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Architecture Navigation

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Core Architecture

DocumentDescriptionFocus Area
🌐 System OverviewHigh-level architecture & design principlesComponents, interactions, data flow
πŸ”„ Request FlowRequest processing pipeline deep diveProcessing stages, memory management
πŸ“Š BenchmarksPerformance benchmarks & optimizationMetrics, scaling, optimization
βš™οΈ ConcurrencyWorker pools & threading modelGoroutines, channels, resource isolation

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πŸ”§ Internal Systems

DocumentDescriptionFocus Area
πŸ”Œ Plugin SystemHow plugins work internallyPlugin lifecycle, interfaces, execution
πŸ› οΈ MCP SystemModel Context Protocol internalsTool discovery, execution, integration
πŸ’‘ Design DecisionsArchitecture rationale & trade-offsWhy we built it this way, alternatives

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Architecture at a Glance

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High-Performance Design Principles

  • πŸ”„ Asynchronous Processing - Channel-based worker pools eliminate blocking
  • πŸ’Ύ Memory Pool Management - Object reuse minimizes garbage collection
  • πŸ—οΈ Provider Isolation - Independent resources prevent cascade failures
  • πŸ”Œ Plugin-First Architecture - Extensible without core modifications
  • ⚑ Connection Optimization - HTTP/2, keep-alive, intelligent pooling

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System Components Overview

Processing Flow: Transport β†’ Router β†’ Plugins β†’ MCP β†’ Workers β†’ Providers

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Key Performance Characteristics

MetricPerformanceDetails
πŸš€ Throughput10,000+ RPSSustained high-load performance
⚑ Latency11-59μs overheadMinimal processing overhead
πŸ’Ύ MemoryOptimized poolingObject reuse minimizes GC pressure
🎯 Reliability100% success rateUnder 5000 RPS sustained load

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Architectural Features

  • πŸ”„ Provider Isolation - Independent worker pools prevent cascade failures
  • πŸ’Ύ Memory Optimization - Channel, message, and response object pooling
  • 🎣 Extensible Hooks - Plugin system for custom logic injection
  • πŸ› οΈ MCP Integration - Native tool discovery and execution system
  • πŸ“Š Built-in Observability - Prometheus metrics without external dependencies

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πŸ“š Core Concepts

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Request Lifecycle

  1. Transport receives request (HTTP/SDK)
  2. Router selects provider and manages load balancing
  3. Plugin Manager executes pre-processing hooks
  4. MCP Manager discovers and prepares available tools
  5. Worker Pool processes request with dedicated provider workers
  6. Memory Pools provide reusable objects for efficiency
  7. Plugin Manager executes post-processing hooks
  8. Transport returns response to client

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Scaling Strategies

  • Vertical Scaling - Increase pool sizes and buffer capacities
  • Horizontal Scaling - Deploy multiple instances with load balancing
  • Provider Scaling - Independent worker pools per provider
  • Memory Scaling - Configurable object pool sizes

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Extension Points

  • Plugin Hooks - Pre/post request processing
  • Custom Providers - Add new AI service integrations
  • MCP Tools - External tool integration
  • Transport Layers - Multiple interface options (HTTP, SDK, gRPC planned)
πŸ’‘ New to Bifrost architecture? Start with System Overview for the complete picture, then dive into Request Flow to understand how it all works together.