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Cut Network Wait to 3 Minutes
System Architecture
👤 Developers and technical leaders focused on AI application architecture, cross-border network optimization, and cloud deployment
Based on 513,336 real production calls from July 16 to September 8, 2026, this article analyzes the performance bottleneck caused by cross-border transmission of inference traffic in the legacy architecture. The data shows that inference traffic accounted for approximately 98.3% of total traffic, causing nearly 3 hours of network wait time per day. By deploying the inference device in AWS US and connecting it to OpenAI through a low-latency private network, while transmitting only tool parameters and results between AWS and the primary machine in China, cross-border traffic was reduced from 7.94 GB to 0.14 GB, and network wait time was shortened to approximately 3 minutes.
- ✨ In the legacy architecture, inference requests and responses averaged approximately 794 KB per call, accounting for 98.3% of total traffic.
- ✨ Approximately 7.94 GB of inference traffic crossed borders each day, causing nearly 3 hours of network wait time.
- ✨ The inference device was deployed in AWS US and connected to OpenAI through a private network.
- ✨ The primary machine in China only executes tools and transmits lightweight control data, reducing cross-border traffic to 0.14 GB.
- ✨ Daily network wait time fell from approximately 3 hours to approximately 3 minutes, a reduction of about 98.3%.
📅 2026-09-08 · 993 words · ~5 min read
To-Do List: System Openness, AI Assetization, User and Payment Systems
System Architecture
👤 Technical developers, system architects, business decision-makers, and professionals interested in AI assetization and user system optimization
This article documents the author's work reflections on February 4, 2026, focusing on four core topics. First, it discusses the importance of open system permissions, proposing asymmetric permission design to control data access, supporting Yuan's development as a data source and ordering platform. Second, it analyzes AI assetization capabilities, noting that API assetization is an initial form, with BYOK potentially becoming a trend in the future, though intermediaries still hold value in business assembly. Third, it explores user system enhancement, suggesting the implementation of Supabase's PassKey login via Edge Function to improve user experience. Finally, it briefly mentions the need for payment system construction, emphasizing integration with payment platforms to address compliance issues in revenue collection. The article aims to provide practical references for technical developers and business decision-makers.
- ✨ System permissions require asymmetric design to control data access and support open platform development
- ✨ AI assetization achieves profits through API management, but BYOK may become a trend in the future
- ✨ User systems can be enhanced via Edge Function to support PassKey login and improve experience
- ✨ Payment systems need integration with platforms to resolve compliance issues in revenue collection
- ✨ Technical design should balance security and user experience to drive business innovation
📅 2026-02-04 · 878 words · ~4 min read