Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applications

Östberg, Per-Olov; Le Duc, Thang; Casari, Paolo; García Leiva, Rafael; Fernández Anta, Antonio

doi:https://doi.org/10.1007/978-3-030-39863-7_3#ESM

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Chapter_Application_Optimisation_Workload_Prediction_2020_EN.pdf (374.3Kb)

Identifiers

URI: http://hdl.handle.net/20.500.12761/882

ISBN: 978-3-030-39862-0

DOI: https://doi.org/10.1007/978-3-030-39863-7_3#ESM

Date

2020-07-21

Abstract

Optimisation of (the configuration and deployment of) distributed cloud applications is a complex problem that requires understanding factors such as infrastructure and application topologies, workload arrival and propagation patterns, and the predictability and variations of user behaviour. This chapter outlines the RECAP approach to application optimisation and presents its framework for joint modelling of applications, workloads, and the propagation of workloads in applications and networks. The interaction of the models and algorithms developed is described and presented along with the tools that build on them. Contributions in modelling, characterisation, and autoscaling of applications, as well as prediction and generation of workloads, are presented and discussed in the context of optimisation of distributed cloud applications operating in complex heterogeneous resource environments.