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!Logo (/logo.png) (http://awesome-scalability.com/)
An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers 
and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users.
An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken
from battle-tested systems that serve millions to billions of users.
If your system goes slow
▐ 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.
▐ 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
▐ "Even if you lose all one day, you can build all over again if you retain your calm!" - Thuan Pham, former CTO of Uber. So, keep calm and mind the availability (#availability) and stability
▐ (#stability) matters! 
▐ "Even if you lose all one day, you can build all over again if you retain your calm!" - Thuan Pham, former CTO of Uber. So, keep calm and mind the availability (#availability) and stability (#stability) matters! 
If you are having a system design interview
▐ 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. Good luck!
▐ 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. Good luck!
If you are building your dream team
▐ 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.
▐ 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
▐ Contributions are greatly welcome! You may want to take a look at the contribution guidelines (CONTRIBUTING.md). If you see a link here that is no longer maintained or is not a good fit, 
▐ please submit a pull request!
▐ Contributions are greatly welcome! You may want to take a look at the contribution guidelines (CONTRIBUTING.md). If you see a link here that is no longer maintained or is not a good fit, please submit a pull request!
▐ Many long hours of hard work have gone into this project. If you find it helpful, please share on Facebook, on Twitter (https://ctt.ec/V8B2p), on Weibo (http://t.cn/RnjFLCB), or on your 
▐ chat groups! Knowledge is power, knowledge shared is power multiplied. Thank you!
▐ Many long hours of hard work have gone into this project. If you find it helpful, please share on Facebook, on Twitter (https://ctt.ec/V8B2p), on Weibo (http://t.cn/RnjFLCB), or on your chat groups! Knowledge is power, knowledge 
▐ shared is power multiplied. Thank you!
Content
- Principle (#principle)
@@ -76,8 +73,7 @@
⟡ 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) 
⟡ 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)
@@ -119,8 +115,7 @@
* **Nanoservices at BBC** (https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b) 
* **PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg** (https://www.techatbloomberg.com/blog/powerfulseal-testing-tool-kubernetes-clusters/) 
* **Conductor: Microservices Orchestrator at Netflix** (https://medium.com/netflix-techblog/netflix-conductor-a-microservices-orchestrator-2e8d4771bf40) 
* **Docker Containers that Power Over 100.000 Online Shops at Shopify** (https://shopifyengineering.myshopify.com/blogs/engineering/docker-at-shopify-how-we-built-containers-that-power-over-1 
00-000-online-shops) 
* **Docker Containers that Power Over 100.000 Online Shops at Shopify** (https://shopifyengineering.myshopify.com/blogs/engineering/docker-at-shopify-how-we-built-containers-that-power-over-100-000-online-shops)
* **Microservice Architecture at Medium** (https://medium.engineering/microservice-architecture-at-medium-9c33805eb74f) 
* **From bare-metal to Kubernetes at Betabrand** (https://boxunix.com/post/bare_metal_to_kube/) 
* **Kubernetes at Tinder** (https://medium.com/tinder-engineering/tinders-move-to-kubernetes-cda2a6372f44) 
@@ -153,8 +148,7 @@
* **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-1091ae80f 
74c) 
* **Storing Hundreds of Millions of Simple Key-Value Pairs in Redis at Instagram** (https://engineering.instagram.com/storing-hundreds-of-millions-of-simple-key-value-pairs-in-redis-1091ae80f74c) 
* **Redis at Trivago** (http://tech.trivago.com/2017/01/25/learn-redis-the-hard-way-in-production/) 
* **Optimizing Redis Storage at Deliveroo** (https://deliveroo.engineering/2017/01/19/optimising-membership-queries.html) 
* **Memory Optimization in Redis at Wattpad** (http://engineering.wattpad.com/post/23244724794/store-more-stuff-memory-optimization-in-redis) 
@@ -163,8 +157,7 @@
* **Ratings & Reviews (2 parts) at Flipkart** (https://blog.flipkart.tech/ratings-reviews-flipkart-part-2-574ab08e75cf) 
* **Prefetch Caching of Items at eBay** (https://tech.ebayinc.com/engineering/prefetch-caching-of-ebay-items/) 
* **Cross-Region Caching Library at Wix** (https://www.wix.engineering/post/how-we-built-a-cross-region-caching-library) 
* **Improving Distributed Caching Performance and Efficiency at Pinterest** (https://medium.com/pinterest-engineering/improving-distributed-caching-performance-and-efficiency-at-pinterest-924 
84b5fe39b) 
* **Improving Distributed Caching Performance and Efficiency at Pinterest** (https://medium.com/pinterest-engineering/improving-distributed-caching-performance-and-efficiency-at-pinterest-92484b5fe39b)
* **Standardize and Improve Microservices Caching at DoorDash** (https://doordash.engineering/2023/10/19/how-doordash-standardized-and-improved-microservices-caching/) 
