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System design academy

Skill mahmoud20138/Tradecraft/plugins/tradecraft/skills/system-design-academy

102 Claude Code skills across 7 categories -- trading strategies, Azure, VSCode extensions, AI prompts, and custom automation skills

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npx -y skills add mahmoud20138/Tradecraft --skill system-design-academy

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Real-world system design case studies from 40+ major tech companies + 114 concepts. USE FOR: system design, design Twitter, design YouTube, design Uber, design Netflix, design WhatsApp, design Slack, design Instagram, URL shortener, payment system, distributed systems, scalability, microservices, caching patterns, consistent hashing, rate limiting, system design interview, architecture patterns, database scaling.

SKILL.md

3.1 KB, 567 tokens by cl100k_base, as published. Nobody here has run it

System Design Academy

Case studies from 40+ companies + 114 system design concepts.

Company Case Studies

CompanyTopics
Amazon / AWSS3 architecture, Prime Video microservices, scaling
NetflixMicroservices, chaos engineering
UberETA computation, nearby drivers, payments
WhatsAppMessaging at billions scale
SlackMessaging architecture
StripeRate limiting, idempotent APIs
InstagramInfrastructure scaling to billions
YouTubeScalability, Vitess MySQL
GoogleSearch engine, Docs real-time editing
DiscordPerformance optimization, messaging
FigmaPostgreSQL scaling
ShopifyFlash sales handling
ZoomVideo conferencing
FacebookLive video streaming
TinderSwipe architecture
LinkedInScalability patterns
RedditArchitecture
DropboxFile sync and growth
CanvaReal-time collaboration
Stripe / Razorpay / PayPalPayment gateways
ZapierAutomation platform
BlueskyDecentralized social network
Disney+ Hotstar25M concurrent users, emoji delivery

Core Concepts (114 total)

ConceptKey Points
API GatewayAuth, routing, rate limiting, aggregation
CachingWrite-through, write-behind, cache-aside, eviction
Consistent HashingVirtual nodes, minimal rehashing on scale
Load BalancingRound-robin, least-connections, IP-hash
Rate LimitingToken bucket, sliding window, fixed window
Message QueuesKafka, RabbitMQ, pub/sub patterns
DB ScalingSharding, replication, SQL vs NoSQL trade-offs
CDNEdge caching, origin pull vs push
Bloom FiltersProbabilistic membership, space efficient
Gossip ProtocolDistributed state propagation
Cell ArchitectureBlast radius isolation
Chaos EngineeringNetflix Simian Army approach
Actor ModelConcurrent, message-passing systems
Real-timeWebSocket vs SSE vs long-polling

Back-of-Envelope Numbers

  • 1M req/day = ~12 req/sec
  • 1B req/day = ~12,000 req/sec
  • MySQL write ~1,000 QPS; Redis read ~100,000 QPS
  • Typical read:write ratio = 10:1 to 100:1

7 Interview Failure Patterns

  1. Not clarifying requirements first
  2. Skipping scale estimation
  3. Ignoring failure modes
  4. Not discussing trade-offs
  5. Over-engineering for current scale
  6. Missing data consistency requirements
  7. Forgetting monitoring and observability

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.