scribe-scaling 0.2.0

High-performance scaling optimizations for large repositories
Documentation

Scribe Scaling

Advanced scaling optimizations for handling large repositories (10k-100k+ files) efficiently. This crate implements progressive loading, intelligent caching, parallel processing, and adaptive threshold management for optimal performance at scale.

Core Features

  • Progressive Loading: Metadata-first streaming architecture that avoids loading all files into memory
  • Intelligent Caching: Persistent caching with signature-based invalidation
  • Parallel Processing: Async/parallel pipeline with backpressure management
  • Dynamic Thresholds: Repository-aware adaptive configuration
  • Advanced Signatures: Multi-level signature extraction with budget pressure adaptation
  • Repository Profiling: Automatic detection of repo type and optimal configuration

Performance Targets

  • Small repos (≤1k files): <1s selection, <50MB memory
  • Medium repos (1k-10k files): <5s selection, <200MB memory
  • Large repos (10k-100k files): <15s selection, <1GB memory
  • Enterprise repos (100k+ files): <30s selection, <2GB memory

Architecture

The scaling system is built around a streaming, metadata-first approach:

Repository Discovery → Metadata Stream → Filtered Stream → Analysis Pipeline → Selection
      ↓                     ↓                ↓                   ↓             ↓
  Fast scanning      Lightweight load    Smart filtering   Parallel work   Optimized result