* **HTTP Caching and CDN** (https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching) 
 * **Zynga Geo Proxy: Reducing Mobile Game Latency at Zynga** (https://www.zynga.com/blogs/engineering/zynga-geo-proxy-reducing-mobile-game-latency) 
@@ -185,8 +178,7 @@
* **Improve Zipkin Traces using Kubernetes Pod Metadata at SoundCloud** (https://developers.soundcloud.com/blog/using-kubernetes-pod-metadata-to-improve-zipkin-traces) 
* **Canopy: Scalable Distributed Tracing & Analysis at Facebook** (https://www.infoq.com/presentations/canopy-scalable-tracing-analytics-facebook) 
* **Pintrace: Distributed Tracing at Pinterest** (https://medium.com/@Pinterest_Engineering/distributed-tracing-at-pinterest-with-new-open-source-tools-a4f8a5562f6b) 
* **XCMetrics: All-in-One Tool for Tracking Xcode Build Metrics at Spotify** (https://engineering.atspotify.com/2021/01/20/introducing-xcmetrics-our-all-in-one-tool-for-tracking-xcode-build-m 
etrics/) 
* **XCMetrics: All-in-One Tool for Tracking Xcode Build Metrics at Spotify** (https://engineering.atspotify.com/2021/01/20/introducing-xcmetrics-our-all-in-one-tool-for-tracking-xcode-build-metrics/)
* **Real-time Distributed Tracing at LinkedIn** (https://engineering.linkedin.com/distributed-service-call-graph/real-time-distributed-tracing-website-performance-and-efficiency)  
* **Tracking Service Infrastructure at Scale at Shopify** (https://www.usenix.org/conference/srecon17americas/program/presentation/arthorne)  
* **Distributed Tracing at HelloFresh** (https://engineering.hellofresh.com/scaling-hellofresh-distributed-tracing-7b182928247d) 
@@ -253,8 +245,7 @@
* **WebAuthn Support for Secure Sign In at Dropbox** (https://blogs.dropbox.com/tech/2018/05/introducing-webauthn-support-for-secure-dropbox-sign-in/) 
* **Security Development Lifecycle 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) 
* **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/) 
@@ -274,8 +265,7 @@
* **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/) 
* **Dynein: Distributed Delayed Job Queueing System at Airbnb** (https://medium.com/airbnb-engineering/dynein-building-a-distributed-delayed-job-queueing-system-93ab10f05f99) 
* **Timestone: Queueing System for Non-Parallelizable Workloads at Netflix** (https://netflixtechblog.com/timestone-netflixs-high-throughput-low-latency-priority-queueing-system-with-built-in 
-support-1abf249ba95f) 
* **Timestone: Queueing System for Non-Parallelizable Workloads at Netflix** (https://netflixtechblog.com/timestone-netflixs-high-throughput-low-latency-priority-queueing-system-with-built-in-support-1abf249ba95f)
* **Messaging Service at Riot Games** (https://engineering.riotgames.com/news/riot-messaging-service) 
* **Debugging Production with Event Logging at Zillow** (https://www.zillow.com/engineering/debugging-production-event-logging/) 
* **Cross-platform In-app Messaging Orchestration Service at Netflix** (https://medium.com/netflix-techblog/building-a-cross-platform-in-app-messaging-orchestration-service-86ba614f92d8) 
@@ -296,8 +286,7 @@
 * **Scaling Event-Sourcing at Jet.com** (https://medium.com/@eulerfx/scaling-event-sourcing-at-jet-9c873cac33b8) 
 * **Event Sourcing (2 parts) at eBay** (https://www.ebayinc.com/stories/blogs/tech/event-sourcing-in-action-with-ebays-continuous-delivery-team/) 
 * **Event Sourcing at FREE NOW** (https://medium.com/inside-freenow/event-sourcing-an-evolutionary-perspective-31e7387aa6f1) 
 * **Scalable content feed using Event Sourcing and CQRS patterns at Brainly** (https://medium.com/engineering-brainly/scalable-content-feed-using-event-sourcing-and-cqrs-patterns-e09df98bf977 
) 
 * **Scalable content feed using Event Sourcing and CQRS patterns at Brainly** (https://medium.com/engineering-brainly/scalable-content-feed-using-event-sourcing-and-cqrs-patterns-e09df98bf977) 
* **Pub-Sub Messaging** (https://aws.amazon.com/pub-sub-messaging/) 
 * **Pulsar: Pub-Sub Messaging at Scale at Yahoo** (https://yahooeng.tumblr.com/post/150078336821/open-sourcing-pulsar-pub-sub-messaging-at-scale) 
 * **Wormhole: Pub-Sub System at Facebook** (https://code.facebook.com/posts/188966771280871/wormhole-pub-sub-system-moving-data-through-space-and-time/) 
@@ -318,8 +307,7 @@
 * **Chaperone: Audit Kafka End-to-End at Uber** (https://eng.uber.com/chaperone/) 
 * **Finding Kafka throughput limit in infrastructure at Dropbox** (https://blogs.dropbox.com/tech/2019/01/finding-kafkas-throughput-limit-in-dropbox-infrastructure/) 
 * **Cost Orchestration at Walmart** (https://medium.com/walmartlabs/cost-orchestration-at-walmart-f34918af67c4) 
 * **InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second at Hulu** (https://medium.com/hulu-tech-blog/how-hulu-uses-influxdb-and-kafka-to-scale-to-over-1-million-metrics-a-second-17 
21476aaff5) 
 * **InfluxDB and Kafka to Scale to Over 1 Million Metrics a Second at Hulu** (https://medium.com/hulu-tech-blog/how-hulu-uses-influxdb-and-kafka-to-scale-to-over-1-million-metrics-a-second-1721476aaff5) 
 * **Scaling Kafka to Support Data Growth at PayPal** (https://medium.com/paypal-tech/scaling-kafka-to-support-paypals-data-growth-a0b4da420fab) 
