Optimizing DevOps Pipelines with Automation: Ansible and Terraform in AWS Environments

Venkat Marella

doi:10.32628/IJSRSET2410614

Authors

Venkat Marella Independent Researcher, USA Author

DOI:

https://doi.org/10.32628/IJSRSET2410614

Keywords:

(IaC), Kubernetes Clusters, AWS Platform, Cloud Native, Mathematical Model, IT Environments, CI/CD Pipelines, Simultaneous Project, Cloud Management, (DevOps)

Abstract

In order to improve operational efficiency and agility in contemporary IT systems, this study investigates the integration of DevOps methods with cloud management. It offers a thorough rundown of the main DevOps tools and technologies needed to manage cloud infrastructure, including as monitoring systems, CI/CD pipelines, Infrastructure as Code (IaC) tools, and configuration management systems. The inability to allow concurrent project development and deployment on the same operational infrastructure (such as a cluster of Docker containers) is a practical shortcoming of current DevOps systems. In order to fill the gaps in the current Development and Operations (DevOps) methods, this paper offers a thorough study and explores how such integrations in Amazon Web Services might enhance deployment efficiency, dependability in software and infrastructure delivery, and security. Thus, the goal of this research is to use the AWS platform to automate the processes of developing and maintaining IT infrastructure. Therefore, we provide a mathematical model in this research to ascertain the ideal arrangement for IT infrastructure. This study investigates in detail how Kubernetes clusters in the AWS environment may be efficiently automated, scaled, and managed using Terraform, an Infrastructure as Code (IaC) tool. It thoroughly examines the advantages of using Terraform, highlighting how it may enhance productivity, automation, scalability, and security while managing Kubernetes clusters. To demonstrate Terraform's capabilities in infrastructure management, the paper contrasts it with other popular (IaC) tools and techniques. It also explores how Terraform works with AWS services to streamline procedures and cut down on complexity. Trends and possible developments in combining Kubernetes and Terraform to improve the administration of cloud-native apps are also covered in the paper.

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References

Yu, Y.; Silveira, H.; Sundaram, M. A microservice based reference architecture model in the context of enterprise architecture. In Proceedings of the 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi’an, China, 3–5 October 2016; pp. 1856–1860. DOI: https://doi.org/10.1109/IMCEC.2016.7867539

Villamizar, M.; Garcés, O.; Castro, H.; Verano, M.; Salamanca, L.; Casallas, R.; Gil, S. Evaluating the monolithic and the microservice architecture pattern to deploy web applications in the cloud. In Proceedings of the 2015 10th Computing Colombian Conference (10CCC), Bogota, Colombia, 21–25 September 2015; pp. 583–590. DOI: https://doi.org/10.1109/ColumbianCC.2015.7333476

Kalske, M.; Mäkitalo, N.; Mikkonen, T. Challenges When Moving from Monolith to Microservice Architecture. In Current Trends in Web Engineering. ICWE 2017; Garrigós, I., Wimmer, M., Eds.; Lecture Notes in Computer Science; Springer: Cham, Switzerland, 2018; Volume 10544. DOI: https://doi.org/10.1007/978-3-319-74433-9_3

Bernstein, D. Containers and Cloud: From LXC to Docker to Kubernetes. IEEE Cloud Comput. 2014, 1, 81–84. DOI: https://doi.org/10.1109/MCC.2014.51

Wan, X.; Guan, X.; Wang, T.; Bai, G.; Choi, B.-Y. Application deployment using Microservice and Docker containers: Framework and optimization. J. Netw. Comput. Appl. 2018, 119, 97–109. DOI: https://doi.org/10.1016/j.jnca.2018.07.003

Armenise, V. Continuous Delivery with Jenkins: Jenkins Solutions to Implement Continuous Delivery. In Proceedings of the 2015 IEEE/ACM 3rd International Workshop on Release Engineering, Florence, Italy, 19 May 2015; pp. 24–27. DOI: https://doi.org/10.1109/RELENG.2015.19

Bass, L.; Clements, P.; Kazman, R. Software Architecture in Practice, 3rd ed.; Addison-Wesley: Westford, MA, USA, 2012.

