Results 11 to 20 of about 3,474 (205)
MagicScaler: Uncertainty-Aware, Predictive Autoscaling [PDF]
Predictive autoscaling is a key enabler for optimizing cloud resource allocation in Alibaba Cloud's computing platforms, which dynamically adjust the Elastic Compute Service (ECS) instances based on predicted user demands to ensure Quality of Service (QoS). However, user demands in the cloud are often highly complex,
Pan, Zhicheng +13 more
openaire +4 more sources
ATOM: Model-Driven Autoscaling for Microservices [PDF]
Microservices based architectures are increasingly widespread in the cloud software industry. Still, there is a shortage of auto-scaling methods designed to leverage the unique features of these architectures, such as the ability to independently scale a subset of microservices, as well as the ease of monitoring their state and reciprocal calls.
Alim Ul Gias +2 more
core +4 more sources
The Effects of Autoscaling in Cloud Computing
Web-based firms often rely on cloud-based computational resources to serve customers, but the number of customers they will serve is rarely known at the time of product launch. A recent innovation in cloud computing, known as autoscaling, allows companies to automatically scale their computational load up or down to match customer demand.
Amir Fazli +2 more
openaire +2 more sources
Dynamic Autoscaling and Scheduling in Kubernetes Clusters with LSTM and ILP
Containerized applications provide benefits such as portability, security, and faster deployment, enabling organizations to adapt swiftly to dynamic business needs.
Somashekar Patil +2 more
doaj +2 more sources
Multilayered Autoscaling Performance Evaluation: Can Virtual Machines and Containers Co–Scale? [PDF]
The wide adoption of cloud computing by businesses is due to several reasons, among which the elasticity of the cloud virtual infrastructure is the definite leader.
Podolskiy Vladimir +2 more
doaj +2 more sources
Predicting Failures of Autoscaling Distributed Applications
Predicting failures in production environments allows service providers to activate countermeasures that prevent harming the users of the applications. The most successful approaches predict failures from error states that the current approaches identify from anomalies in time series of fixed sets of KPI values collected at runtime.
Giovanni Denaro +5 more
openaire +3 more sources
Self-aware and self-adaptive autoscaling for cloud based services [PDF]
Modern Internet services are increasingly leveraging on cloud computing for flexible, elastic and on-demand provision. Typically, Quality of Service (QoS) of cloud-based services can be tuned using different underlying cloud configurations and resources,
Chen, Tao
core +6 more sources
Enhancing Cloud Efficiency using Intelligent Autoscaling Algorithms [PDF]
Cloud computing has revolutionized the way data and applications are managed, offering scalable, flexible, and cost-effective solutions. A critical aspect of cloud computing is autoscaling, the ability to dynamically adjust computing resources to match ...
Rahane, Pushkar Deodatta
core +2 more sources
Increased Expression of Desmin and Vimentin Impairs Mitochondrial Function and Reduces Contractility via G0S2 in Bladder Smooth Muscle. [PDF]
Our previous study demonstrated that elevated levels of desmin and vimentin reduce BSM contractility. This study shows that the reduced BSM contractility is associated with mitochondrial impairment. G0/G1 switch gene 2 (G0S2) is upregulated in desmin‐ and vimentin‐overexpressing BSM.
Javed E +21 more
europepmc +2 more sources
Continual Learning in Predictive Autoscaling
Predictive Autoscaling is used to forecast the workloads of servers and prepare the resources in advance to ensure service level objectives (SLOs) in dynamic cloud environments. However, in practice, its prediction task often suffers from performance degradation under abnormal traffics caused by external events (such as sales promotional activities and
Hongyan Hao +9 more
openaire +2 more sources

