DevOps and its Philosophy : Education Matters!
April 04, 2019 ยท Declared Dead ยท ๐ Microservices, Science and Engineering
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Evgeny Bobrov, Antonio Bucchiarone, Alfredo Capozucca, Nicolas Guelfi, Manuel Mazzara, Alexandr Naumchev, Larisa Safina
arXiv ID
1904.02469
Category
cs.SE: Software Engineering
Citations
17
Venue
Microservices, Science and Engineering
Last Checked
3 months ago
Abstract
DevOps processes comply with principles and offer practices with main objective to support efficiently the evolution of IT systems. To be efficient a DevOps process relies on a set of integrated tools. DevOps is the first required competency together with Agile Method required by the industry. DevOps processes are sharing many aspects with microservices approaches especially the modularity and flexibility which enables continuous change and delivery. As a new approach it is necessary to developp and offer to the academy and to the industry training programs to prepare our engineers in the best possible way. In this chapter we present the main aspects of the educational effort made in the recent years to educate to the concepts and values of the DevOps philosophy. This includes principles, practices, tools and architectures, primarily the Microservice architectural style. Two experiences have been made, one at academic level as a master program course and the other, as an industrial training. Based on those two experiences, we provide a comparative analysis and some proposals in order to develop and improve DevOps education for the future.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Software Engineering
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
GraphCodeBERT: Pre-training Code Representations with Data Flow
R.I.P.
๐ป
Ghosted
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars
R.I.P.
๐ป
Ghosted
Microservices: yesterday, today, and tomorrow
R.I.P.
๐ป
Ghosted
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks
R.I.P.
๐ป
Ghosted
A Survey of Machine Learning for Big Code and Naturalness
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted