Predictive Autoscaling for Containerized Applications Using ...

This research paper proposes a Predictive Auto-scaling framework leveraging machine-learning(ML) techniques to anticipate and proactively adjust the resources ...

Predictive Hybrid Autoscaling for Containerized Applications

Abstract: One of the main challenges in deploying container service is providing the scalability to satisfy the service performance and ...

(PDF) Predictive Hybrid Autoscaling for Containerized Applications

This paper proposes a hybrid autoscaling method with burst awareness for containerized applications. This new approach considers a combination ...

Auto Scaling and Monitoring of Containerized Applications with High ...

Auto-scaling in Kubernetes · It looks at how much CPU and memory your application is using. · Instead of adding or removing copies of your ...

Burst-Aware Predictive Autoscaling for Containerized Microservices

Autoscaling methods are used for cloud-hosted applications to dynamically scale the allocated resources for guaranteeing Quality-of-Service (QoS).

Predictive autoscaling - enhanced forecasting for cloud workloads

Elastigroup predictive autoscaling uses a machine learning algorithm to accurately predict the CPU utilization pattern of your workloads and increase the ...

Burst-Aware Predictive Autoscaling for Containerized Microservices

Abstract—Autoscaling methods are used for cloud-hosted applications to dynamically scale the allocated resources for guaranteeing Quality- of-Service (QoS).

A Guide to AI-Powered Kubernetes Autoscaling - overcast blog

Predictive Scaling. One of the most significant advantages of AI-powered autoscaling is its predictive scaling feature. · Cost Optimization.

KEDA | Introducing PredictKube - an AI-based predictive autoscaler ...

The predictive autoscaling process is possible thanks to an AI model that observes the requests-per-second (RPS) or CPU values for a period of ...

PASS: Predictive Auto-Scaling System for Large-scale Enterprise ...

We confront two challenges in the management of a vast and diverse array of online web applications deployed on enterprise-grade ...

Proactive auto-scaling technique for web applications in container ...

Proactive auto-scaling techniques in Kubernetes improve utilization by allocating resources based on future workload prediction. However, prediction models run ...

(PDF) SBPAM: Secure Based Predictive Autoscaling Model For ...

Kubernetes Autoscaling Mechanism for Integration into Cloud Services to Achieve Cost Efficiency Organizations have turned towards containerized applications and ...

Scaling based on predictions - Compute Engine - Google Cloud

You can use predictive autoscaling to improve response times for applications with long initialization times and whose workloads vary predictably with daily or ...

Joint Autoscaling of Containers and Virtual Machines for Cost ...

Autoscaling enables container cluster orchestrators to automatically adjust computational resources, such as containers and Virtual Machines ...

Machine learning-based auto-scaling for containerized applications

However, container-based cloud applications require sophisticated auto-scaling methods that automatically and in a timely manner provision and de-provision ...

Predictive Autoscaling in Kubernetes with Keda and Prophet - Medium

Kubernetes, the de facto standard for container orchestration, offers robust autoscaling capabilities to help applications handle varying loads.

Auto-Scaling Containerized Applications in Geo-Distributed Clouds

To guarantee the application performance in terms of the average response time of global user requests container scaling must work effectively across geo- ...

Efficient evolutionary optimization using predictive auto-scaling in ...

With all that being said, the auto-scaler in compliance with the distributed evolutionary optimization in the container-based cloud environment should meet ...

I Fixed Kubernetes Autoscaling using Machine Learning - YouTube

Explore how you can predictively scale your workloads to reduce downtime. The primary way of autoscaling microservices in Kubernetes is by ...

Burst-Aware Predictive Autoscaling for Containerized Microservices

This article proposes a novel burst-aware autoscaling method which detects burst in dynamic workloads using workload forecasting, resource prediction, ...