摘要
服务监控、故障溯源和服务日志的统计分析,是数字城市地理信息公共服务平台和智慧城市时空信息云平台的重要能力,能够为平台的稳定运行提供可靠保障。本文分析了现有地理信息服务监控方案的局限性,引入了ELK日志框架和Kafka Streams流计算框架,并对地理信息服务特性进行优化,设计和实现了一种分布式地理信息服务监控框架。多地的应用实践表明,该框架实现了海量服务日志数据的采集、处理、存储和多维度快速检索,解决了传统集中式日志数据库写入性能差、扩展困难、查询统计效率低和商业GIS软件服务兼容性差等问题,满足了GIS平台的统一运维、统计分析和监管需要。
Service monitoring,fault tracking,and the statistical analysis of service logs are important capabilities of the digital city geographic information public service platform and the smart city spatio-temporal information cloud platform,which can provide reliable guarantees for the stable operation of the platform.This paper analyzes the limitations of existing geographic information service monitoring solutions,introduces the ELK log framework and Kafka Streams stream computing framework,and optimizes the framework according to the characteristics of geographic information services,and designs a distributed geographic information service monitoring framework.The application practice shows that the framework realizes the collection,processing,storage,and multi-dimensional fast retrieval of massive service log data,and solves problems in traditional centralized log databases,such as the poor writing performance,expansion difficulties,low query statistics efficiency,and poor compatibility with commercial GIS software services.It meets the requirements of unified operation and maintenance,statistical analysis,and supervision of the GIS platform.
作者
刘柄宏
张剑
朱向晖
翁宝凤
徐晓新
LIU Binghong;ZHANG Jian;ZHU Xianghui;WENG Baofeng;XU Xiaoxin(Zhejiang Acadamy of Surveying and Mapping,Hangzhou 311100,China;Longquan Natural Resources and Planning Bureau,Longquan 323700,China;Kecheng Branch of Quzhou Land and Space Planning and Design Institute,Quzhou 324000,China)
出处
《测绘与空间地理信息》
2021年第9期98-101,共4页
Geomatics & Spatial Information Technology
