Modernizing Service Assurance: Migration and Optimization of IBM Netcool in OpenShift Environments
DOI:
https://doi.org/10.32628/CSEIT1825411Keywords:
IBM Netcool Operations, OpenShift Container Platform (OCP), JFrog Artifactory, IBM Netcool Operations Insight (NOI), KafkaAbstract
This article investigates the complexities of migrating and optimizing IBM Netcool Operations Insight (NOI) within OpenShift Container Platform (OCP). It provides a detailed analysis of architectural considerations, practical migration strategies, and optimization techniques, focusing on the upgrade from NOI 1.6.4 to 1.6.5. The study explores the integration of Kafka-based probes and JDBC gateways, alongside the automation of deployments using JFrog Artifactory. The findings offer valuable insights for IT architects, DevOps engineers, and Netcool administrators seeking to enhance service assurance in modern cloud-native environments, highlighting the benefits of containerization and automation in improving operational efficiency and scalability.
References
- Mell, P., & Grance, T. (2011). The NIST definition of cloud computing. National Institute of Standards and Technology, 53(6), 50.
- Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future generation computer systems, 25(6), 599-616.
- Fnu, Y., Saqib, M., Malhotra, S., Mehta, D., Jangid, J., & Dixit, S. (2021). Thread mitigation in cloud native application Develop- Ment. Webology, 18(6), 10160–10161, https://www.webology.org/abstract.php?id=5338s
- Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., ... & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
- Dean, J., & Ghemawat, S. (2004). MapReduce: simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113.
- Ousterhout, J., Rosencrantz, R., Agrawal, A., Armbrust, M., Gupta, R., Hinshaw, D., ... & Zaharia, M. (2015). Sparrow: distributed, low-latency scheduling. ACM SIGOPS Operating Systems Review, 49(1), 175-190.
- J. Jangid, "Efficient Training Data Caching for Deep Learning in Edge Computing Networks," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 7, no. 5, pp. 337–362, 2020. doi: 10.32628/CSEIT20631113
- Brewer, E. A. (2012). CAP twelve years later: how “rules” have changed. Computer, 45(2), 23-29.
- Dikaiakos, M. D., Katsaros, D., Mehra, P., Pallis, G., & Vakali, A. (2009). Cloud computing: distributed internet computing for IT and scientific research. Internet computing, 13(5), 10-13
- Vaquero, L. M., Rodero-Merino, L., Caceres, J., & Lindner, M. (2009). A break in the clouds: towards a cloud definition. ACM SIGCOMM Computer Communication Review, 39(1), 50-55.
- Bernstein, D. (2009). Containers and cloud: From lxc to docker to kubernetes. IEEE Cloud Computing, 1(3), 81-84.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT

This work is licensed under a Creative Commons Attribution 4.0 International License.