下载PDF
Amica reduces software deployment times by 95 – 98 percent
技术
- 应用基础设施与中间件 - API 集成与管理
适用功能
- 离散制造
用例
- 预测性维护
服务
- 软件设计与工程服务
挑战
Amica 是一家提供汽车、房屋和人寿保险的互助保险公司，其软件部署流程面临问题。该公司的环境包括众多 Web 服务、多个 Web 应用和核心应用程序。由于有数十名开发人员签入代码，将每个服务和应用程序的正确版本部署到多个测试、生产和备份环境变得极其困难。确保在每个环境中正确安装正确代码的正确版本的过程已成为一场后勤噩梦。当部署出现问题时，它们通常是由应用程序不一致而不是代码缺陷引起的。
关于客户
Amica 是一家提供汽车、房屋和人寿保险的互助保险公司。该公司的环境包括众多 Web 服务、多个 Web 应用和核心应用程序。数十名开发人员正在签入代码，然后该公司必须将这些代码部署到多个环境中。确保将每个服务和应用程序的正确版本部署到众多测试、生产和备份环境的过程变得极其困难。
解决方案
Amica 组建了一个应用程序配置管理 (ACM) 团队，该团队实施了 IBM UrbanCode Deploy 软件，并将其与公司现有的开源工具集成。该团队与客户端/服务器基础架构 (CSI) 团队合作，使用 IBM UrbanCode 软件创建可重复的部署流程，帮助其部署每个 Web 服务和应用程序的正确版本以及所有相关代码的正确版本，从而显著减少兼容性问题。使用 IBM UrbanCode Deploy 软件，团队可以快速重新创建部署。作为更全面的 DevOps 方法的一部分，ACM 还将静态代码分析工具嵌入到其构建和部署流程中。每次将代码签入公司存储库时，这些工具都会对其进行分析，如果代码未达到某个质量阈值，工具就会拒绝它。此过程有助于从一开始就防止部署缺陷。
运营影响
数量效益
相关案例.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Asset Management and Predictive Maintenance
The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.
