Leveraging OpenShift on AWS (ROSA) for Enterprise Container Platforms
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DOI:
https://doi.org/10.67228/30716357/IJMRSE-2024PI7Z4VPublished 03-04-2024
Red Hat Openshift Service On AWS (ROSA), Enterprise Container Platforms, Kubernetes, Cloud-Native Applications, AWS Cloud, Devops, Container Orchestration, Hybrid Cloud Issue
Section
ArticlesAbstract
Enterprise container platforms enable organizations to build, deploy, and manage cloud-native applications with greater efficiency, scalability, and consistency. However, managing Kubernetes clusters at scale introduces challenges related to infrastructure provisioning, security, monitoring, upgrades, and compliance. Red Hat OpenShift Service on AWS (ROSA) addresses these challenges by combining the enterprise capabilities of Red Hat OpenShift with the scalability and reliability of Amazon Web Services (AWS). This paper examines how ROSA supports secure and resilient container platforms while reducing operational complexity. A systematic review of containerization technologies, managed Kubernetes services, OpenShift architecture, and AWS capabilities is complemented by comparative analysis and practical deployment scenarios. Key factors include cluster management, security, scalability, automation, developer productivity, and cost optimization. The findings indicate that ROSA simplifies Kubernetes operations through managed infrastructure, integrated security, automated lifecycle management, and seamless AWS service integration, thereby improving developer productivity, deployment efficiency, and application modernization while supporting governance and reliability for mission-critical workloads.
References
[1] Vikas, G., Ishu Verma, and Praveen Rajagopalan. Achieving Digital Transformation Using Hybrid Cloud: Design standardized next-generation applications for any infrastructure. Packt Publishing Ltd, 2023.
[2] Parakala, A. (2023). Vendor Highlights – IoT, AI, and Process Mining. International Journal of Emerging Trends in Computer Science and Information Technology, 4(4), 135–146. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I4P115
[3] Muppaneni, R. K. (2023). Low-Code Revolution: How Power Platform Extends Dynamics 365 Capabilities. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(3), 162–171. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I3P119
[4] Santana, David. Cloud Computing Demystified for Aspiring Professionals: Hone your skills in AWS, Azure, and Google cloud computing and boost your career as a cloud engineer. Packt Publishing Ltd, 2023.
[5] Kumar Doodala, A. N., Thatraju, S., & Kankanala, V. (2023). Post-Pandemic QA Evolution in Healthcare IT. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 223–232. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P122
[6] Srigadde, B. R. (2023). The Hidden Gem: Lightning Headless Component. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 244–254. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P125
[7] Watada, Junzo, et al. "Emerging trends, techniques and open issues of containerization: A review." Ieee Access 7 (2019): 152443-152472.
[8] Vppalapati, M., & Talasila, P. K. (2023). Unobservable Performance: Storage Failures That Leave No Metrics Behind. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 177–188. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P120
[9] Kumar Doodala, A. N. (2023). Offline-First Android Architecture for waste management in low connectivity zones. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 201-209. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P121.
[10] Vanapalli, Satyendra Kumar. "Reducing Financial Fraud Using Machine Learning and CRM Data Models." International Journal of Machine Learning and Predictive Analytics 6.2 (2023): 01-20.
[11] Truyen, Eddy, et al. "A comprehensive feature comparison study of open-source container orchestration frameworks." Applied Sciences 9.5 (2019): 931.
[12] Gaddam, R. R., & Krishna, K. (2023). KFP v2 Artifact-Centric ML Pipeline Governance. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 142–153. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P116
[13] Takkalapally, D., & Takkellapally, M. R. (2023). GC-TuneHFT: AI-Based Garbage Collection Optimization in High-Frequency Trading Environments. American International Journal of Computer Science and Technology, 5(6), 25-37. https://doi.org/10.63282/3117-5481/AIJCST-V5I6P103
[14] Kandregula, Narendra. "Evaluating performance and scalability of multi-cloud environments: Key metrics and optimization strategies." World Journal of Advanced Research and Reviews (2022).
[15] Katangoori, S., & Katangoori, A. (2021). AI-Augmented Data Governance: Enabling Intelligent Access, Lineage, and Compliance Across Hybrid Clouds. American International Journal of Computer Science and Technology, 3(6), 36–45. https://doi.org/10.63282/3117-5481/AIJCST-V3I6P104
[16] Muppaneni, K. (2023). Virtual DOM vs Real DOM: Performance Benchmarks. International Journal of AI, BigData, Computational and Management Studies, 4(4), 180–189. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P118
[17] Shiramalla, R. (2022). Predictive Record Assignment Engine in Salesforce Using LWC and Einstein AI. International Journal of AI, BigData, Computational and Management Studies, 3(3), 147–159. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P117
[18] Taleb, Tarik, et al. "Toward supporting XR services: Architecture and enablers." IEEE Internet of Things Journal 10.4 (2022): 3567-3586.
