| 1. |
- Domaschka, Jörg, et al.
(author)
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Towards an Architecture for Reliable Capacity Provisioning for Distributed Clouds
- 2020
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In: Managing Distributed Cloud Applications and Infrastructure. - Cham : Palgrave Macmillan. - 9783030398620 - 9783030398637 ; , s. 1-25
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Book chapter (peer-reviewed)abstract
- The complexity of computing along the cloud-to-edge continuum presents significant challenges to ICT operations and in particular reliable capacity planning and resource provisioning to meet unpredictable, fluctuating, and mobile demand. This chapter presents a high-level conceptual overview of RECAP—an architectural innovation to support reliable capacity provisioning for distributed clouds—and its operational modes and functional building blocks. In addition, the major design concepts informing its design—namely separation of concerns, model-centricism, modular design, and machine learning and artificial intelligence for IT operations—are also discussed.
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| 2. |
- Östberg, Per-Olov, et al.
(author)
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Application Optimisation : Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applications
- 2020
-
In: Managing Distributed Cloud Applications and Infrastructure. - Cham : Palgrave Macmillan. - 9783030398620 - 9783030398637 ; , s. 51-68
-
Book chapter (peer-reviewed)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.
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