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NETSCOUT > 实例探究 > 全美航空使用 NetScout 解决方案优化并确保其在线预订系统的性能
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US Airways Uses NetScout Solutions to Optimize and Ensure the Performance of its Online Reservation System

技术
  • 应用基础设施与中间件 - 数据交换与集成
  • 平台即服务 (PaaS) - 连接平台
适用功能
  • 商业运营
  • 销售与市场营销
用例
  • 预测性维护
  • 实时定位系统 (RTLS)
服务
  • 数据科学服务
  • 系统集成
挑战
全美航空需要优化并确保其为客户提供的在线预订和信息服务的性能。为了更严格地管理这一关键业务资产的性能,全美航空的 IT 部门意识到需要全面了解支持其网站的应用程序和网络。该航空公司现有的基于 SNMP 的报告工具无法提供支持公司网站的网络和应用程序的详细、全面的视图。当该公司从外包商那里获得预订网站的管理权时,该公司首先向 NetScout 寻求帮助。
关于客户
全美航空与美国西部航空合并后,成为美国第五大国内航空公司,拥有 35,000 多名航空专业人员,每天运营 3,800 多个航班,飞往 28 个国家的 234 个目的地,包括美国、加拿大、欧洲、加勒比地区和拉丁美洲。全美航空的企业网站每天处理超过 114 万次点击,客户通过这些网站查看航班时刻表、进行预订和提前办理登机手续,每天的交易收入超过 700 万美元。网站停机的成本非常高。
解决方案
nGeniusONE 服务保障平台让全美航空能够全面了解其网站和整个公司的所有交易和应用程序。通过在战略位置(DMZ、内部基础设施内以及一些大型设施)部署 NetScout 智能数据源,全美航空现在能够看到哪些类型的流量正在通过其 LAN、WAN 和 Internet 链路传播。部署 nGenius 解决方案是为了使网络运营组能够深入了解网络和应用程序流。他们之前基于 SNMP 的工具只能让他们看到正在发生的事情的大致情况,但无法确定谁在做什么。
运营影响
  • Since the introduction of the nGenius solution, the airline has become more responsive to its customers, suffering fewer dropped connections and Web site slow downs.
  • US Airways also uses the nGenius solution to assist other IT groups by providing them with tailored reports on application usage and bandwidth consumption, helping the many stakeholders of the IT group validate architectural, device and application performance.
  • The network team works especially closely with the security team. Like most organizations, US Airways is concerned about security issues, the greatest of which are possible virus and other hacker attacks that could disrupt the network. Fortunately, security isn’t a huge problem for the airline since they supplement their security tools by relying on the nGenius solution to report attacks on the network.
数量效益
  • Web site downtime is very costly. The airline chose the nGeniusONE™ Service Assurance platform from NetScout for its ability to provide detailed, comprehensive views of the networks and applications supporting its corporate Web site.
  • The network team appreciates being able to show colleagues the details – network and application response times, top applications, top conversations, etc. – for the particular timeframe in question, as well as the entire 31-day historical timeframe so both groups can immediately see who’s utilizing what resources and where the source of the problem is.

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