Self-Awareness of Cloud Applications
Alexandru Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina, Maggio, Simon Spinner, Tarek Abdelzaher, Ole Mengshoel, Sara Bouchenak

TL;DR
This paper presents a framework for analyzing self-awareness approaches in cloud applications, comparing their practical characteristics, and outlining future research directions to enhance cloud management and scheduling.
Contribution
It introduces a conceptual framework for evaluating self-awareness methods in cloud applications and provides a comparative analysis of their practical use and challenges.
Findings
Self-awareness approaches vary across application domains.
The framework highlights benefits and drawbacks of different methods.
A roadmap for future research addresses open challenges.
Abstract
Cloud applications today deliver an increasingly larger portion of the Information and Communication Technology (ICT) services. To address the scale, growth, and reliability of cloud applications, self-aware management and scheduling are becoming commonplace. How are they used in practice? In this chapter, we propose a conceptual framework for analyzing state-of-the-art self-awareness approaches used in the context of cloud applications. We map important applications corresponding to popular and emerging application domains to this conceptual framework, and compare the practical characteristics, benefits, and drawbacks of self-awareness approaches. Last, we propose a roadmap for addressing open challenges in self-aware cloud and datacenter applications.
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Taxonomy
TopicsCloud Computing and Resource Management · Software System Performance and Reliability · IoT and Edge/Fog Computing