* **Stream Data Deduplication** (https://en.wikipedia.org/wiki/Data_deduplication) 
 * **Exactly-once Semantics with Kafka** (https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/) 
@@ -330,8 +318,7 @@
⟡ Distributed Logging (https://blog.codinghorror.com/the-problem-with-logging/)
* **Logging at LinkedIn** (https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying) 
* **Scalable and Reliable Log Ingestion at Pinterest** (https://medium.com/@Pinterest_Engineering/scalable-and-reliable-data-ingestion-at-pinterest-b921c2ee8754) 
* **High-performance Replicated Log Service at Twitter** (https://blog.twitter.com/engineering/en_us/topics/infrastructure/2015/building-distributedlog-twitter-s-high-performance-replicated-l 
og-servic.html) 
* **High-performance Replicated Log Service at Twitter** (https://blog.twitter.com/engineering/en_us/topics/infrastructure/2015/building-distributedlog-twitter-s-high-performance-replicated-log-servic.html)
* **Logging Service with Spark at CERN Accelerator** (https://databricks.com/blog/2017/12/14/the-architecture-of-the-next-cern-accelerator-logging-service.html) 
* **Logging and Aggregation at Quora** (https://engineering.quora.com/Logging-and-Aggregation-at-Quora) 
* **Collection and Analysis of Daemon Logs at Badoo** (https://badoo.com/techblog/blog/2016/06/06/collection-and-analysis-of-daemon-logs-at-badoo/) 
@@ -368,11 +355,9 @@
 * **Predictions in Real Time with ELK at Uber** (https://eng.uber.com/elk/) 
 * **Building a scalable ELK stack at Envato** (https://webuild.envato.com/blog/building-a-scalable-elk-stack/) 
 * **ELK at Robinhood** (https://robinhood.engineering/taming-elk-4e1349f077c3) 
 * **Scaling Elasticsearch Clusters at Uber** (https://www.infoq.com/presentations/uber-elasticsearch-clusters?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study 
) 
 * **Scaling Elasticsearch Clusters at Uber** (https://www.infoq.com/presentations/uber-elasticsearch-clusters?utm_source=presentations_about_Case_Study&utm_medium=link&utm_campaign=Case_Study) 
 * **Elasticsearch Performance Tuning Practice at eBay** (https://www.ebayinc.com/stories/blogs/tech/elasticsearch-performance-tuning-practice-at-ebay/) 
 * **Improve Performance using Elasticsearch Plugins (2 parts) at Tinder** (https://medium.com/tinder-engineering/how-we-improved-our-performance-using-elasticsearch-plugins-part-2-b051da2ee85 
b) 
 * **Improve Performance using Elasticsearch Plugins (2 parts) at Tinder** (https://medium.com/tinder-engineering/how-we-improved-our-performance-using-elasticsearch-plugins-part-2-b051da2ee85b)
 * **Elasticsearch at Kickstarter** (https://kickstarter.engineering/elasticsearch-at-kickstarter-db3c487887fc) 
 * **Log Parsing with Logstash and Google Protocol Buffers at Trivago** (https://tech.trivago.com/2016/01/19/logstash_protobuf_codec/) 
 * **Fast Order Search using Data Pipeline and Elasticsearch at Yelp** (https://engineeringblog.yelp.com/2018/06/fast-order-search.html) 
@@ -382,8 +367,7 @@
 * **Vulcanizer: a library for operating Elasticsearch at Github** (https://github.blog/2019-03-05-vulcanizer-a-library-for-operating-elasticsearch/)  
⟡ Distributed Storage (http://highscalability.com/blog/2011/11/1/finding-the-right-data-solution-for-your-application-in-the.html)
* **In-memory Storage** (https://medium.com/@denisanikin/what-an-in-memory-database-is-and-how-it-persists-data-efficiently-f43868cff4c1) 
 * **MemSQL Architecture - The Fast (MVCC, InMem, LockFree, CodeGen) And Familiar (SQL)** (http://highscalability.com/blog/2012/8/14/memsql-architecture-the-fast-mvcc-inmem-lockfree-codegen-an 
d.html) 
 * **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 at Tapjoy** (http://eng.tapjoy.com/blog-list/moving-to-memsql) 
@@ -396,11 +380,9 @@
 * **Image Recovery at Scale Using S3 Versioning at Trivago** (https://tech.trivago.com/2018/09/03/efficient-image-recovery-at-scale-using-amazon-s3-versioning/) 
 * **Cloud Object Store at Yahoo** (https://yahooeng.tumblr.com/post/116391291701/yahoo-cloud-object-store-object-storage-at) 
 * **Ambry: Distributed Immutable Object Store at LinkedIn** (https://www.usenix.org/conference/srecon17americas/program/presentation/shenoy) 
 * **Dynamometer: Scale Testing HDFS on Minimal Hardware with Maximum Fidelity at LinkedIn** (https://engineering.linkedin.com/blog/2018/02/dynamometer--scale-testing-hdfs-on-minimal-hardware- 
with-maximum) 
 * **Dynamometer: Scale Testing HDFS on Minimal Hardware with Maximum Fidelity at LinkedIn** (https://engineering.linkedin.com/blog/2018/02/dynamometer--scale-testing-hdfs-on-minimal-hardware-with-maximum)
 * **Hammerspace: Persistent, Concurrent, Off-heap Storage at Airbnb** (https://medium.com/airbnb-engineering/hammerspace-persistent-concurrent-off-heap-storage-3db39bb04472) 
 * **MezzFS: Mounting Object Storage in Media Processing Platform at Netflix** (https://medium.com/netflix-techblog/mezzfs-mounting-object-storage-in-netflixs-media-processing-platform-cda01c4 
46ba)  
 * **MezzFS: Mounting Object Storage in Media Processing Platform at Netflix** (https://medium.com/netflix-techblog/mezzfs-mounting-object-storage-in-netflixs-media-processing-platform-cda01c446ba)  
