Mastering DevOps
A Cloud Engineering and Data Science Perspective
- 1st Edition - April 1, 2026
- Latest edition
- Authors: Chinmaya Kumar Dehury, Satish Narayana Srirama
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 5 0 3 2 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 5 0 3 3 - 4
Mastering DevOps: A Cloud Engineering and Data Science Perspective addresses the challenge of understanding and implementing DevOps in an era of rapid technological advanc… Read more
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Mastering DevOps: A Cloud Engineering and Data Science Perspective addresses the challenge of understanding and implementing DevOps in an era of rapid technological advancement, where cloud-based infrastructure and data science applications have become integral to many organizations. The book covers the specific requirements of these fields, such as scalability, automation, and managing large-scale data and containerized applications. Mastering DevOps offers readers the knowledge and skills necessary to build, deploy, and manage DevOps practices effectively within the context of cloud engineering and data science. The book focuses on DevOps principles while integrating core technologies such as cloud computing, microservices, and continuous integration/continuous delivery (CI/CD). Additionally, the book provides coverage of a DevOps approach tailored to data science by covering recent advancements and explaining their relevance in a DevOps environment. The structure of the book is divided into four units, each progressively building on the concepts of the previous one. The first unit (Unit 1: Foundations of DevOps) provides the fundamental principles of DevOps, including its history, planning, and essential tools like Git. The second unit (Unit 2: Core Technologies and Architectures) introduces the core technologies and architectures that power modern DevOps, such as microservices, cloud computing, and containerization. The third unit (Unit 3: CI/CD Practices and Automation) focuses on the practical implementation of DevOps, exploring key practices like continuous integration, automation, and monitoring. Finally, the fourth unit (Unit 4: Advanced Topics and Data Science Perspective) delves into advanced topics and future trends, such as deployment strategies and the extension of DevOps principles to data science and other narrowed-down domains.
- Presents end-to-end DevOps phases with real-world applications, covering each DevOps phase, from planning to monitoring, with practical examples and scenarios that resonate with real-world applications in cloud and data science
- Includes detailed coverage of core technologies such as cloud computing, containerization (e.g., Docker and Kubernetes), and continuous integration/delivery pipelines
- Chapters on DataOps explain how to implement DevOps principles in data pipelines and machine learning workflows, meeting the unique demands of these growing fields and empowering readers to effectively manage data and models in production
Computer Science researchers, software engineers, programmers, and software researchers in academia and industry, including software engineers, software developers, and architects who are interested in developing software that includes best practices for systems hosted in the cloud. The book also caters to developers, researchers, or professionals working with data pipeline management who are looking to incorporate DevOps principles through DataOps for efficient pipeline management and model deployment. Suitable for graduate-level courses on DevOps, cloud infrastructure, and data pipeline management
1. Introduction to DevOps
2. Planning
3. Version Control System
4. Microservices
5. Cloud Computing for DevOps
6. Packaging and Shipping with Containers
7. Containers Orchestration System
8. Continuous Integration, Delivery and Deployment
9. Continuous Testing
10. Monitoring in DevOps
11. Automation
12. Deployment Models
13. DataOps: Data Science Perspective
2. Planning
3. Version Control System
4. Microservices
5. Cloud Computing for DevOps
6. Packaging and Shipping with Containers
7. Containers Orchestration System
8. Continuous Integration, Delivery and Deployment
9. Continuous Testing
10. Monitoring in DevOps
11. Automation
12. Deployment Models
13. DataOps: Data Science Perspective
- Edition: 1
- Latest edition
- Published: April 1, 2026
- Language: English
CD
Chinmaya Kumar Dehury
Chinmaya Kumar Dehury is currently an Assistant Professor of Distributed Systems, member of Mobile & Cloud Lab in the Institute of Computer Science, University of Tartu, Estonia. He received a Ph.D. Degree in the Department of Computer Science and Information Engineering, Chang Gung University, Taiwan. His research interests include scheduling, resource management and fault tolerance problems of Cloud and fog Computing, the application of artificial intelligence in cloud management, edge intelligence, Internet of Things, and data management frameworks. His research results are published by top-tier journals and transactions such as IEEE TCC, JSAC, TPDS, FGCS, etc. He is a member of IEEE and ACM India. He is also serving as a PC member of several conferences and reviewer to several journals and conferences, such as IEEE TPDS, IEEE JSAC, IEEE TCC, IEEE TNNLS, Wiley Software: Practice and Experience, etc. He also has co-authored 5 book chapters and edited one book published by Springer.
Affiliations and expertise
Institute of Computer Science, University of Tartu, Tartu, EstoniaSS
Satish Narayana Srirama
Satish Narayana Srirama is a Professor at the School of Computer and Information Sciences, University of Hyderabad, India. He is also a Visiting Professor and the honorary head of the Mobile & Cloud Lab at the Institute of Computer Science, University of Tartu, Estonia, which he led as a Research Professor until June 2020. He received his PhD in computer science from RWTH Aachen University, Germany in 2008. His current research focuses on cloud computing, mobile web services, mobile cloud, Internet of Things, fog computing, migrating scientific computing and enterprise applications to the cloud and large-scale data analytics on the cloud. He is an IEEE Senior Member, an Editor of Wiley Software: Practice and Experience, a 54 year old Journal, was an Associate Editor of IEEE Transactions in Cloud Computing and a program committee member of several international conferences and workshops. Dr. Srirama has co-authored over 200 refereed scientific publications in international conferences and journals. He is also a co-author Mastering of Cloud Computing from Elsevier/Morgan Kaufmann and several other book chapters. In addition, Dr. Srirama has co-edited 3 reference books.
Affiliations and expertise
School of Computer and Information Sciences, University of Hyderabad, India