Productivity
System Design
- Google File System (GFS): https://lnkd.in/gTJQtVHw
- Google Chubby Locking Service: https://lnkd.in/gHAT7cBR
- Meta XFaaS: Hyperscale and Low-cost serverless functions: https://lnkd.in/eHqbPXpH
- Facebook Cassandra (Distributed NoSQL DB): https://lnkd.in/eD9erCNu
- Facebook Memcache (KV store): https://lnkd.in/eYZM5SPb
- LinkedIn Kafka (PubSub): https://lnkd.in/eGcagdRA
- Amazon DynamoDB: https://lnkd.in/eQxJXgMs
- Dapper Tracing System: https://lnkd.in/dm36-6jn
- Borg Cluster Management: https://lnkd.in/gHzNDwQP
- Zanzibar Authentication System: https://lnkd.in/d5Vf7sRD
- Pregel Graph Processing: https://lnkd.in/daq4576Y
- Napa – Data Warehousing: https://lnkd.in/dbEfsa5B
- Napa – Partitioning Algorithm: https://lnkd.in/dkhA7efJ
- BigTable NoSQL Document Store: https://lnkd.in/drmvvSAK
- Monarch Time Series DB: https://lnkd.in/d3kH_NCp
- Scalability at what COST: https://lnkd.in/dJ9ScYKq
- TikTok Monolith – Embedding in real-time: https://lnkd.in/dcjBXCnc
- Apache Kafka – Event Bus: https://lnkd.in/dyxuKbMb
- Meta ServiceRouter – Service Mesh: https://lnkd.in/dVnkv_bV
- Spanner – CAP Theorem Considerations: https://lnkd.in/dq29BAWQ
- Apache Thrift – Definition Language: https://lnkd.in/d7NzhP54
- Cassandra – NoSQL DB: https://lnkd.in/d-_nhtED
- Meta Twine – Cluster Management System: https://lnkd.in/d5t7VFKE
- Colossus Next Gen File Store: https://lnkd.in/dERKhwMf
- TAO Graph Database: https://lnkd.in/daasJpYf
- Hive – Map Reduce Jobs: https://lnkd.in/dpV8BM2R
- Facebook Prophet – Forecasting at Scale: https://lnkd.in/daCmAjak
- Amazon Aurora DB Architecture: https://lnkd.in/dcevpwFt
- Apache Hadoop – Distributed File System: https://lnkd.in/dHsQu9FN
- Millisampler Network Sampling: https://lnkd.in/dsj9FuD6
- Gorilla – Time Series DB: https://lnkd.in/d3AeN2kB
- Google F1 – Fast Analytics: https://lnkd.in/dbZqEKuf
- FlexiRaft – Distributed Consensus Tradeoffs: https://lnkd.in/dX3nMvmt
- Mesa – Data Warehousing: https://lnkd.in/dFJ_Jrz6
- MineSweeper – Root Cause Analysis: https://lnkd.in/dEsd6iwj
- HALP – YouTube Content Delivery Network: https://lnkd.in/dHzJtUc7
- Facebook Prophet – Forecasting at Scale: https://lnkd.in/daCmAjak
- Dynamo DB NoSQL Database: https://lnkd.in/dMD8C_WK
- TensorFlow – Machine Learning at Scale: https://lnkd.in/d-4NfV2Z
- Apple Foundation DB – NewSQL database: https://lnkd.in/dG75i_9K
- Google Firestore: https://lnkd.in/drtEN9qR
- Netflix: Extracting Image Metadata at Scale: https://lnkd.in/eHuVCMca
- Enhancing Netflix Reliability with Service-Level Prioritized Load Shedding: https://lnkd.in/gy3Cz9e5
- Stripe: Designing robust and predictable APIs with idempotency: https://lnkd.in/g7rZvb7t
- How Uber Optimized Cassandra Operations At Scale: https://lnkd.in/e4SjNSXh
- Stripe: Scaling your API with Rate Limiters: https://lnkd.in/eF9KS7RF
- Horizontally scaling the Rails backend of Shopify with Vitess https://lnkd.in/eq_cmQPH
- High-Quality Video Encoding at Scale at Netflix: https://lnkd.in/ekPyMu7b
- How Uber Track Billions of Completed Trips: https://lnkd.in/e4YeJbzs
- OpenAI: Scaling Kubernetes to 7,500 Nodes: https://lnkd.in/eBAPpkvs
- Scaling Knowledge Access and Retrieval at Airbnb: https://lnkd.in/eTSRA4T3
- Finding Kafka’s throughput limit in Dropbox infrastructure: https://lnkd.in/e6p6XWjJ
- How Figma scaled their databases by 100x: https://lnkd.in/eNZG2YSA
- How Quora scaled MySQL to 100k+ queries per second: https://lnkd.in/eagmmMtj
- How LinkedIn serves 5M+ user profiles per second: https://lnkd.in/ep-KUeQ9
- MySQL Replication: https://lnkd.in/edtXWB7M
- Netflix DBLog: Change Data Capture Framework: https://lnkd.in/e53hBDZM
- The Log: Real-Time Data’s Unifying Abstraction (LinkedIn): https://lnkd.in/eCmKbr5S
- Scaling Memcache at Facebook https://lnkd.in/eyDFsaxb
- Uber AresDB: https://lnkd.in/eGgVuZ_s
- Gorilla: Facebook’s Time Series DB: https://lnkd.in/g4Dw5dbb
- Elasticsearch: Time-Based Index Management: https://lnkd.in/eMTXTAYD