Official account of Yiche Technology, regularly sharing the team's technical practices and insights.
The article explains how to design a C++‑based multithreaded service that uses Pthreads, channels, and TensorRT to parallelize deep‑learning inference tasks, thereby reducing latency and dramatically increasing throughput for AI applications such as facial‑recognition access control systems.
This document provides a comprehensive technical overview of Elasticsearch, comparing it with Solr and ClickHouse, detailing common operational pain points and configuration solutions, describing containerized and ECK deployments, and outlining a company‑wide automation platform for cluster provisioning, monitoring, index and security management, with future directions for lifecycle and backup strategies.
The Yiche OCR system combines a DBNet‑based text detector and a CRNN recognizer, enhances performance on natural‑scene texts through data expansion, multi‑branch dictionaries, distribution‑aware weighting, and accelerates training via IPEX and parallel processing on CPU servers.
This article describes Yiche's cloud‑native transformation that unifies virtualization and containerization by evaluating Kata, Virtlet and KubeVirt, selecting KubeVirt, detailing its architecture, storage integration, custom enhancements, deployment challenges, and future work for a hybrid infrastructure.
This article explains how Spring Framework resolves circular dependencies during object creation using a three-level caching mechanism, detailing the process through code examples and architectural diagrams.
This article presents a technical case study of Yiche’s 818 Car Carnival data dashboard, detailing the background, business requirements, TiDB selection and architecture, encountered issues with TiDB, TiCDC and query performance, and the solutions and performance results achieved.
This article provides a comprehensive overview of MyBatis, covering its purpose as a semi‑automatic persistence framework, the reasons for using ORM, how to download and build the source, its core workflow, layered architecture, and detailed configuration parsing with code examples.
