
Mastering Devops
A Cloud Engineering and Data Science Perspective
Morgan Kaufmann (Publisher)
Will be published approx. on 1. April 2026
Book
Paperback/Softback
250 pages
978-0-443-45032-7 (ISBN)
Description
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. Content 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.
Specific topics cover fundamental principles, including history, planning, and essential tools like Git, introduce the core technologies and architectures that power modern DevOps, such as microservices, cloud computing, and containerization, and focus on the practical implementation of DevOps, exploring key practices like continuous integration, automation, and monitoring. Finally, the book 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.
Specific topics cover fundamental principles, including history, planning, and essential tools like Git, introduce the core technologies and architectures that power modern DevOps, such as microservices, cloud computing, and containerization, and focus on the practical implementation of DevOps, exploring key practices like continuous integration, automation, and monitoring. Finally, the book 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.
More details
Language
English
Place of publication
Burlington, Massachusetts
United States
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 276 mm
Width: 216 mm
Weight
450 gr
ISBN-13
978-0-443-45032-7 (9780443450327)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Chinmaya Kumar Dehury | Satish Narayana Srirama
Mastering DevOps
A Cloud Engineering and Data Science Perspective
E-Book
03/2026
Elsevier
€166.99
Available for download
Persons
Chinmaya Kumar Dehury is currently an Assistant Professor in the Computer Science department, IISER Berhampur, India. He was an Assistant Professor in the Institute of Computer Science, University of Tartu, Estonia. His research interests include scheduling, resource management and fault tolerance problems of Cloud and fog Computing, 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.
Author
Institute of Computer Science University of Tartu Tartu Estonia
School of Computer and Information Sciences University of Hyderabad India
Content
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