curated-list-design

Online Resources:

1. Gergely Orosz's real world postmortems have great learnings - https://lnkd.in/grywMqKt
2. Neo K.'s System Design Newsletter makes engineering blogs more digestible - https://lnkd.in/gVnPv-Q8
3. Google Senior Staff (L7) Engineer's detailed whitepaper notes - https://lnkd.in/gGWf-Nvy
4. system-design-primer (hollistic resource for system design interviews) - https://lnkd.in/g6yMEsGv
5. ByteByteGo system design newsletter by Alex Xu - https://lnkd.in/gbCDC7XT
6. Architecture Notes - https://lnkd.in/grMHDuuE
7. Quastor System Design Case Studies - https://lnkd.in/g3bbCPHV
8. Level Up Coding's System Design Interview Survival Guide - https://lnkd.in/g8vKAbmD

Engineering Blogs:

1. Figma Engineering: https://lnkd.in/gFbvV8Mk
2. OpenAI Software Engineering: https://lnkd.in/g3wFsZk7
3. Engineering @ Meta: https://lnkd.in/gc9xnZQ8
4. Stripe Engineering: https://lnkd.in/g4JqgY39
5. Nextflix Tech: https://lnkd.in/gq-SWapT
6. Airbnb Tech: https://lnkd.in/gy3RF5ih
7. Uber Engineering: https://lnkd.in/gvga-NEg
8. Dropbox Tech: https://dropbox.tech/
9. Jane Street Tech Blog: https://lnkd.in/gRudhsrn
10. Engineering @ Ramp: https://lnkd.in/gw_kd2Vj
11. Instacart Tech: https://lnkd.in/gdGN9SrY
12. Paypal Tech: https://lnkd.in/gxj9Mx64
13. Rippling Engineering: https://lnkd.in/ge6K-UkG
14. Longer list https://lnkd.in/g3xqDpg6

Youtube Channels:

1. Martin Kleppman's channel - https://lnkd.in/gUJGHWEw
2. CMU Database Group - https://lnkd.in/gzTf2ZMs
3. MIT6.824: Distributed Systems - https://lnkd.in/gtmXKew7
4. DistSys Reading Group - https://lnkd.in/gdX7DQzq
5. TLA+ Video Course - https://lnkd.in/gUYB_FxX

Books:

1. Designing Data Intensive Systems by Martin Kleppman https://lnkd.in/gMhbvW23
2. Specifying Systems by Leslie Lamport - https://lnkd.in/gYzdwwBh
3. System Design Interview by Alex Xu - https://lnkd.in/gzUBcRe3
4. Database Internals by Alex Petrov - https://lnkd.in/gMC9B9UR
5. Building Microservices by Sam Newman - https://lnkd.in/gz5cwpG9

System Design:

1. Grokking System Design Fundamentals: https://lnkd.in/gtcCT-dJ
2. Grokking the System Design Interview: https://lnkd.in/giwyzfkT
3. Grokking Microservice Design Patterns - https://lnkd.in/gDMtPQxi

Tips:

1. For a Read-Heavy System - Consider using a Cache.
2. For a Write-Heavy System - Use Message Queues for async processing
3. For a Low Latency Requirement - Consider using a Cache and CDN.
4. Need 𝐀tomicity, 𝐂onsistency, 𝐈solation, 𝐃urability Compliant DB - Go for RDBMS/SQL Database.
5. Have unstructured data - Go for NoSQL Database.
6. Have Complex Data (Videos, Images, Files) - Go for Blob/Object storage.
7. Complex Pre-computation - Use Message Queue & Cache.
8. High-Volume Data Search - Consider search index, tries or search engine.
9. Scaling SQL Database - Implement Database Sharding.
10. High Availability, Performance, & Throughput - Use a Load Balancer.
11. Global Data Delivery - Consider using a CDN.
12. Graph Data (data with nodes, edges, and relationships) - Utilize Graph Database.
13. Scaling Various Components - Implement Horizontal Scaling.
14. High-Performing Database Queries - Use Database Indexes.
15. Bulk Job Processing - Consider Batch Processing & Message Queues.
16. Server Load Management & Preventing DOS Attacks- Use a Rate Limiter.
17. Microservices Architecture - Use an API Gateway.
18. For Single Point of Failure - Implement Redundancy.
19. For Fault-Tolerance and Durability - Implement Data Replication.
20. For User-to-User fast communication - Use Websockets.
21. Failure Detection in Distributed Systems - Implement a Heartbeat.
22. Data Integrity - Use Checksum Algorithm.
23. Efficient Server Scaling - Implement Consistent Hashing.
24. Decentralized Data Transfer - Consider Gossip Protocol.
25. Location-Based Functionality - Use Quadtree, Geohash, etc.
26. Avoid Specific Technology Names - Use generic terms.
27. High Availability and Consistency Trade-Off - Eventual Consistency.
28. For IP resolution & Domain Name Query - Mention DNS.
29. Handling Large Data in Network Requests - Implement Pagination.
30. Cache Eviction Policy - Preferred is LRU (Least Recently Used) Cache.
31. To handle traffic spikes: Implement Autoscaling to manage resources dynamically
32. Need analytics and audit trails - Consider using data lakes or append-only databases
33. Handling Large-Scale Simultaneous Connections - Use Connection Pooling and consider using Protobuf to minimize data payload

34 𝐇𝐨𝐰 𝐓𝐨 𝐇𝐚𝐯𝐞 𝐋𝐨𝐰 𝐋𝐚𝐭𝐞𝐧𝐜𝐲 𝐢𝐧 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐒𝐲𝐬𝐭𝐞𝐦𝐬?

35 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐔𝐬𝐞𝐝 𝐀𝐜𝐫𝐨𝐬𝐬 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐋𝐚𝐲𝐞𝐫𝐬.

36. To prevent overloading system - Use Token bucket and Leaky bucket algorithm
37. Minimize deployment downtime - Implement blue green deployment to minimize downtime and reduce risk
38. 5 𝐖𝐚𝐲𝐬 𝐭𝐨 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐘𝐨𝐮𝐫 𝐀𝐏𝐈 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