Results 11 to 20 of about 2,745 (218)

Time series forecasting-based Kubernetes autoscaling using Facebook Prophet and Long Short-Term Memory

Frontiers in Computer Science
The advancement of cloud computing technologies has led to increased usage in application deployment in recent years. Kubernetes, a widely used container orchestration platform for deploying applications on cloud systems, provides benefits such as ...
Pasan Bhanu Guruge, Y.H.P.P. Priyadarshana   +1 more
exaly   +3 more sources

Predicting Failures of Autoscaling Distributed Applications [PDF]

Proceedings of the ACM on Software Engineering
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, Noura El Moussa, Rahim Heydarov, Francesco Lomio, Mauro Pezzè, Ketai Qiu   +5 more
openaire   +2 more sources

Distributed Resource Autoscaling in Kubernetes Edge Clusters [PDF]

2022 18th International Conference on Network and Service Management (CNSM), 2022
Maximizing the performance of modern applications requires timely resource management of the virtualized resources. However, proactively deploying resources for meeting specific application requirements subject to a dynamic workload profile of incoming requests is extremely challenging.
Dimitrios Spatharakis, Ioannis Dimolitsas, Eleftherios E. Vlahakis, Dimitrios Dechouniotis, Nikolaos Athanasopoulos, Symeon Papavassiliou   +5 more
openaire   +4 more sources

Evaluation of explainability in autoscaling frameworks [PDF]

, 2022
Mit der Einführung von Container- und Microservice-basierten Software-Architekturen steigt die Arbeitsbelastung von Betreibern bei der Überwachung und Verwaltung dieser Systeme. Um mit der Komplexität dieser Software-Architekturen Schritt halten zu können, benötigen die Betreiber nun immer mehr Software-Unterstützung.
Zilch, Markus
openaire   +5 more sources

Proactive Random-Forest Autoscaler for Microservice Resource Allocation

IEEE Access, 2023
Cloud service providers have been shifting their workloads to microservices to take advantage of their modularity, flexibility, agility, and scalability. However, numerous obstacles remain to achieving the most out of microservice deployments, especially
Lamees M. Al Qassem, Thanos Stouraitis, Ernesto Damiani, Ibrahim Abe M. Elfadel   +3 more
doaj   +1 more source

Continual Learning in Predictive Autoscaling

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
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, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Y. Zhang, Wei Jiang, Siqiao Xue, Jun Zhou   +9 more
openaire   +2 more sources

Online Workload Burst Detection for Efficient Predictive Autoscaling of Applications

IEEE Access, 2020
Autoscaling methods are employed to ensure the scalability of cloud-hosted applications. The public-facing applications are prone to receive sudden workload bursts, and the existing autoscaling methods do not handle the bursty workloads gracefully. It is
Fatima Tahir, Muhammad Abdullah, Faisal Bukhari, Khaled Mohamad Almustafa, Waheed Iqbal   +4 more
doaj   +1 more source

Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure

IEEE Access, 2022
Container-based Internet of Things (IoT) applications in an edge computing environment require autoscaling to dynamically adapt to fluctuations in IoT device requests.
Le Hoang Phuc, Linh-An Phan, Taehong Kim
doaj   +1 more source

EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX

Applied Sciences, 2021
With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices.
Seunghwan Lee, Linh-An Phan, Dae-Heon Park, Sehan Kim, Taehong Kim   +4 more
doaj   +1 more source

Autopilot [PDF]

Proceedings of the Fifteenth European Conference on Computer Systems, 2020
In many public and private Cloud systems, users need to specify a limit for the amount of resources (CPU cores and RAM) to provision for their workloads. A job that exceeds its limits might be throttled or killed, resulting in delaying or dropping end-user requests, so human operators naturally err on the side of caution and request a larger limit than
Krzysztof Rzadca, Pawel Findeisen, Jacek Swiderski, Przemyslaw Zych, Przemyslaw Broniek, Jarek Kusmierek, Pawel Nowak, Beata Strack, Piotr Witusowski, Steven Hand 0001, John Wilkes   +10 more
openaire   +2 more sources