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# What is system design |
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# How to approach system design |
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# Who is this guide for |
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# Introduction |
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# Performance vs scalability |
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# Latency vs throughput |
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# Cap theorem |
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# Availability vs consistency |
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# Weak consistency |
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# Eventual consistency |
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# Strong consistency |
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# Consistency patterns |
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# Fail over |
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# Replication |
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# Availability in numbers |
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# Availability patterns |
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# Event driven |
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# Schedule driven |
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# Returning results |
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# Background jobs |
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# Domain name system |
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# Push cdns |
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# Pull cdns |
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# Content delivery networks |
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# Horizontal scaling |
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# Layer 4 load balancing |
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# Layer 7 load balancing |
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# Load balancing algorithms |
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# Lb vs reverse proxy |
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# Load balancers |
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# Microservices |
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# Service discovery |
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# Application layer |
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# Replication |
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# Sharding |
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# Federation |
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# Denormalization |
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# Sql tuning |
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# Rdbms |
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# Key value store |
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# Document store |
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# Wide column store |
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# Graph databases |
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# Nosql |
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# Sql vs nosql |
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# Databases |
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# Client caching |
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# Cdn caching |
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# Web server caching |
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# Database caching |
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# Application caching |
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# Cache aside |
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# Write through |
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# Write behind |
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# Refresh ahead |
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# Caching strategies |
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# Caching |
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# Message queues |
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# Task queues |
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# Back pressure |
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# Asynchronism |
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# Idempotent operations |
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# Http |
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# Tcp |
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# Udp |
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# Rpc |
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# Rest |
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# Grpc |
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# Graphql |
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# Communication |
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# Busy database |
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# Busy frontend |
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# Chatty io |
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# Extraneous fetching |
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# Improper instantiation |
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# Monolithic persistence |
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# No caching |
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# Noisy neighbor |
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# Retry storm |
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# Synchronous io |
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# Performance antipatterns |
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# Health monitoring |
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# Availability monitoring |
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# Performance monitoring |
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# Security monitoring |
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# Usage monitoring |
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# Instrumentation |
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# Visualization and alerts |
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# Monitoring |
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# Asynchronous request reply |
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# Claim check |
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# Choreography |
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# Competing consumers |
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# Pipes and filters |
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# Priority queue |
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# Publisher subscriber |
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# Queue based load leveling |
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# Scheduling agent supervisor |
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# Sequential convoy |
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