Elastic Data Platform Architecture for Multi-Cloud IT Cost Optimization and Performance

  • Authors

    • Dr. Nimal Perera Professor, University of Colombo, Sri Lanka. Author

    DOI:

    https://doi.org/10.67228/30715717/IJDEIC-2020PII9H6A

    Published 12-11-2020

  • Elastic Data Platform (EDP), Multi-cloud architecture, IT cost optimization, Cloud performance, Cloud resource scaling, Data distribution, Auto-scaling, Cost analytics, Cloud-native architecture, Cloud migration strategies

    Issue

    Vol. 3 No. 2 (2020)

    Section

    Articles

    How to Cite

    [1]
    N. Perera, “Elastic Data Platform Architecture for Multi-Cloud IT Cost Optimization and Performance”, IJDEIC, vol. 3, no. 2, pp. 01–10, Dec. 2020, doi: 10.67228/30715717/IJDEIC-2020PII9H6A.

  • Abstract

    In today’s dynamic business environment, organizations are increasingly relying on multi-cloud strategies to achieve flexibility, cost efficiency, and scalability. However, managing and optimizing IT costs while ensuring optimal performance across multiple cloud environments remains a complex challenge. This paper explores the concept of an Elastic Data Platform (EDP) as a solution for multi-cloud IT cost optimization and performance. By leveraging the inherent elasticity of cloud resources, this architecture provides the ability to scale data infrastructure efficiently while maintaining high performance levels. We discuss the key design principles of an EDP, including data distribution, workload optimization, auto-scaling, and cost analytics, and how these can be implemented across multiple cloud providers. Additionally, we analyze real-world use cases, benefits, and challenges associated with this architecture. This paper aims to provide insights into how businesses can optimize both costs and performance in a multi-cloud environment using an Elastic Data Platform.

  • References

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