Effective priority|based resource allocation for proactive auto|scaling ...

Proactive Auto-Scaling Algorithm PASA for Cloud Application

However, variation in the arrival rate of user application requests on the one hand, and the attractive cloud resource auto-scaling feature on the other hand, ...

[PDF] Proactive Container Auto-scaling for Cloud Native Machine ...

This work uses a time-window MultiLayer Perceptron (MLP) to predict phases in containers with different types of workload and proposes a predictive vertical ...

RLPAS: Reinforcement Learning-based Proactive Auto-Scaler for ...

Automated resource provisioning is an effective methodology for handling workload fluctuations by provisioning the resources on demand. Simple reactive ...

Efficient resource provisioning for elastic Cloud services based on ...

Cloud providers often implement elasticity by using auto-scaling techniques [5]. These make automated scaling decisions based on the value of ...

Cushion: A proactive resource provisioning method to mitigate SLO ...

Autoscaling methods of cloud vendors are used to provide dynamic resource provisioning for applications in containerized clusters. They add the ...

A proactive resource allocation method based on adaptive ...

An effective cloud resource allocation method should meet the following conditions for such requests. First, a large number of sudden resource ...

efficient resource management in cloud environment - arXiv

... auto-adapt based on variable resource demands by efficiently using ... A proactive autoscaling and energy-efficient vm allocation framework.

Cluster Autoscaler Vs Karpenter: The Essential Guide - nOps

When it comes to resource management and autoscaling in Kubernetes, you have two main options: Cluster Autoscaler or Karpenter.

CRAMP: Cost-efficient Resource Allocation for Multiple web ... - CoLab

This paper presents a prediction-based dynamic resource allocation ... efficient Resource Allocation for Multiple web applications with Proactive scaling).

Budgeting Strategies For AI Services | Restackio

Reactive auto-scaling is a crucial strategy for optimizing resource allocation in cloud-based AI systems. By continuously monitoring system ...

A proactive energy-aware auto-scaling solution for edge-based ...

The reason is that, unlike cloud servers, edge servers have limited computing resources due to their size and power constraints, making efficient resource ...

The Ultimate Guide to Mastering Resource Management and ...

Resource management and capacity planning within the business realm present various challenges, including the efficient allocation of resources, ...

Proactive Measures to Prevent Overbilling in Cloud-based Services

It is crucial to analyze workload demands accurately and select the appropriate instance types that align with performance and resource needs.

Proactive auto-scaling techniques for containerised applications

... Based Auto-Scaling EBAS, which is powered by a novel time-series-based hybrid prediction ... efficient management of CPU resources in cloud data centres.

Proactive auto-scaling techniques for containerised applications

Thus, our proposed techniques show great promise in terms of practical implementation for the efficient management of CPU resources in cloud ...

Proactive Automated Dependable Resource Management in Cloud ...

of fully automated and highly efficient scaling processes, and more ... with cloud scaling algorithms based on utilization values. REFERENCES. [1] M ...

ScaleOps Platform: Optimize Kubernetes Resource Management

Zero onboarding time using context-aware and automatic policy detection – Out-of-the-box policies and automatic policy selection for any workload, including ...

Universal, proactive, and dynamic scaling of computing resources

A proactive autoscaling system can use heuristics and machine learning to proactively, dynamically and automatically scale computing resources allocated to ...

Reducing Infra costs with time-based scaling for Kubernetes - Devtron

Proactive Planning: Time-based auto-scaling enables you to anticipate resource needs based on historical patterns. This proactive planning allows you to ...

Graph-PHPA: Graph-based Proactive Horizontal Pod Autoscaling for ...

To address this challenge, we propose Graph-PHPA, a graph-based proactive horizontal pod autoscaling strategy for allocating cloud resources to microservices ...