Automation-Driven Reliability Engineering for Public-Sector Biomedical Systems
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Abstract
One of the fundamental requirements of the biomedical systems of the state that takes part in the support of the national research and the national health programs is reliability. These are mission-sensitive platforms that are very sensitive as regards maintenance because any slight failure can lead to severe consequences. The paper will discuss how reduced reliability engineering through automation can be applied to enhance the resiliency of the systems and this is particularly in cases where the systems are operating on a limited regulatory framework. It takes into account among the most significant practices, including self-healing pipelines, automated rollback plans, and telemetry-based monitors to strengthen the performance of the system and minimize disruptions. Such systems can independently detect and react to failures with the aid of automation so as to reduce the possibility of occurrence of incident and speed up recovery. The research demonstrates that incident rate and recovery duration have greatly been reduced with time which is due to the study that is conducted longitudinally which justifies the value of such automation plans in providing continuity of operations. It has shown that the practices can be used to create fault tolerant and high availability architectures that can be used to meet the demands. Besides, the paper discusses the telemetry-based monitoring as the means of enhancing the reliability of services through the integration of real-time data to implement a quick response and make decisions. Overall, this research demonstrates that automation is essential in promoting credibility of biomedical platforms, which also offers helpful information as to how such systems can be capable of responding to the changes, which are being made, and at the same time meet the regulatory and operational demands. The results can be used as a guide toward the implementation of automation architectures into government-based IT infrastructure, which facilitates the resilience of systems, as well as their efficiency in key biomedical services.
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References
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