[19] Allenki, S. S. (2023). Reducing Security Vulnerabilities With Encryption, IAM, and Regular Audits. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 265–275. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P127
[20] Suryadevara, S. S. K., & Nakirikanti, S. (2023). Privacy-Preserving Personalization Using Federated Learning in AEM. International Journal of AI, BigData, Computational and Management Studies, 4(4), 190–199. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P119
[21] Vanapalli, S. K. (2023). Data-Driven Decision Making: Integrating AI Tools With CRM Platforms. International Journal of Applied Data Science & Modern Computing, 6(1), 1–21.
[22] Edmundson, Chris, and Kenneth G. Hartman. "SANS 2022 DevSecOps Survey: Creating a Culture to Significantly Improve Your Organization’s Security Posture." URL https://www. Sans. Org/white-papers/sans-2022-devsecops-survey-creating-cultureimprove-organization-security (2022).
[23] Martin, Angel, et al. "Open-VERSO: a vision of 5G experimentation infrastructures, hurdles and challenges." arXiv preprint arXiv: 2308.14532 (2023).
[24] Henriques, Joao, et al. "The 5G-EPICENTRE Approach for Decreasing Attack Surface on Cross-Testbeds Cloud-native 5G Scenarios." 2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). IEEE, 2021.
[25] Gaddam, R. R. (2023). Progressive Delivery for Models with Quality KPIs. American International Journal of Computer Science and Technology, 5(4), 33–47. https://doi.org/10.63282/3117-5481/AIJCST-V5I4P104
[26] Alaisami, Mirna. Cloud-native applications: authoring and evaluation of two deployment patterns. Diss. Universitätsbibliothek der Universität Stuttgart, 2018.
[27] Muppaneni, R. K. (2023). AI-Driven Forecasting in Dynamics 365 Sales: What Businesses Need to Know? International Journal of AI, BigData, Computational and Management Studies, 4(1), 168–176. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I1P117
[28] Kommuru, Madhurima, and Appala Nooka Kumar Doodala. "Performance Bottlenecks Necks in Data Heavy Python Applications." International Journal of Applied Data Science & Modern Computing 6.2 (2023): 01-19.
[29] Shrivastava, Saurabh, Neelanjali Srivastav Alberto Artasanchez Imtiaz Sayed, and Dr Siddhartha Choubey. AWS for Solutions Architects. Packt Publishing, 2023.
[30] Vppalapati, M. (2023). When Identity Decisions Throttle Data Movement. International Journal of Emerging Research in Engineering and Technology, 4(3), 160–170. https://doi.org/10.63282/3050-922X.IJERET-V4I3P117
[31] Allenki, S. S. (2023). Applying Cloud Security Best Practices in Regulated Environments. American International Journal of Computer Science and Technology, 5(3), 48–60. https://doi.org/10.63282/3117-5481/AIJCST-V5I3P105
[32] Kaur, Kiranbir, DR Sandeep Sharma, and DR Karanjeet Singh Kahlon. "Interoperability and portability approaches in inter-connected clouds: A review." ACM Computing Surveys (CSUR) 50.4 (2017): 1-40.
[33] Suryadevara, S. S. K., & Nakirikanti, S. (2023). Privacy-Preserving Personalization Using Federated Learning in AEM. International Journal of AI, BigData, Computational and Management Studies, 4(4), 190–199. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P119
[34] Muppaneni, K. (2023). Virtual DOM vs Real DOM: Performance Benchmarks. International Journal of AI, BigData, Computational and Management Studies, 4(4), 180–189. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P118
[35] Shamim, Shazibul Islam, et al. "Benefits, challenges, and research topics: A multi-vocal literature review of Kubernetes." arXiv preprint arXiv: 2211.07032 (2022).
[36] Takkalapally, D. (2023). HoloSearchAI: AI-Driven Latency Optimization Framework for Distributed Search Systems. International Journal of Emerging Trends in Computer Science and Information Technology, 4(3), 217–227. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P122
[37] Shen, Junxian, et al. "Network-centric distributed tracing with deepflow: Troubleshooting your microservices in zero code." Proceedings of the ACM SIGCOMM 2023 Conference. 2023.
[38] Shiramalla, R. (2023). Optimizing Cross-Platform Enterprise Integrations Using Workato: A Case Study of Salesforce and Oracle SaaS Applications. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 232–243. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P124
[39] Srigadde, B. R. (2023). Creating Object Quick Actions With Lightning Web Components. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 167–180. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P118
[40] Parakala, A. (2021). Building Analytics-Driven Bots: RPA Meets Business Intelligence. International Journal of Emerging Research in Engineering and Technology, 2(1), 77–87. https://doi.org/10.63282/3050-922X.IJERET-V2I1P109
[41] Sarddar, Debabrata, Rajesh Bose, and Sandip Roy. Exploring the Fundamentals of: Cloud Computing. LAP LAMBERT Academic Publishing, 2018.
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