Cloud Native Software Engineering
July 03, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Brian S. Mitchell
arXiv ID
2307.01045
Category
cs.SE: Software Engineering
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Cloud compute adoption has been growing since its inception in the early 2000's with estimates that the size of this market in terms of worldwide spend will increase from \$700 billion in 2021 to \$1.3 trillion in 2025. While there is a significant research activity in many areas of cloud computing technologies, we see little attention being paid to advancing software engineering practices needed to support the current and next generation of cloud native applications. By cloud native, we mean software that is designed and built specifically for deployment to a modern cloud platform. This paper frames the landscape of Cloud Native Software Engineering from a practitioners standpoint, and identifies several software engineering research opportunities that should be investigated. We cover specific engineering challenges associated with software architectures commonly used in cloud applications along with incremental challenges that are expected with emerging IoT/Edge computing use cases.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted