Enhancing DevOps with Azure Cloud Continuous Integration and Deployment Solutions

Authors

  • Kanaka Rakesh Varma Kothapalli Consultant, Yotta Systems Inc., 340 Mt Kemble Ave, Morristown, New Jersey, 07960, USA

DOI:

https://doi.org/10.18034/ei.v7i2.721

Keywords:

DevOps, Azure Cloud, Continuous Integration, Continuous Deployment, CI/CD Solutions, Cloud Automation

Abstract

This study addresses the critical gap in optimizing DevOps practices within Azure Cloud environments, focusing on continuous integration and deployment solutions. The primary objective is to explore advanced security practices, scalability through architectural patterns, and the integration of compliance and performance monitoring. Key findings indicate that leveraging Azure Security Center and Azure Sentinel significantly enhances data protection and regulatory compliance. Employing scalable architectures, such as microservices and serverless computing, optimizes resource usage and application performance. The integration of Azure Monitor, Log Analytics, and Application Insights ensures comprehensive monitoring, proactive issue detection, and adherence to compliance standards. These strategies collectively improve DevOps efficiency, resulting in faster and more reliable software delivery. Policy implications suggest that organizations should adopt Azure's advanced tools and practices to enhance security, scalability, and compliance in their DevOps processes, ultimately driving operational excellence and continuous improvement in cloud-based applications.

Downloads

Download data is not yet available.

References

Bharadi, V. A., & Meena, M. (2015). Novel architecture for CBIR SAAS on Azure cloud. The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, 366-371. https://doi.org/10.1109/INFOP.2015.7489409 DOI: https://doi.org/10.1109/INFOP.2015.7489409

Bhardwaj, A., Singh, V. K., Vanraj, V., & Narayan, Y. (2015). Analyzing BigData with Hadoop cluster in HDInsight azure Cloud. The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, 1-5. https://doi.org/10.1109/INDICON.2015.7443472 DOI: https://doi.org/10.1109/INDICON.2015.7443472

Chen, P., Lee, E., & Wang, L. (2013). A cloud-based synthetic seismogram generator implemented using Windows Azure. Earthquake Science, 26(5), 321-329. https://doi.org/10.1007/s11589-013-0038-8 DOI: https://doi.org/10.1007/s11589-013-0038-8

Costan, A., Tudoran, R., Antoniu, G., & Brasche, G. (2016). TomusBlobs: scalable data-intensive processing on Azure clouds. Concurrency and Computation: Practice & Experience, 28(4), 950-976. https://doi.org/10.1002/cpe.3034 DOI: https://doi.org/10.1002/cpe.3034

Hoske, M. T. (2014). Microsoft Azure cloud platform connects with Rockwell Automation as first industrial partner. Control Engineering, 61(7).

Kim, I., Jung, J., DeLuca, T. F., Nelson, T. H., & Wall, D. P. (2012). Cloud Computing for Comparative Genomics with Windows Azure Platform. Evolutionary Bioinformatics, 8, 527. DOI: https://doi.org/10.4137/EBO.S9946

Lu, S., Ranjan, R., & Strazdins, P. (2015). Reporting an experience on design and implementation of e-Health systems on Azure cloud. Concurrency and Computation: Practice & Experience, 27(10), 2602-2615. https://doi.org/10.1002/cpe.3325 DOI: https://doi.org/10.1002/cpe.3325

Mohammed, M. A., Kothapalli, K. R. V., Mohammed, R., Pasam, P., Sachani, D. K., & Richardson, N. (2017a). Machine Learning-Based Real-Time Fraud Detection in Financial Transactions. Asian Accounting and Auditing Advancement, 8(1), 67–76. https://4ajournal.com/article/view/93

Mohammed, R., Addimulam, S., Mohammed, M. A., Karanam, R. K., Maddula, S. S., Pasam, P., & Natakam, V. M. (2017). Optimizing Web Performance: Front End Development Strategies for the Aviation Sector. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 38-45. https://upright.pub/index.php/ijrstp/article/view/142

Mrozek, D., Gosk, P., & Małysiak-Mrozek, B. (2015). Scaling Ab Initio Predictions of 3D Protein Structures in Microsoft Azure Cloud. Journal of Grid Computing, 13(4), 561-585. https://doi.org/10.1007/s10723-015-9353-8 DOI: https://doi.org/10.1007/s10723-015-9353-8

Persico, V., Marchetta, P., Botta, A., & Pescape, A. (2014). On Network Throughput Variability in Microsoft Azure Cloud. The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings., 1-6. https://doi.org/10.1109/GLOCOM.2014.7416997 DOI: https://doi.org/10.1109/GLOCOM.2014.7416997

Sachani, D. K., & Vennapusa, S. C. R. (2017). Destination Marketing Strategies: Promoting Southeast Asia as a Premier Tourism Hub. ABC Journal of Advanced Research, 6(2), 127-138. https://doi.org/10.18034/abcjar.v6i2.746 DOI: https://doi.org/10.18034/abcjar.v6i2.746

Shanahan, H. P., Owen, A. M., & Harrison, A. P. (2014). Bioinformatics on the Cloud Computing Platform Azure. PLoS One, 9(7). https://doi.org/10.1371/journal.pone.0102642 DOI: https://doi.org/10.1371/journal.pone.0102642

Ying, D., Kothapalli, K. R. V., Mohammed, M. A., Mohammed, R., & Pasam, P. (2018). Building Secure and Scalable Applications on Azure Cloud: Design Principles and Architectures. Technology & Management Review, 3, 63-76. https://upright.pub/index.php/tmr/article/view/149

Ying, D., Patel, B., & Dhameliya, N. (2017). Managing Digital Transformation: The Role of Artificial Intelligence and Reciprocal Symmetry in Business. ABC Research Alert, 5(3), 67–77. https://doi.org/10.18034/ra.v5i3.659 DOI: https://doi.org/10.18034/ra.v5i3.659

Downloads

Published

2019-12-31

Issue

Section

Peer Reviewed Articles

How to Cite

Kothapalli, K. R. V. (2019). Enhancing DevOps with Azure Cloud Continuous Integration and Deployment Solutions. Engineering International, 7(2), 179-192. https://doi.org/10.18034/ei.v7i2.721

Similar Articles

51-60 of 61

You may also start an advanced similarity search for this article.