It is a trend for hospitals to shift healthcare applications to cloud computing because the cloud has a powerful computing ability. The valuable, sensitive patient data is stored in the remote cloud. This makes it necessary for a hospital to build an autonomous cloud. However, there is a conflict between limited IT department staff and prosperous e-healthcare applications. To solve this problem, a distributed container-based Internet of Things (IoT)-enabled e-healthcare system for Development and Operations (DevOps) is presented. Using container technology and orchestration, a traditional healthcare application is deconstructed into a series of containers and is reorganized according to the application logic that facilitates DevOps. The introducing of container technology makes it possible to automatically increase or decrease docker containers when the e-healthcare application scales up or down. The function and performance of the proposed system are proved through three cases, i.e., scalability, service, and continuous integration (CI)/continuous delivery (CD) pipeline.

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A Distributed Container-Based Internet of Things (IoT)-Enabled Autonomous E-Healthcare System for Development and Operations (DevOps)

  • Qinglong Dai,
  • Guangjun Qin,
  • Ran Li

摘要

It is a trend for hospitals to shift healthcare applications to cloud computing because the cloud has a powerful computing ability. The valuable, sensitive patient data is stored in the remote cloud. This makes it necessary for a hospital to build an autonomous cloud. However, there is a conflict between limited IT department staff and prosperous e-healthcare applications. To solve this problem, a distributed container-based Internet of Things (IoT)-enabled e-healthcare system for Development and Operations (DevOps) is presented. Using container technology and orchestration, a traditional healthcare application is deconstructed into a series of containers and is reorganized according to the application logic that facilitates DevOps. The introducing of container technology makes it possible to automatically increase or decrease docker containers when the e-healthcare application scales up or down. The function and performance of the proposed system are proved through three cases, i.e., scalability, service, and continuous integration (CI)/continuous delivery (CD) pipeline.