Saito, H.; Lee, H.-C.; Wu, C.-Y. DevOps with Kubernetes; Packt Publishing: Birmingham, UK, 2017; ISBN 978-1-78839-664-6.

Jenkins, D.; Arnaud, J.; Thompson, S.; Yau, M.; Wright, J. Version Control and Patch Management of Protection and Automation Systems. In Proceedings of the 12th IET International Conference on Developments in Power System Protection, Copenhagen, Denmark, 31 March–3 April 2014. DOI: https://doi.org/10.1049/cp.2014.0152

Chandrasekara, C.; Herath, P. Branching with Azure Git Repos. In Hands-On Azure Repos; Apress: Berkeley, CA, USA, 2020. DOI: https://doi.org/10.1007/978-1-4842-5425-7

Chen, L. Microservices: Architecting for Continuous Delivery and DevOps. In Proceedings of the 2018 IEEE International Conference on Software Architecture (ICSA), Seattle, WA, USA, 30 April–4 May 2018; pp. 39–397. DOI: https://doi.org/10.1109/ICSA.2018.00013

Abrar Mohammad Mowad, Hamed Fawareh, Mohammad A. Hassan, Effect of Using Continuous Integration (CI) and Continuous Delivery (CD) Deployment in DevOps to reduce the Gap between Developer and Operation, International Arab Conference on Information Technology (ACIT),22-24 November 2022.

Gowtham Mulpuri, CI/CD Pipeline Optimization for Accelerated Development Cycles,European Journal of Advances in Engineering and Technology, 2023.

A. Rahman, R. Mahdavi-hezaveh, and L. Williams, “A systematic mapping study of infrastructure as code research,” Information and Software Technology, vol. 108, 12 2018. DOI: https://doi.org/10.1016/j.infsof.2018.12.004

D. K. Sharma, “Terraform vs ansible: Key differences between devops tools,” Mar 2024.

K. MORRIS, Infrastructure as code: Dynamic Systems for the cloud age. O’REILLY MEDIA, 2021. ISBN 9781098114671.

R. Alif and L. Munggaran, “Implementation of gitops in containerized infrastructure,” Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, vol. 9, no. 1, pp. 154–161, Feb. 2024. DOI: https://doi.org/10.36341/rabit.v9i1.3787

Ekanayaka E, Thathsarani J, Karunanayaka D, Kuruwitaarachchi N, Skandakumar N. Enhancing devops infrastructure for efficient management of microservice applications. 2023 IEEE International Conference on e-Business Engineering (ICEBE) 2023; 63-68. DOI: https://doi.org/10.1109/ICEBE59045.2023.00035

Sheikh S, Suganya G, Premalatha M. Automated resource management on AWS cloud platform. Proceedings of 6th International Conference on Big Data and Cloud Computing Challenges 2019. DOI: https://doi.org/10.1007/978-981-32-9889-7_11

Sindhu G, N. Mtech, and R. Pavithra D. Deploying a Kubernetes Cluster with Kubernetes Operation (kops) on AWS Cloud: Experiments and Lessons Learned. Int J Engineering Advanced Technology 2020.

Campbell B. Terraform In-Depth. The definitive guide of AWS infrastructure automation 2019; 123-203. DOI: https://doi.org/10.1007/978-1-4842-5398-4_4

Sahana B, Kumaraswamy T, Nachiketh RG, Navadeep S, Noronha J. Weight based load balancing in Kubernetes using AWS. 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) 2023; 629-634. DOI: https://doi.org/10.1109/IDCIoT56793.2023.10053466

Bailuguttu S, Chavan A, Pal O, Sannakavalappa K, Chakrabarti D. Comparing performance of bastion host on cloud using Amazon web services vs terraform. Indonesian J Electrical Engineering Computer Science 2023. DOI: https://doi.org/10.11591/ijeecs.v30.i3.pp1722-1728

Ganeshan M, Malathi S. Building and deploying a static application using Jenkins and Docker in AWS, Int J Trend in Scientific Research and Development 2020.

Haragi LD, Mahith S, Sahana B. Infrastructure Optimization in Kubernetes Cluster. J University of Shanghai for Science and Technology 2021.