Performance Details
GPT-Load adopts a "proxy path first" high-performance design philosophy, where all optimizations ensure ultimate performance and stability of core proxy requests.
Core Performance Features
Zero I/O Operations
Full in-memory proxy request processing
Zero-Copy Streaming
Direct streaming data forwarding
Lock-Free Concurrency
Efficient atomic operation processing
Ultra-Low Resource Usage
Single core 128MB memory operation
Ultimate Proxy Request Performance
To achieve minimum latency and maximum concurrency, the core path of proxy requests is designed as "zero I/O operations".
Full In-Memory Service
All data required for routing and decision-making, including group configurations and key information, are preloaded into memory during service startup and configuration changes. No database or disk access is needed during proxy requests.
Zero-Copy Streaming
Real-time Transparent Transmission Mechanism
GPT-Load adopts real-time transparent transmission mode, directly connecting upstream service data streams to client responses without any intermediate buffering, line-by-line reading, or content parsing.
Difference from Traditional Streaming Processing
❌ Traditional Approach
Line reading → Parse processing → Buffer output
✅ GPT-Load Approach
Upstream data stream → Direct transmission → Client
Core Advantages
Won't damage original data packet structure due to line-by-line reading
Naturally supports all data formats including SSE, JSON streams, binary, etc.
Theoretically can handle upstream response data of any size
Data forwarded immediately upon arrival, no buffer waiting time
No data caching, memory usage independent of response size
Response speed infinitely close to upstream service native performance
Asynchronous Logging
Request logging uses delayed asynchronous write strategy, completely decoupled from request-response lifecycle, ensuring logging operations don't interfere with real-time proxy performance.
Dynamic Resource & Concurrency Management
Efficient HTTP Client Reuse
Maintain independent HTTP client instances with reusable underlying connections for each group
When group configurations (like timeouts) change, system dynamically generates new client instances in real-time to ensure immediate configuration effectiveness
Atomic Operations & Lock-Free Design
In high-frequency concurrent operations like key polling counting, use sync/atomic package for lock-free programming, avoiding performance overhead from mutex locks.
Asynchronous Tasks & Scalability
Asynchronous Management of Massive Keys
Mechanism
Operations like adding and validating keys are all executed as asynchronous background tasks.
Advantage
Management operations don't block service, theoretically allowing system to manage millions of keys.
Cluster Support & Configuration Synchronization
Architecture
Supports multi-node Master-Slave architecture for horizontal scaling.
Synchronization
Master node configuration changes pushed via Redis Pub/Sub notifications
Slave nodes listen and pull updates through built-in configuration synchronizer, achieving eventual consistency across cluster configurations
Lightweight & Resource Efficiency
Ultra-Low Resource Usage
Thanks to Go language's efficient memory management and the above performance optimizations (like zero-copy, connection pool reuse), GPT-Load runs as a compiled binary with no additional runtime dependencies, achieving ultra-low resource usage.
Wide Applicability
In typical single-machine deployment scenarios, only low CPU and memory are needed to ensure smooth service operation.