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The Beginning of a Cognitive Software Engineering Era with Self-Managing Applications

机译:具有自我管理应用程序的认知软件工程时代的开始

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The recent explosion of data and the resurgence of AI, Machine Learning and Deep Learning, and the emergence of unbounded cloud computing resources are stretching current software engineering practices to meet business application development, deployment and management requirements. As consumers demand communication, collaboration and commerce almost at the speed of light without interruption, businesses are looking for information technologies that keep up the pace in delivering faster time to market and real-time data processing to meet rapid fluctuations in both workload demands and available computing resources. While the performance of server, network and storage resources have dramatically improved by orders of magnitude in the past decade, software engineering practices and IT operations are evolving at a slow pace. This paper explores a new approach that will provide a path to self-managing software systems with fluctuation tolerance to both workload demands and available resource pools. The infusion of a cognitive control overlay enables an advanced management of application workloads in a distributed multi-cloud computing infrastructure. Resulting architecture provides a uniform framework for managing workload non-functional requirements such as availability, performance, security, data compliance and cost independent of the execution venue for functional requirement workflows.
机译:数据的爆炸式增长以及AI,机器学习和深度学习的兴起以及无限制的云计算资源的出现,正在扩展当前的软件工程实践,以满足业务应用程序开发,部署和管理要求。随着消费者几乎无间断地要求通信,协作和商务的发展,企业正在寻找能够与时俱进的信息技术,以加快上市时间和实时数据处理,从而满足工作负载需求和可用资源的快速波动。计算资源。在过去的十年中,尽管服务器,网络和存储资源的性能已显着提高了几个数量级,但软件工程实践和IT运营却在缓慢发展。本文探索了一种新方法,该方法将提供一种自我管理软件系统的路径,该系统具有对工作负载需求和可用资源池的波动容忍度。认知控制覆盖的注入可在分布式多云计算基础架构中对应用程序工作负载进行高级管理。最终的架构提供了一个统一的框架,用于管理工作负载非功能性需求,例如可用性,性能,安全性,数据合规性和成本,而与功能性需求工作流的执行场所无关。

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