Mohamed SAEED HAMMAD’s Post

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

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

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

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

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

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.