| Summary: | Context: Backup and Disaster Recovery, DR play a vital role in day-to-day IT operations. They define extensive aspects of business continuity plan in an enterprise. There is a continuous need to improve backup and recovery performance concerning attributes such as backup window size, high availability, security, etc. Definitive information is what enterprises strive for and rely upon to deviate from traditional methods towards advancing technologies, which are an intrinsic segment of business mundane actions. Objectives: In this study, we investigate Backup and DR plans on an enterprise level. They are compared in terms of performance metrics such as Recovery Time Objective, Recovery Point Objective, Time taken to backup, Time taken to recover and Total cost of ownership. Also, how CPU and memory utilization conduct differ in both tape-based, cloud-based Backup and DR. Methods: Literature study was the first step to formulate research questions by understanding present technologies in Backup and DR. This led us to conduct a survey for further understanding of challenges faced in industries gaining a more practical exposure. A case study was conducted in an enterprise to capture accurate values. An experiment had been deployed to compare performance of both scenarios and analyze which methodology elevates Backup and DR performance by overcoming challenges. Results: The results attained through this thesis encompass performance related metrics and also the load in terms of CPU and memory utilizations. Survey results were observed to gain better understanding of current technologies and challenges with Backup and DR in enterprises. The cloudbased backup has proved to be better in considered enterprise environment during experimentation in terms of RPO, RTO, CPU, memory utilizations and Total Cost of ownership. Conclusions: There have been numerous research works conducted on how backup and DR plans can be made better. But, they lack accurate information on how their performances vary, what all parameters can be improved by shifting towards advanced and contemporary methodologies withaddressing features such as scalability, flexibility and adaptability, which is provided in this study.
|
|---|
