𝐈𝐭 𝐭𝐨𝐨𝐤 𝐬𝐨𝐦𝐞𝐨𝐧𝐞'𝐬 7 𝐲𝐞𝐚𝐫𝐬 𝐚𝐧𝐝 𝐬𝐞𝐯𝐞𝐫𝐚𝐥 𝐟𝐚𝐢𝐥𝐮𝐫𝐞𝐬 𝐭𝐨 𝐠𝐞𝐭 𝐭𝐡𝐞𝐬𝐞 30 𝐬𝐲𝐬𝐭𝐞𝐦 𝐝𝐞𝐬𝐢𝐠𝐧 𝐜𝐨𝐧𝐜𝐞𝐩𝐭𝐬 𝘠𝘰𝘶 𝘤𝘢𝘯 𝘨𝘦𝘵 𝘵𝘩𝘦𝘮 𝘪𝘯 7 𝘴𝘦𝘤𝘰𝘯𝘥𝘴 𝘣𝘺 𝘴𝘢𝘷𝘪𝘯𝘨 𝘵𝘩𝘪𝘴 𝘱𝘰𝘴𝘵. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication Credit: Sumit L. P.S.: Repost♻️ to help your network and someone who may need it
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Perfect checklist #systemdesign #infrastructure #architecture #software #security #devops #design #compliance #scalability #latency #eventdriven #microservices #api #iaac
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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Great concepts and most of them can be applied in Embedded Software as well
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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Few good design concepts to follow, although (1) autoscaling would be slow to handle sporadic traffic spikes, need a faster response design. Let me know about your thoughts on other design concepts in the comments 🤓 🤓
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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These principles cover various aspects, from scalability to fault tolerance and flexibility.
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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Will surely look at these and add to the list!
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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SWE @ Google | Ex- Amazon, Oracle | I talk about engineering leadership and software engineering | Follow me to become a better software engineer
It took me 10 years and several failures to get these 30 system design concepts You can get them in the next 10 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication
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🚀💡 Sharing Wisdom: 30 Key System Design Concepts 💡🚀 I recently stumbled upon an incredibly valuable post that encapsulated years of experience into 30 essential system design concepts. From autoscaling to handle traffic spikes, to the nuances of data partitioning, sharding, and the importance of designing for scalability from the get-go, these insights are gold for anyone in tech, especially those navigating the complexities of system architecture. What makes this list stand out is not just the breadth of topics covered but the depth of understanding it promotes—lessons learned over 7 years, distilled into a quick read. Happy Reading Folks !!!
It took me 7 years and several failures to get these 30 system design concepts You can get them in 7 seconds by saving this post. 1. Use autoscaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement rate Limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost♻️ to help your network and someone who may need it
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Building Next-Gen developers for Current-Gen Startups | Founder @ Kivio | I train and deploy day one ready developers for businesses | Entrepreneur & Educator
It took me 8 years and several failures to get these 30 system design concepts. You can get them in 10 seconds by reading this post. 1. use autoscaling to handle traffic spikes 2. design for scalability from the beginning 3. plan and implement fault tolerance 4. prioritize horizontal scaling for growth 5. implement data partitioning and sharding 6. use data lakes for analytics and reports 7. employ CDNs to reduce global latency 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. use blob/object storage for media files 11. accept tradeoffs; perfection is unattainable 12. implement data replication and redundancy 13. use rate limiting to protect the system 14. utilize read-through cache for read-heavy applications 15. use write-through cache for write-heavy applications 16. choose NoSQL databases for unstructured data 17. use heartbeat mechanisms to detect failures 18. adopt WebSockets for real-time communication 19. employ database sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for adaptability; expect evolving requirements 23. use database indexing for efficient data retrieval 24. thoroughly understand requirements before designing 25. utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy workloads 27. avoid over-engineering; add features only as needed 28. prefer SQL databases for structured data and transactions 29. use load balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication P.S.: Repost ♻️ to help your network and someone who may need it
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"design for scalability from the start" is a pretty good statement. Even if the project is not going to have +100k users, building for scalability is something necessary when developing any application. You dont need to have components that will help you to scale from 0 to +100k users right away, instead, scale thinking about having +100 users or whateaver the project requirements ask, but the application needs to be scalable for sure.
Engineering Leader @ Amazon || Ex-JP Morgan || Keynote Speaker || Love to write for leaders and technologists
Funny thing about system design? The more I learn, the more I realize how much I don’t know. Sharing my 30 notes to keep on system design interviews, I learnt over the years. 1. Use auto-scaling for traffic spikes 2. design for scalability from the start 3. plan for and implement fault tolerance 4. prioritize horizontal scaling for scalability 5. implement data partitioning and sharding 6. use data lakes for analytics and reporting 7. employ CDNs for global latency reduction 8. make operations idempotent for simplicity 9. use event-driven architecture for flexibility 10. employ blob/object storage for media files 11. embrace tradeoffs; perfection is unattainable 12. implement Data Replication and Redundancy 13. Implement Rate limiting for system protection 14. use a read-through cache for read-heavy apps 15. utilize write-through cache for write-heavy apps 16. opt for NoSQL Databases for unstructured data 17. use Heartbeat Mechanisms for failure detection 18. adopt WebSockets for real-time communication 19. employ Database Sharding for horizontal scaling 20. clearly define system use cases and constraints 21. consider microservices for flexibility and scalability 22. design for flexibility; expect requirements to evolve 23. utilize Database Indexing for efficient data retrieval 24. understand requirements thoroughly before designing 25. Utilize asynchronous processing for background tasks 26. consider denormalizing databases for read-heavy tasks 27. avoid over-engineering; add functionality only as needed 28. prefer SQL Databases for structured data and transactions 29. use Load Balancers for high availability and traffic distribution 30. consider message queues for asynchronous communication Add one thing to this list you think is useful to remember and repost ♻️ for others.
