Designing Cloud-Native CRM Platforms for Next-Generation Telecom Operations
Authors/Creators
Description
Telecommunications enterprises increasingly rely on Customer Relationship Management (CRM) systems to coordinate customer engagement, revenue-cycle operations, and seamless digital service delivery across diverse channels. Yet, a significant portion of existing CRM implementations remain tightly embedded within monolithic Business Support Systems (BSS) and Operational Support Systems (OSS), creating rigid architectures that constrain scalability, hinder functional extensibility, and impede the fluid exchange of information across the enterprise ecosystem. Such legacy constructs are unable to support the dynamic orchestration, real-time responsiveness, and cross-domain interoperability that modern telecom environments demand.
This article introduces a cloud-native integration framework engineered to modernize telecom CRM ecosystems by decomposing core CRM functions into granular, independently deployable microservices governed through unified API gateways and event-driven orchestration layers. The proposed framework leverages distributed cloud infrastructure to facilitate high-throughput, low-latency information flows between CRM, billing, provisioning, assurance, and network intelligence domains. Through this modularization, the architecture supports elastic scaling, continuous feature evolution, and streamlined cross-platform integration, thereby enabling more adaptive customer experiences and substantial operational efficiencies. Beyond addressing immediate architectural limitations, the model establishes a strategic foundation for future-ready digital ecosystems capable of integrating advanced analytics, AI-driven personalization, autonomous service operations, and next-generation engagement platforms.
Files
EJAET-6-3-130-138.pdf
Files
(508.2 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:2870f3612b9c554e3a49d87c7a0bf0f9
|
508.2 kB | Preview Download |
Additional details
References
- [1]. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., & Zaharia, M. A view of cloud computing. Communications of the ACM, 53(4), 50-58. (2010) https://dl.acm.org/doi/10.1145/1721654.1721672
- [2]. Montesi, F., & Weber, J. Circuit breakers, discovery, and API gateways in microservices. https://arxiv.org/abs/1609.05830
- [3]. Google Cloud. (2016) Creating a scalable API with microservices. https://cloud.google.com/blog/products/gcp/creating-a-scalable-api-with-microservices/
- [4]. Amazon Web Services. (2015) Building API-Driven Microservices with Amazon API Gateway. https://docs.aws.amazon.com/apigateway/latest/developerguide/welcome.html
- [5]. Newman, S. Building Microservices (2015): Designing Fine-Grained Systems. https://www.oreilly.com/library/view/building-microservices/9781491950340/
- [6]. Richardson, C. Microservices Patterns: With Examples in Java. Manning Publications. (2018) https://www.manning.com/books/microservices-patterns
- [7]. Ericsson (2012). The Impact of Internet-Based Services on OSS and BSS. Ericsson Review. https://www.ericsson.com/4ac61a/assets/local/reports-papers/ericsson-technology-review/docs/2012/er-internet-impact-oss-bss.pdf
- [8]. Khaligh, A. A., Miremadi, A., & Aminilari, M. (2012). The impact of eCRM on loyalty and retention of customers in Iranian telecommunication sector. International Journal of Business and Management, 7(2), 150. http://dx.doi.org/10.5539/ijbm.v7n2p150
- [9]. Ekakitie-Emonena, S., & Abolaji, O. S. Electronic Customer Relationship Management and Marketing Performance in the Telecom Sector. (2015). https://doi.org/10.9734/BJEMT/2016/19924
- [10]. McKinsey & Company. (2017). The Case for Digital Reinvention. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-case-for-digital-reinvention
- [11]. Shravan Kumar Reddy Padur. (2016). Network Modernization in Large Enterprises: Firewall Transformation, Subnet Re-Architecture, and Cross-Platform Virtualization. In International Journal of Scientific Research & Engineering Trends (Vol. 2, Number 5). Zenodo. https://doi.org/10.5281/zenodo.17291987
- [12]. Chen, L. (2015). Continuous delivery: Huge benefits, but challenges too. IEEE software, 32(2), 50-54. https://doi.org/10.1109/MS.2015.27
- [13]. Shravan Kumar Reddy Padur "Empowering Developer & Operations Self-Service: Oracle APEX + ORDS as an Enterprise Platform for Productivity and Agility" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN: 2395-1990, Online ISSN: 2394-4099, Volume 4, Issue 11, pp.364-372, November-December-2018. Available at doi: https://doi.org/10.32628/IJSRSET1844429
- [14]. Kranthi Kumar Routhu. (2018). Seamless HR Finance Interoperability: A Unified Framework through Oracle Integration Cloud. In International Journal of Science, Engineering and Technology (Vol. 6, Number 1). Zenodo. https://doi.org/10.5281/zenodo.17292100
- [15]. Sudhir Vishnubhatla. (2019). From Rules to Neural Pipelines: NLP-Powered Automation for Regulatory Document Classification in Financial Systems. In International Journal of Science, Engineering and Technology (Vol. 7, Number 1). Zenodo. https://doi.org/10.5281/zenodo.17473977
- [16]. Kranthi Kumar Routhu. (2019). Hybrid Machine Learning Architecture for Absence Forecasting within Oracle Cloud HCM. KOS Journal of AIML, Data Science, and Robotics, 1(1), 1–5. https://doi.org/10.5281/zenodo.17531173
- [17]. Sudhir Vishnubhatla. (2018). From Risk Principles to Runtime Defenses: Security and Governance Frameworks for Big Data in Finance. In International Journal of Science, Engineering and Technology (Vol. 6, Number 1). Zenodo. https://doi.org/10.5281/zenodo.17452405