianperone.com/2015/08/googles-s2-geometry-on-the-sphere-cells-and-hilbert-curve/
LinkedIn Brooklin- Real time data streaming: https://engineering.linkedin.com/blog/2019/brooklin-open-source
Netflix Real Time Stream Processing: https://netflixtechblog.com/keystone-real-time-stream-processing-platform-a3ee651812a
Google Guava Cache: https://github.com/google/guava/wiki/CachesExplained
Caching (See the README): https://github.com/ben-manes/caffeine/
Caching: http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html
Microsoft Caching Guide: https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn589802(v%3dpandp.10)
Caching patterns: https://hazelcast.com/blog/a-hitchhikers-guide-to-caching-patterns/
Paxos: http://ifeanyi.co/posts/understanding-consensus/
Raft: https://raft.github.io/