 * **Magic Pocket: In-house Multi-exabyte Storage System at Dropbox** (https://blogs.dropbox.com/tech/2016/05/inside-the-magic-pocket/) 
⟡ Relational Databases (https://www.mysql.com/products/cluster/scalability.html)
* **Building and Deploying MySQL Raft at Meta** (https://engineering.fb.com/2023/05/16/data-infrastructure/mysql-raft-meta/) 
@@ -414,8 +396,7 @@
* **Handling Growth with Postgres at Instagram** (https://engineering.instagram.com/handling-growth-with-postgres-5-tips-from-instagram-d5d7e7ffdfcb) 
* **Scaling the Analytics Database (Postgres) at TransferWise** (http://tech.transferwise.com/scaling-our-analytics-database/) 
* **Updating a 50 Terabyte PostgreSQL Database at Adyen** (https://medium.com/adyen/updating-a-50-terabyte-postgresql-database-f64384b799e7) 
* **Scaling Database Access for 100s of Billions of Queries per Day at PayPal** (https://medium.com/paypal-engineering/scaling-database-access-for-100s-of-billions-of-queries-per-day-paypal-i 
ntroducing-hera-e192adacda54) 
* **Scaling Database Access for 100s of Billions of Queries per Day at PayPal** (https://medium.com/paypal-engineering/scaling-database-access-for-100s-of-billions-of-queries-per-day-paypal-introducing-hera-e192adacda54)
* **Minimizing Read-Write MySQL Downtime at Yelp** (https://engineeringblog.yelp.com/2020/11/minimizing-read-write-mysql-downtime.html) 
* **Migrating MySQL from 5.6 to 8.0 at Facebook** (https://engineering.fb.com/2021/07/22/data-infrastructure/mysql/) 
* **Migration from HBase to MyRocks at Quora** (https://quoraengineering.quora.com/Migration-from-HBase-to-MyRocks-at-Quora) 
@@ -468,8 +449,7 @@
 * **Benchmarking Cassandra Scalability on AWS at Netflix** (https://medium.com/netflix-techblog/benchmarking-cassandra-scalability-on-aws-over-a-million-writes-per-second-39f45f066c9e) 
 * **Service Decomposition at Scale with Cassandra at Intuit QuickBooks** (https://quickbooks-engineering.intuit.com/service-decomposition-at-scale-70405ac2f637) 
 * **Cassandra for Keeping Counts In Sync at SoundCloud** (https://developers.soundcloud.com/blog/keeping-counts-in-sync) 
 * **Cassandra Driver Configuration for Improved Performance and Load Balancing at Glassdoor** (https://medium.com/glassdoor-engineering/cassandra-driver-configuration-for-improved-performance 
-and-load-balancing-1b0106ce12bb) 
 * **Cassandra Driver Configuration for Improved Performance and Load Balancing at Glassdoor** (https://medium.com/glassdoor-engineering/cassandra-driver-configuration-for-improved-performance-and-load-balancing-1b0106ce12bb)
 * **cstar: Cassandra Orchestration Tool at Spotify** (https://labs.spotify.com/2018/09/04/introducing-cstar-the-spotify-cassandra-orchestration-tool-now-open-source/) 
 * **HBase** (https://hbase.apache.org/) 
 * **HBase at Salesforce** (https://engineering.salesforce.com/investing-in-big-data-apache-hbase-b9d98661a66b) 
@@ -482,10 +462,8 @@
 * **Redshift at Hudl** (https://www.hudl.com/bits/the-low-hanging-fruit-of-redshift-performance) 
 * **Redshift at Drivy** (https://drivy.engineering/redshift_tips_ticks_part_1/) 
* **Document Databases** (https://msdn.microsoft.com/en-us/magazine/hh547103.aspx) 
 * **eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB** (https://www.mongodb.com/blog/post/ebay-building-mission-critical-multi-data-center-applications-with-mongodb 
) 
 * **MongoDB at Baidu: Multi-Tenant Cluster Storing 200+ Billion Documents across 160 Shards** (https://www.mongodb.com/blog/post/mongodb-at-baidu-powering-100-apps-across-600-nodes-at-pb-scal 
e) 
 * **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) 
@@ -526,8 +504,7 @@
* **Dynamic Configuration at GoDaddy** (https://sg.godaddy.com/engineering/2019/03/06/dynamic-configuration-for-nodejs/) 
⟡ Scaling Continuous Integration and Continuous Delivery (https://www.synopsys.com/blogs/software-security/agile-cicd-devops-glossary/)
* **Continuous Integration Stack at Facebook** (https://code.fb.com/web/rapid-release-at-massive-scale/) 
* **Continuous Integration with Distributed Repositories and Dependencies at Netflix** (https://medium.com/netflix-techblog/towards-true-continuous-integration-distributed-repositories-and-de 
pendencies-2a2e3108c051) 
* **Continuous Integration with Distributed Repositories and Dependencies at Netflix** (https://medium.com/netflix-techblog/towards-true-continuous-integration-distributed-repositories-and-dependencies-2a2e3108c051)
* **Continuous Integration and Deployment with Bazel at Dropbox** (https://blogs.dropbox.com/tech/2019/12/continuous-integration-and-deployment-with-bazel/) 
* **Continuous Deployments at BuzzFeed** (https://tech.buzzfeed.com/continuous-deployments-at-buzzfeed-d171f76c1ac4) 
* **Screwdriver: Continuous Delivery Build System for Dynamic Infrastructure at Yahoo** (https://yahooeng.tumblr.com/post/155765242061/open-sourcing-screwdriver-yahoos-continuous) 
@@ -618,25 +595,21 @@
* **Circuit Breaker at Traveloka** (https://medium.com/traveloka-engineering/circuit-breakers-dont-let-your-dependencies-bring-you-down-5ba1c5cf1eec)
* **Circuit Breaker at Shopify** (https://shopify.engineering/circuit-breaker-misconfigured) 
