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Classic designs 8

Ordered by design number

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2. Design a Distributed Rate Limiter
Enforce tenant quotas across servers while making burst behavior and outage policy explicit.
ClassicMedium
Caching Databases Concurrency
+8
Distributed systems API gateways AWS Lua Rate limiting Redis Reliability Token bucket
Worked design
Practice
3. Design a Distributed Cache
Partition cached data, survive node loss and keep cache misses from overwhelming the source of truth.
ClassicMedium
Caching Sharding Databases
+9
Distributed systems AWS Consistency Consistent hashing Hot keys LRU eviction Memcached Redis Replication
Worked design
Practice
42. Design a Metrics Monitoring Platform
Collect 5 million samples a second from 500,000 hosts, store them as time series, chart them and page people.
ClassicMedium
Databases Streaming Observability
+7
Distributed systems Alerting AWS Cardinality Kafka Prometheus Time series
Worked design
Practice
45. Design a Job Scheduler
Run 10,000 jobs a second within two seconds of their time, at least once, with retries, fairness between tenants and exactly-once effects.
ClassicMedium
Queues Databases AWS
+5
Cron DynamoDB Idempotency Scheduling Amazon SQS
Worked design
Practice
66. Design for Read Scale: A Product Page Read a Million Times a Second
Serve a product page a million times a second: a cheap query, replicas, Redis and the edge, with hot keys, stampedes and invalidation handled.
ClassicMedium
Caching Databases Aurora
+4
AWS CDNs Read replicas Redis
Worked design
Practice
67. Design for Write Scale: A Million Writes a Second
A live TV vote at a million writes a second: spread by key, buffer in Kafka, aggregate the hot counter in two stages, shed what can wait.
ClassicMedium
Sharding Databases Streaming
+6
Distributed systems AWS DynamoDB Flink Kafka Scaling writes
Worked design
Practice
70. Design an In-Memory Data Store like Redis
An in-memory data store like Redis, from one event loop to Redis Cluster to a durable platform.
ClassicMedium
Caching Sharding Databases
+5
Distributed systems AWS In memory Redis Replication
Worked design
Practice
100. Design a Distributed File System
Billions of files, hundreds of petabytes, one strongly consistent tree: a namespace partitioned by directory, chunk servers, replication, repair, erasure coding. One-hour boards for junior, senior and staff, with the theory behind them.
ClassicMedium
Databases Distributed systems AWS
+6
DynamoDB Erasure coding File system Infrastructure Replication Storage
Worked design
Practice

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Classic designs 8

2. Design a Distributed Rate Limiter

3. Design a Distributed Cache

42. Design a Metrics Monitoring Platform

45. Design a Job Scheduler

66. Design for Read Scale: A Product Page Read a Million Times a Second

67. Design for Write Scale: A Million Writes a Second

70. Design an In-Memory Data Store like Redis

100. Design a Distributed File System