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An Intelligent DevOps Platform Research and Design Based on Machine Learning

机译:基于机器学习的智能Devops平台研究与设计

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With the continuous deepens and expansion of IT business based on AI, machine learning and blockchain technologies, there are many developments in intelligent communication and Internet industries. Matured IT business cause daily DevOps (Development & Operations) works must deal with huge amounts of data. What the trickier work gradually emerged is that these data have complex sources, various formats, and other issues. Efficient and inexpensive DevOps of computer software and hardware systems become an important task which needs to be resolved. In SLC (Software Life Cycle), DevOps occupies more than half proportion. It impact entire IT business reflected in the business overall control, business risk control, and business cost control. In order to improve the efficiency of DevOps engineers and ensure the high-quality intelligence level of DevOps, this project starts with the DevOps theoretical framework, use machine learning method to do research, and design an intelligent DevOps platform, which can help engineers analyze huge amounts of multifarious system alarms, promotes the development of DevOps in the direction of informatization.
机译:基于AI,机器学习和区块科技的持续加深和扩展IT业务,智能沟通和互联网行业存在许多发展。成熟的IT业务导致日常Devops(开发和运营)工作必须处理大量数据。逐渐出现的棘手工作是什么,这些数据具有复杂的来源,各种格式和其他问题。高效廉价的计算机软件和硬件系统的DevOps成为需要解决的重要任务。在SLC(软件生命周期)中,Devops占据了超过半比例的。它会影响整个IT业务,反映在业务整体控制,企业风险控制和商业成本控制中。为了提高Devops工程师的效率并确保Devops的高质量智能水平,该项目从Devops理论框架开始,使用机器学习方法进行研究,并设计智能Devops平台,可以帮助工程师分析巨大多种系统报警量的数量,促进了信息化方向的Devops的发展。

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