⟡ Timeouts (https://www.javaworld.com/article/2824163/application-performance/stability-patterns-applied-in-a-restful-architecture.html)
* **Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Netflix** (https://medium.com/netflix-techblog/fault-tolerance-in-a-high-volume-distributed-syst 
em-91ab4faae74a) 
* **Fault Tolerance (Timeouts and Retries, Thread Separation, Semaphores, Circuit Breakers) at Netflix** (https://medium.com/netflix-techblog/fault-tolerance-in-a-high-volume-distributed-system-91ab4faae74a)
* **Enforce Timeout: A Reliability Methodology at DoorDash** (https://doordash.engineering/2018/12/21/enforce-timeout-a-doordash-reliability-methodology/) 
* **Troubleshooting a Connection Timeout Issue with tcp_tw_recycle Enabled at eBay** (https://www.ebayinc.com/stories/blogs/tech/a-vip-connection-timeout-issue-caused-by-snat-and-tcp-tw-recyc 
le/) 
* **Troubleshooting a Connection Timeout Issue with tcp_tw_recycle Enabled at eBay** (https://www.ebayinc.com/stories/blogs/tech/a-vip-connection-timeout-issue-caused-by-snat-and-tcp-tw-recycle/) 
⟡ Crash-safe Replication for MySQL at Booking.com (https://medium.com/booking-com-infrastructure/better-crash-safe-replication-for-mysql-a336a69b317f)
⟡ Bulkheads: Partition and Tolerate Failure in One Part (https://skife.org/architecture/fault-tolerance/2009/12/31/bulkheads.html)
⟡ Steady State: Always Put Logs on Separate Disk (https://docs.microsoft.com/en-us/sql/relational-databases/policy-based-management/place-data-and-log-files-on-separate-drives)
⟡ Throttling: Maintain a Steady Pace (http://www.sosp.org/2001/papers/welsh.pdf)
⟡ Multi-Clustering: Improving Resiliency and Stability of a Large-scale Monolithic API Service at LinkedIn
 (https://engineering.linkedin.com/blog/2017/11/improving-resiliency-and-stability-of-a-large-scale-api)
⟡ Multi-Clustering: Improving Resiliency and Stability of a Large-scale Monolithic API Service at LinkedIn (https://engineering.linkedin.com/blog/2017/11/improving-resiliency-and-stability-of-a-large-scale-api)
⟡ Determinism (4 parts) in League of Legends Server (https://engineering.riotgames.com/news/determinism-league-legends-fixing-divergences)
Performance
⟡ Performance Optimization on OS, Storage, Database, Network (https://stackify.com/application-performance-metrics/)
* **Improving Performance with Background Data Prefetching at Instagram** (https://engineering.instagram.com/improving-performance-with-background-data-prefetching-b191acb39898) 
* **Fixing Linux filesystem performance regressions at LinkedIn** (https://engineering.linkedin.com/blog/2020/fixing-linux-filesystem-performance-regressions) 
* **Compression Techniques to Solve Network I/O Bottlenecks at eBay** (https://www.ebayinc.com/stories/blogs/tech/how-ebays-shopping-cart-used-compression-techniques-to-solve-network-io-bottl 
enecks/) 
* **Compression Techniques to Solve Network I/O Bottlenecks at eBay** (https://www.ebayinc.com/stories/blogs/tech/how-ebays-shopping-cart-used-compression-techniques-to-solve-network-io-bottlenecks/) 
* **Optimizing Web Servers for High Throughput and Low Latency at Dropbox** (https://blogs.dropbox.com/tech/2017/09/optimizing-web-servers-for-high-throughput-and-low-latency/) 
* **Linux Performance Analysis in 60.000 Milliseconds at Netflix** (https://medium.com/netflix-techblog/linux-performance-analysis-in-60-000-milliseconds-accc10403c55) 
* **Live Downsizing Google Cloud Persistent Disks (PD-SSD) at Mixpanel** (https://engineering.mixpanel.com/2018/07/31/live-downsizing-google-cloud-pds-for-fun-and-profit/) 
@@ -658,17 +631,14 @@
* **API Profiling at Pinterest** (https://medium.com/@Pinterest_Engineering/api-profiling-at-pinterest-6fa9333b4961) 
* **Pagelets Parallelize Server-side Processing at Yelp** (https://engineeringblog.yelp.com/2017/07/generating-web-pages-in-parallel-with-pagelets.html) 
* **Improving key expiration in Redis at Twitter** (https://blog.twitter.com/engineering/en_us/topics/infrastructure/2019/improving-key-expiration-in-redis.html) 
* **Ad Delivery Network Performance Optimization with Flame Graphs at MindGeek** (https://medium.com/mindgeek-engineering-blog/ad-delivery-network-performance-optimization-with-flame-graphs-b 
c550cf59cf7) 
* **Ad Delivery Network Performance Optimization with Flame Graphs at MindGeek** (https://medium.com/mindgeek-engineering-blog/ad-delivery-network-performance-optimization-with-flame-graphs-bc550cf59cf7)
* **Predictive CPU isolation of containers at Netflix** (https://medium.com/netflix-techblog/predictive-cpu-isolation-of-containers-at-netflix-91f014d856c7) 
* **Improving HDFS I/O Utilization for Efficiency at Uber** (https://eng.uber.com/improving-hdfs-i-o-utilization-for-efficiency/) 
* **Cloud Jewels: Estimating kWh in the Cloud at Etsy** (https://codeascraft.com/2020/04/23/cloud-jewels-estimating-kwh-in-the-cloud/) 
* **Unthrottled: Fixing CPU Limits in the Cloud (2 parts) at Indeed** (https://engineering.indeedblog.com/blog/2019/12/unthrottled-fixing-cpu-limits-in-the-cloud/) 
⟡ Performance Optimization by Tuning Garbage Collection (https://confluence.atlassian.com/enterprise/garbage-collection-gc-tuning-guide-461504616.html)
