Official Ctrip Technology account, sharing and discussing growth.
This article details Ctrip's end‑to‑end weak‑network identification model, covering background, metric selection, data collection on iOS and Android, processing pipelines with dynamic weighting, weighted median calculations, success‑rate trends, threshold tuning, and deployment results across multiple platforms.
This article details Ctrip's data middle‑platform solution for international ticketing, covering background challenges, design principles, key technical practices such as version control, P2P distribution, data timeliness, robustness, consumption‑process optimization, overall architecture, achieved benefits, and future plans.
This article presents the SCNN model for multivariate time series forecasting, explains its decomposition into long‑term, seasonal, short‑term, and co‑evolving components, details the neural‑network‑based fusion and loss design, provides Python code snippets, and demonstrates its practical deployment for business volume prediction at Ctrip.
This article details the design and deployment of an intelligent alert attribution system for Ctrip Hotel's front‑end, describing the background challenges, the unified data pool, weighted alert rules, three attribution algorithms, achieved improvements in accuracy and troubleshooting speed, and future enhancement plans.
The article outlines Ctrip Hotel's transition from a monolithic BFF model to a multi‑endpoint "one‑code‑many‑ends" architecture using NestJS, introduces a cloud‑function platform for improved performance and operational efficiency, and describes a dynamic gateway layer that further enhances front‑end flexibility across multiple client types.
This article details the three‑stage evolution of Ctrip's vacation product log system—from a simple single‑table DB approach, through a platform‑based ES + HBase solution, to a scalable V3.0 architecture that improves storage, search, and business empowerment while handling billions of log entries.
TaskHub is a front‑end automation platform that separates core and auxiliary modules to improve task scheduling, logging, and debugging, featuring a decoupled engine, RPC BFF architecture, and real‑world use cases that demonstrate faster issue resolution, task termination, and overall development efficiency.
This article details the architecture, component design, DAG execution engine, optimization techniques, and real‑world performance gains of Ctrip's Eagle algorithm strategy platform, illustrating how modular, visualized, and automated workflow management improves development efficiency, stability, and resource utilization for large‑scale recommendation services.
The article presents a comprehensive case study of Ctrip's full‑chain desktop operations system, detailing its architecture, cross‑platform Rust/Tauri agents, SpringBoot server, security measures, operational challenges, performance optimizations, and the measurable improvements in fault detection and repair across a massive corporate PC fleet.
This article details the deployment of QUIC in Trip.com’s mobile app, covering multi‑process architecture, containerized upgrades, service discovery, health monitoring, push‑pull resilience, full‑link tracing, congestion‑control algorithm redesign, and the resulting performance and reliability improvements achieved across global users.
