Case Study Based Investigation on Self-Healing Cloud Deployments for Edge-Based Software Development

Cloud Computing has enabled many application providers to deploy web applications in cloud data centers with the advent of on-demand resource allocation and self-healing techniques that provide high availability and flexibility. However, web applications frequently have dynamic workloads that are difficult to forecast. Researchers and Cloud service providers are working hard to find ways to cut costs without sacrificing Quality of Service (QoS). Self-healing is one of the key issues in Cloud computing for application deployment, which is still in its early phases and necessitates extensive research on taxonomy, methodologies, and resource requirements. This article provides a complete overview of self-healing approaches for cloud application deployment. This work aims to assist the scientific community in identifying the elements required for efficient self-healing strategies. An overview of evaluated studies is presented, including various self-healing strategies, resources, monitoring tools, experiments, workloads, metrics, and other pertinent factors. This work provides useful insights and lays the groundwork for future research in this area. In this work, an existing platform is deployed using several self-healing deployment methodologies and responses from various stakeholders are collected and analyzed. The analysis of stakeholders response indicates that self-healing strategies provide better acceptance and deployment with increased customer delight. After self-healing cloud deployment. The survey result indicates self healing improves issue detection, down time and overall system reliability by 90%, 85% and 70%. The operational overhead was reduced by 70%.