* **Garbage Collection in Java Applications at LinkedIn** (https://engineering.linkedin.com/garbage-collection/garbage-collection-optimization-high-throughput-and-low-latency-java-application 
s) 
* **Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe** (https://medium.com/adobetech/engineering-high-throughput-low-latency-machine-learning-services-7d4 
5edac0271) 
* **Garbage Collection in Java Applications at LinkedIn** (https://engineering.linkedin.com/garbage-collection/garbage-collection-optimization-high-throughput-and-low-latency-java-applications) 
* **Garbage Collection in High-Throughput, Low-Latency Machine Learning Services at Adobe** (https://medium.com/adobetech/engineering-high-throughput-low-latency-machine-learning-services-7d45edac0271)
* **Garbage Collection in Redux Applications at SoundCloud** (https://developers.soundcloud.com/blog/garbage-collection-in-redux-applications) 
* **Garbage Collection in Go Application at Twitch** (https://blog.twitch.tv/go-memory-ballast-how-i-learnt-to-stop-worrying-and-love-the-heap-26c2462549a2) 
* **Analyzing V8 Garbage Collection Logs at Alibaba** (https://www.linux.com/blog/can-nodejs-scale-ask-team-alibaba) 
@@ -734,13 +704,10 @@
* **Analytics Pipeline at Grammarly** (https://tech.grammarly.com/blog/building-a-versatile-analytics-pipeline-on-top-of-apache-spark) 
* **Analytics Pipeline at Teads** (https://medium.com/teads-engineering/give-meaning-to-100-billion-analytics-events-a-day-d6ba09aa8f44) 
* **ML Data Pipelines for Real-Time Fraud Prevention at PayPal** (https://www.infoq.com/presentations/paypal-ml-fraud-prevention-2018) 
* **Big Data Analytics and ML Techniques at LinkedIn** (https://cdn.oreillystatic.com/en/assets/1/event/269/Big%20data%20analytics%20and%20machine%20learning%20techniques%20to%20drive%20and%2 
0grow%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%20P 
resentation%201.pdf) 
* **Big Data Analytics and ML Techniques at LinkedIn** (https://cdn.oreillystatic.com/en/assets/1/event/269/Big%20data%20analytics%20and%20machine%20learning%20techniques%20to%20drive%20and%20grow%20business%20Presentation%201.pdf)
* **Self-Serve Reporting Platform on Hadoop at LinkedIn** (https://cdn.oreillystatic.com/en/assets/1/event/137/Building%20a%20self-serve%20real-time%20reporting%20platform%20at%20LinkedIn%20Presentation%201.pdf) 
* **Privacy-Preserving Analytics and Reporting at LinkedIn** (https://engineering.linkedin.com/blog/2019/04/privacy-preserving-analytics-and-reporting-at-linkedin) 
* **Analytics Platform for Tracking Item Availability at Walmart** (https://medium.com/walmartlabs/how-we-build-a-robust-analytics-platform-using-spark-kafka-and-cassandra-lambda-architecture 
-70c2d1bc8981) 
* **Analytics Platform for Tracking Item Availability at Walmart** (https://medium.com/walmartlabs/how-we-build-a-robust-analytics-platform-using-spark-kafka-and-cassandra-lambda-architecture-70c2d1bc8981) 
* **Real-Time Analytics for Mobile App Crashes using Apache Pinot at Uber** (https://www.uber.com/en-SG/blog/real-time-analytics-for-mobile-app-crashes/) 
* **HALO: Hardware Analytics and Lifecycle Optimization at Facebook** (https://code.fb.com/data-center-engineering/hardware-analytics-and-lifecycle-optimization-halo-at-facebook/) 
* **RBEA: Real-time Analytics Platform at King** (https://techblog.king.com/rbea-scalable-real-time-analytics-king/) 
@@ -754,8 +721,7 @@
* **Maze: Funnel Visualization Platform at Uber** (https://eng.uber.com/maze/) 
* **Metacat: Making Big Data Discoverable and Meaningful at Netflix** (https://medium.com/netflix-techblog/metacat-making-big-data-discoverable-and-meaningful-at-netflix-56fb36a53520) 
* **SpinalTap: Change Data Capture System at Airbnb** (https://medium.com/airbnb-engineering/capturing-data-evolution-in-a-service-oriented-architecture-72f7c643ee6f) 
* **Accelerator: Fast Data Processing Framework at eBay** (https://www.ebayinc.com/stories/blogs/tech/announcing-the-accelerator-processing-1-000-000-000-lines-per-second-on-a-single-computer 
/) 
* **Accelerator: Fast Data Processing Framework at eBay** (https://www.ebayinc.com/stories/blogs/tech/announcing-the-accelerator-processing-1-000-000-000-lines-per-second-on-a-single-computer/) 
* **Omid: Transaction Processing Platform at Yahoo** (https://yahooeng.tumblr.com/post/180867271141/a-new-chapter-for-omid) 
* **TensorFlowOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo** (https://yahooeng.tumblr.com/post/157196488076/open-sourcing-tensorflowonspark-distributed-deep) 
* **CaffeOnSpark: Distributed Deep Learning on Big Data Clusters at Yahoo** (https://yahooeng.tumblr.com/post/139916828451/caffeonspark-open-sourced-for-distributed-deep) 
@@ -765,10 +731,8 @@
* **Smart Product Platform at Zalando** (https://jobs.zalando.com/tech/blog/zalando-smart-product-platform/?gh_src=4n3gxh1) 
* **Log Analysis Platform at LINE** (https://www.slideshare.net/wyukawa/strata2017-sg) 
* **Data Visualisation Platform at Myntra** (https://medium.com/myntra-engineering/universal-dashboarding-platform-udp-data-visualisation-platform-at-myntra-5f2522fcf72d) 
* **Building and Scaling Data Lineage at Netflix** (https://medium.com/netflix-techblog/building-and-scaling-data-lineage-at-netflix-to-improve-data-infrastructure-reliability-and-1a52526a797 
