Datadog 助力法国国家铁路公司加快数字化转型步伐
公司规模
Large Corporate
地区
- Europe
国家
- France
产品
- Datadog Infrastructure Monitoring
- Datadog Log Management
- Datadog APM products
技术栈
- Azure Kubernetes Service (AKS)
- Apache
- JBoss
- Tomcat
- Wildfly
- Oracle
- SQL Server
- PostgreSQL
- Python
- JavaScript
实施规模
- Enterprise-wide Deployment
影响指标
- Digital Expertise
- Productivity Improvements
技术
- 分析与建模 - 实时分析
- 平台即服务 (PaaS) - 连接平台
适用行业
- 铁路与地铁
适用功能
- 离散制造
- 物流运输
用例
- 预测性维护
- 实时定位系统 (RTLS)
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
SNCF 是法国国有铁路运营商，也是全球公共交通服务提供商。该公司在 120 个国家/地区拥有 275,000 名员工，还提供工程和物流专业知识，以协助全球许多公共交通项目。SNCF 长期以来一直被公认为交通运输领域的全球领导者，于 1981 年推出了世界上第一条高速铁路之一——Train à Grande Vitesse (TGV)。自推出这项开创性的公共资源以来，SNCF 实力不断增强。该公司已将业务扩展到法国以外，目前正在全球舞台上取得成功，它提供工程和物流专业知识，以协助全球公共交通项目。SNCF 现在除了是一家公共交通提供商之外，还是一家蓬勃发展的软件公司，它构建了无数内部和面向公众的应用程序来支持其运营、产品和服务。
挑战
法国国有铁路运营商 SNCF 于 2016 年启动了一项重大的数字化转型计划。该计划的目标是通过将 90% 的应用程序迁移到云中并采用 PaaS 和容器化来更新其 IT 基础设施并提高竞争力。然而，SNCF 发现它没有协调一致的监控方法。业务部门一直在独立采用监控解决方案，导致公司总共使用 11 种不同的监控工具。缺乏单一的标准监控工具严重限制了每个团队的监控范围，使得不同的 IT 团队难以就共同的问题进行合作。这显然阻碍了该组织提高竞争力和敏捷性的目标。此外，SNCF 现有的监控工具不是云原生的，导致用户摩擦和额外的管理开销。
解决方案
为了通过数字化转型提高竞争力，SNCF 认为，对于其团队来说，统一采用单一的集中式监控解决方案至关重要。在使用 Datadog 的基础设施监控、日志管理和 APM 产品进行试点项目并取得巨大成功后，SNCF 决定在全公司范围内全面部署 Datadog。在八个月内，SNCF 将 4,800 台服务器（包括 2,000 台生产服务器）、655 个应用程序和 13,000 个容器从旧监控工具迁移到 Datadog。SNCF 团队现在以多种方式使用 Datadog，例如用于警报、故障排除、查看应用程序日志和性能指标以及检查与云提供商的账单。
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Building Smart IoT-Connected Railways
• Difficult environment. Communications equipment on trains must function properly in harsh conditions, such as environment temperatures ranging from -25°C to +85°C, according to the EU standard EN50155.• Railway regulations. All products in a train must adhere to strict standards, relating to working vibration, power consumption, and lifetime.• Lengthy process. Time to market in the railway industry can take years from concept to mass production, so product design requires a solid long term vision.
Case Study
Connected Transportation: A Smarter Brain for Your Train with Intel
A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.
Case Study
Using LonWorks to Keep Acela Trains Zip Along
Canadian transportation company, Bombardier was tasked with building a bullet train system on rails that were designed for lower speed trains. In addition, they had to ensure safe and optimal operation at high speeds, maximize train uptime and enhance communication with passengers.
Case Study
Delhi NCR Metro: A Mobile App Revolutionizing Public Transportation
The Delhi NCR Metro, a major public transportation system in India, was facing a challenge in providing accurate and comprehensive information to its daily commuters and tourists. The lack of a centralized platform for information about metro station details, train schedules, fare details, parking, elevators, and tourist locations was causing inconvenience to the users. The challenge was to develop a mobile app that could provide all this information accurately and conveniently. The app needed to be equipped with GPS services to help users find the nearest metro and renowned locations. An interactive map was also required to assist travelers who were familiar with the metro lines. The goal was to provide maximum information with minimum input.
Case Study
Automated Railcar Inspections Increase Security and Revenue
Providing industry and government customers with intelligent inspection, automation, safety, and security solutions, Duos Technologies Group, Inc. (“Duos” or the “Company” - Nasdaq: DUOT) continually pushes the boundaries of IT. To keep pace with expanding AI-enabled data capture analytics for its edge railcar inspections, the company chose the latest Dell EMC PowerEdge servers.Duos Technologies’ challenge was finding a way to leverage technology as a force multiplier to meet customer requirements for a better, faster inspection process for trains running at full speed. Duos developed innovative data analytic solutions with AI at the edge to conduct more reliable railcar inspections, which are available 24/7/365 in all climates and conditions.
