Phase 7 · architecture in context System design walkthroughs. Move from individual concepts to complete systems. Each walkthrough starts with the request path, makes the important trade-offs explicit, and stress-tests the design with failures.
How to use these State the invariant first. Trace one request. Then challenge every dependency with latency, duplication, overload, and partial failure. 01 10B redirects/day · read-heavy
URL Shortener Resolve compact links with low latency while creating globally unique aliases.
Consistent hashing Replication Failure and retries Open walkthrough → 02 Millions of decisions/second
Distributed Rate Limiter Enforce fair request budgets across many stateless service instances.
Consistent hashing Load shedding Replication Open walkthrough → 03 Sub-millisecond reads · high churn
Distributed Cache Serve hot data quickly while controlling staleness, skew, and stampedes.
Consistent hashing Backpressure Failure and retries Open walkthrough → 04 Billions of notifications/day
Notification Platform Deliver user notifications across channels with preferences, retries, and auditability.
Delivery semantics Backpressure Idempotent workflows Open walkthrough → 05 Hundreds of millions of concurrent users
Chat System Preserve conversation order and deliver messages across connected and offline devices.
Distributed logs Delivery semantics Replication Open walkthrough → 06 High-throughput asynchronous work
Distributed Queue Buffer work durably while coordinating ownership, retries, and poison messages.
Distributed logs Delivery semantics Backpressure Open walkthrough → 07 Exabytes · eleven-nines durability target
Object Storage Store enormous immutable blobs durably with metadata, multipart upload, and repair.
Replication Quorums Geo replication Open walkthrough → 08 Tens of milliseconds · read-heavy
Search Autocomplete Return useful ranked suggestions within a keystroke-scale latency budget.
LSM trees Load shedding Replication Open walkthrough → 09 Millions of samples/second
Metrics Platform Ingest, aggregate, retain, and query high-cardinality time-series data.
Distributed logs LSM trees Load shedding Open walkthrough → 10 Elastic data and transaction throughput
Distributed Database Provide a coherent data model across partitions, replicas, transactions, and failures.
Quorums Replication LSM trees Open walkthrough → 11 Gigabytes/second · long retention
Kafka-like Event Platform Retain ordered event streams for independent consumers and replayable processing.
Distributed logs Delivery semantics Backpressure Open walkthrough → 12 Multi-region · low-latency reads and writes
Global Key-Value Store Serve keys near users while balancing consistency, conflicts, and regional failure.
Consistent hashing Geo replication Conflict resolution Open walkthrough →