7) 
* **Building a scalable data management system for computer vision tasks at Pinterest** (https://medium.com/@Pinterest_Engineering/building-a-scalable-data-management-system-for-computer-visi 
on-tasks-a6dee8f1c580) 
* **Building and Scaling Data Lineage at Netflix** (https://medium.com/netflix-techblog/building-and-scaling-data-lineage-at-netflix-to-improve-data-infrastructure-reliability-and-1a52526a7977) 
* **Building a scalable data management system for computer vision tasks at Pinterest** (https://medium.com/@Pinterest_Engineering/building-a-scalable-data-management-system-for-computer-vision-tasks-a6dee8f1c580) 
* **Structured Data at Etsy** (https://codeascraft.com/2019/07/31/an-introduction-to-structured-data-at-etsy/) 
* **Scaling a Mature Data Pipeline - Managing Overhead at Airbnb** (https://medium.com/airbnb-engineering/scaling-a-mature-data-pipeline-managing-overhead-f34835cbc866) 
* **Spark Partitioning Strategies at Airbnb** (https://medium.com/airbnb-engineering/on-spark-hive-and-small-files-an-in-depth-look-at-spark-partitioning-strategies-a9a364f908) 
@@ -784,15 +748,13 @@
* **Platform for Serving Recommendations at Etsy** (https://www.etsy.com/sg-en/codeascraft/building-a-platform-for-serving-recommendations-at-etsy) 
* **Infrastructure to Run User Forecasts at Spotify** (https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/) 
* **Aroma: Using ML for Code Recommendation at Facebook** (https://code.fb.com/developer-tools/aroma/) 
* **Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft** (https://eng.lyft.com/introducing-flyte-cloud-native-machine-learning-and-data-processing-platform-fb2bb3046a59 
) 
* **Flyte: Cloud Native Machine Learning and Data Processing Platform at Lyft** (https://eng.lyft.com/introducing-flyte-cloud-native-machine-learning-and-data-processing-platform-fb2bb3046a59) 
* **LyftLearn: ML Model Training Infrastructure built on Kubernetes at Lyft** (https://eng.lyft.com/lyftlearn-ml-model-training-infrastructure-built-on-kubernetes-aef8218842bb) 
* **Horovod: Open Source Distributed Deep Learning Framework for TensorFlow at Uber** (https://eng.uber.com/horovod/) 
* **COTA: Improving Customer Care with NLP & Machine Learning at Uber** (https://eng.uber.com/cota/) 
* **Manifold: Model-Agnostic Visual Debugging Tool for Machine Learning at Uber** (https://eng.uber.com/manifold/)  
* **Repo-Topix: Topic Extraction Framework at Github** (https://githubengineering.com/topics/) 
* **Concourse: Generating Personalized Content Notifications in Near-Real-Time at LinkedIn** (https://engineering.linkedin.com/blog/2018/05/concourse--generating-personalized-content-notifica 
tions-in-near) 
* **Concourse: Generating Personalized Content Notifications in Near-Real-Time at LinkedIn** (https://engineering.linkedin.com/blog/2018/05/concourse--generating-personalized-content-notifications-in-near) 
* **Altus Care: Applying a Chatbot to Platform Engineering at eBay** (https://www.ebayinc.com/stories/blogs/tech/altus-care-apply-chatbot-to-ebay-platform-engineering/) 
* **PyKrylov: Accelerating Machine Learning Research at eBay** (https://tech.ebayinc.com/engineering/pykrylov-accelerating-machine-learning-research-at-ebay/) 
* **Box Graph: Spontaneous Social Network at Box** (https://blog.box.com/blog/box-graph-how-we-built-spontaneous-social-network/) 
@@ -807,12 +769,10 @@
* **Content-based Video Relevance Prediction at Hulu** (https://medium.com/hulu-tech-blog/content-based-video-relevance-prediction-b2c448e14752) 
* **Moderating Inappropriate Video Content at Yelp** (https://engineeringblog.yelp.com/2024/03/moderating-inappropriate-video-content-at-yelp.html) 
* **Improving Photo Selection With Deep Learning at TripAdvisor** (http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/) 
* **Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor** (https://www.tripadvisor.com/engineering/personalized-recommendations-for-experiences-using-deep-learning 
/) 
* **Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor** (https://www.tripadvisor.com/engineering/personalized-recommendations-for-experiences-using-deep-learning/) 
* **Personalised Recommender Systems at BBC** (https://medium.com/bbc-design-engineering/developing-personalised-recommender-systems-at-the-bbc-e26c5e0c4216) 
* **Machine Learning (2 parts) at Condé Nast** (https://technology.condenast.com/story/handbag-brand-and-color-detection) 
* **Natural Language Processing and Content Analysis (2 parts) at Condé Nast** (https://technology.condenast.com/story/natural-language-processing-and-content-analysis-at-conde-nast-part-2-sy 
stem-architecture) 
* **Natural Language Processing and Content Analysis (2 parts) at Condé Nast** (https://technology.condenast.com/story/natural-language-processing-and-content-analysis-at-conde-nast-part-2-system-architecture) 
* **Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio** (https://tech.iheart.com/mapping-the-world-of-music-using-machine-learning-part-2-aa50b6a0304c) 
* **Machine Learning to Improve Streaming Quality at Netflix** (https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) 
