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Systems Papershelf

Architectural Papershelf & Reading Notes

Seminal papers, textbooks, and RFCs distilled into actionable mental models for designing real-world distributed architectures. Powered dynamically from the open content repository.

01A Critique of ANSI SQL Isolation Levels
Berenson, Bernstein, Gray, Melton, O'Neil, O'Neil (1995)·9 min read
Databases

Why 'serializable' in the 1992 standard is incomplete — dissects anomalies like Write Skew and clarifies snapshot isolation.

Key Architectural Insights
  • The original 1992 ANSI SQL definitions using phenomenon diagrams failed to capture Snapshot Isolation anomalies.
  • Introduces Write Skew: two transactions concurrently read overlapping state and perform non-overlapping writes that violate global invariants.
  • Snapshot Isolation provides repeatable read without read locks, but requires Serializable Snapshot Isolation (SSI) for true serializability.
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02Optimal Probabilistic Cache Expiration with XFetch
Vattani, Chierichetti, Lowenstein (2015)·8 min read
Caching

TTLs as a probability distribution rather than a hard cutoff — prevents cache stampedes without cold cache recompute storms.

Key Architectural Insights
  • Under heavy read loads, hard TTLs cause thousands of concurrent misses at expiration (thundering herd).
  • XFetch calculates an early recompute probability: e^(-delta * beta * log(rand()) / TTL) > remaining_time.
  • Near expiration, a single worker proactively refreshes the cache in the background while other requests receive warm data.
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03Designing Data-Intensive Applications
Martin Kleppmann (2017)·10 min read
Distributed Systems

Foundational mental models on replication topologies, partition strategies, consensus protocols, and stream processing.

Key Architectural Insights
  • Single-leader vs multi-leader vs leaderless: trade-offs in write scalability, conflict resolution, and consistency.
  • SSTables & LSM-Trees vs B-Trees: sequential write speed vs deterministic read lookups.
  • Linearizability vs Serializability: single-object recency guarantees vs multi-object transaction safety.
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04Model Context Protocol (MCP) Specification
Anthropic & Open Source Community (2024)·7 min read
AI Infrastructure

Standardized open protocol enabling seamless, secure connectivity between LLM agents and external data sources & tools.

Key Architectural Insights
  • Decouples agent clients from specialized tool backends via JSON-RPC 2.0 transport (stdio / SSE).
  • Provides standard primitives for Resources (read-only data), Tools (executable actions), and Prompts (reusable templates).
  • Enables modular agent architectures without bespoke tool glue code.
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