Disaster Recovery and Data Backup Optimization: Exploring Next-Gen Storage and Backup Strategies in Multi-Cloud Architectures
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V5I3P104Keywords:
Disaster recovery, data backup, multi-cloud, storage optimization, cloud resilience, backup automation, next-gen storage, data security, business continuity, DRaaS (Disaster Recovery as a Service)Abstract
Companies mostly depend on data in the new digital environment; hence, sustaining resilience and continuity depends on backup planning and disaster recovery (DR). Common multi-cloud architectures must allow businesses to manage advanced storage systems characterized by data distribution across many cloud providers. Conventional backup plans for dynamic environments show security flaws, inefficiency, and compliance difficulties. Modern storage choices, analytics driven by artificial intelligence & the improved backup system automation are changing how businesses protect their critical information. While simultaneously reducing downtime, modern cloud-based disaster the recovery methods must also handle basic issues such as cost-effectiveness, data redundancy, latency & the regulatory compliance. Edge storage, unchangeable backups & the distributed data management are among creative ideas improving security and the accelerating business recovery times. Adopting a comprehensive disaster recovery & the backup strategy calls for a great awareness of workload distribution, interoperability across cloud service providers and the changing terrain of cyber threats. By means of proactive policies & the cutting-edge technology, companies may build a strong multi-cloud architecture guaranteeing data integrity, operational stability & the fast recovery during interruptions
References
[1] Mulder, Jeroen. Multi-Cloud Architecture and Governance: Leverage Azure, AWS, GCP, and VMware vSphere to build effective multi-cloud solutions. Packt Publishing Ltd, 2020.
[2] Grover, Vikas, Ishu Verma, and Praveen Rajagopalan. Achieving Digital Transformation Using Hybrid Cloud: Design standardized next-generation applications for any infrastructure. Packt Publishing Ltd, 2023.
[3] Raj, Pethuru, et al. "Automated multi-cloud operations and container orchestration." Software-Defined Cloud Centers: Operational and Management Technologies and Tools (2018): 185-218.
[4] George, A. Shaji, et al. "The Impact of Cloud Hosting Solutions on IT Jobs: Winners and Losers in the Cloud Era." Partners Universal International Research Journal 2.3 (2023): 1-19.
[5] Shrivastwa, Alok. Hybrid cloud for architects: Build robust hybrid cloud solutions using aws and openstack. Packt Publishing Ltd, 2018.
[6] Kandi, Pravallika, et al. "A review: Data security in cloud computing using machine learning." 2022 5th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2022.
[7] Mukherjee, Aditya. Network Security Strategies: Protect your network and enterprise against advanced cybersecurity attacks and threats. Packt Publishing Ltd, 2020.
[8] Raj, Pethuru, and Anupama Raman. Software-defined Cloud Centers. Springer, 2018.
[9] Watada, Junzo, et al. "Emerging trends, techniques and open issues of containerization: A review." IEEE Access 7 (2019): 152443-152472.
[10] McGlynn, Jason. "Literature Survey of Big Data." (2023).
[11] Patel, Jalpa, Manuel Velasco, and Avinash Shukla. Implementing Cisco HyperFlex Solutions. Cisco Press, 2020.
[12] Lamsal, Binod. Cloud-based Cybersecurity Products, a Detail Analysis, and the Awareness Platform. MS thesis. Utica College, 2020.
[13] Ozgur, Ceyhun, Jeffrey Coto, and David Booth. "Usage of Hadoop and Microsoft Cloud in Big Data Analytics." AIMS International Journal of Management 12.3 (2018).
[14] Eryurek, Evren, et al. Data governance: The definitive guide. " O'Reilly Media, Inc.", 2021.
[15] Data, EcoStruxureTM. "FASTER." (2022).