* **Machine Learning to Match Drivers & Riders at GO-JEK** (https://blog.gojekengineering.com/how-we-use-machine-learning-to-match-drivers-riders-b06d617b9e5) 
@@ -823,8 +783,7 @@
* **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-recommen 
dations/) 
* **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) 
@@ -856,8 +815,7 @@
* **Personalized Search at Etsy** (https://codeascraft.com/2020/10/29/bringing-personalized-search-to-etsy/) 
* **ML Feature Serving Infrastructure at Lyft** (https://eng.lyft.com/ml-feature-serving-infrastructure-at-lyft-d30bf2d3c32a) 
* **Context-Specific Bidding System at Etsy** (https://codeascraft.com/2021/03/23/how-we-built-a-context-specific-bidding-system-for-etsy-ads/) 
* **Moderating Promotional Spam and Inappropriate Content in Photos at Scale at Yelp** (https://engineeringblog.yelp.com/2021/05/moderating-promotional-spam-and-inappropriate-content-in-photo 
s-at-scale-at-yelp.html) 
* **Moderating Promotional Spam and Inappropriate Content in Photos at Scale at Yelp** (https://engineeringblog.yelp.com/2021/05/moderating-promotional-spam-and-inappropriate-content-in-photos-at-scale-at-yelp.html)
* **Optimizing Payments with Machine Learning at Dropbox** (https://dropbox.tech/machine-learning/optimizing-payments-with-machine-learning) 
* **Scaling Media Machine Learning at Netflix** (https://netflixtechblog.com/scaling-media-machine-learning-at-netflix-f19b400243) 
* **Similarity Engine at eBay** (https://tech.ebayinc.com/engineering/ebays-blazingly-fast-billion-scale-vector-similarity-engine/) 
@@ -873,8 +831,7 @@
⟡ Architecture of API Gateway at Uber (https://eng.uber.com/architecture-api-gateway/)
⟡ Architecture of API Gateway at Tinder (https://medium.com/tinder/how-we-built-the-tinder-api-gateway-831c6ca5ceca)
⟡ Basic Architecture of Slack (https://slack.engineering/how-slack-built-shared-channels-8d42c895b19f)
⟡ Lightweight Distributed Architecture to Handle Thousands of Library Releases at eBay
 (https://tech.ebayinc.com/engineering/a-lightweight-distributed-architecture-to-handle-thousands-of-library-releases-at-ebay/)
⟡ Lightweight Distributed Architecture to Handle Thousands of Library Releases at eBay (https://tech.ebayinc.com/engineering/a-lightweight-distributed-architecture-to-handle-thousands-of-library-releases-at-ebay/)
⟡ Back-end at LinkedIn (https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin)
⟡ Back-end at Flickr (https://yahooeng.tumblr.com/post/157200523046/introducing-tripod-flickrs-backend-refactored)
⟡ Infrastructure (3 parts) at Zendesk (https://medium.com/zendesk-engineering/the-history-of-infrastructure-at-zendesk-part-3-foundation-team-forming-and-evolving-9859e40f5390)
@@ -888,8 +845,7 @@
⟡ Kabootar: Communication Platform at Swiggy (https://bytes.swiggy.com/kabootar-swiggys-communication-platform-e5a43cc25629)
⟡ Simone: Distributed Simulation Service at Netflix (https://medium.com/netflix-techblog/https-medium-com-netflix-techblog-simone-a-distributed-simulation-service-b2c85131ca1b)
⟡ Seagull: Distributed System that Helps Running > 20 Million Tests Per Day at Yelp (https://engineeringblog.yelp.com/2017/04/how-yelp-runs-millions-of-tests-every-day.html)
⟡ PriceAggregator: Intelligent System for Hotel Price Fetching (3 parts) at Agoda
 (https://medium.com/agoda-engineering/priceaggregator-an-intelligent-system-for-hotel-price-fetching-part-3-52acfc705081)
⟡ PriceAggregator: Intelligent System for Hotel Price Fetching (3 parts) at Agoda (https://medium.com/agoda-engineering/priceaggregator-an-intelligent-system-for-hotel-price-fetching-part-3-52acfc705081)
⟡ Phoenix: Testing Platform (3 parts) at Tinder (https://medium.com/tinder-engineering/phoenix-tinders-testing-platform-part-iii-520728b9537)
⟡ Hexagonal Architecture at Netflix (https://netflixtechblog.com/ready-for-changes-with-hexagonal-architecture-b315ec967749)
⟡ Architecture of Sticker Services at LINE (https://www.slideshare.net/linecorp/architecture-sustaining-line-sticker-services)
@@ -916,8 +872,7 @@
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.p 
df) 
* **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/) 
@@ -952,13 +907,11 @@
⟡ 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)
⟡ 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/)
⟡ Using Metrics to Improve the Development Process (and Coach People) at Indeed (https://engineering.indeedblog.com/blog/2018/10/using-metrics-to-improve-the-development-process-and-coach-people/)
⟡ Mistakes to Avoid while Creating an Internal Product at Skyscanner (https://medium.com/@SkyscannerEng/9-mistakes-to-avoid-while-creating-an-internal-product-63d579b00b1a)
⟡ RACI (Responsible, Accountable, Consulted, Informed) at Etsy (https://codeascraft.com/2018/01/04/selecting-a-cloud-provider/)
⟡ Four Pillars of Leading People (Empathy, Inspiration, Trust, Honesty) at Zalando (https://jobs.zalando.com/tech/blog/four-pillars-leadership/)
@@ -993,10 +946,8 @@
⟡ 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/)
⟡ 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/)
@@ -1004,8 +955,7 @@
⟡ 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 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)