Orthosis 发表于 2025-3-21 16:12:03
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Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applils 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.Itinerant 发表于 2025-3-22 07:13:26
RECAP Data Acquisition and Analytics Methodology,chine learning models from this data. These models are then used to identify relevant features and forecast future values, and thus inform run-time planning, decision making, and optimisation support at both the infrastructure and application levels. We conclude the chapter with an overview of RECAP data visualisation approaches.分开如此和谐 发表于 2025-3-22 08:47:03
Towards an Architecture for Reliable Capacity Provisioning for Distributed Clouds,s. 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.stratum-corneum 发表于 2025-3-22 13:11:26
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RECAP Data Acquisition and Analytics Methodology,nfrastructure for the acquisition and processing of data from applications and systems, and explains the methodology used to derive statistical and machine learning models from this data. These models are then used to identify relevant features and forecast future values, and thus inform run-time pl态度暖昧 发表于 2025-3-23 05:10:27
Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Appliinfrastructure 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 propaHARP 发表于 2025-3-23 08:30:07
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