Latency-aware failover strategies for containerized web applications in distributed clouds

Aldwyan, Yasser; Sinnott, Richard

doi:10.1016/j.future.2019.07.032

Cited by 18 publications

(13 citation statements)

References 11 publications

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Section: Related Workmentioning

confidence: 99%

“…In the distributed Cloud context, a body of work has been proposed considering proximity to users, for example, Reference 11,45,46, inter‐data center latency issues, for example, References 47 or both 12,25,48. Work has explored place virtual desktops 45 and service‐oriented solutions, 46,48 web solutions 11,12,25 or diverse 47 applications across data centers. Works have explored either a static 12,47 or dynamic 11,25,45,48 deployments using VMs 11,25,45‐48 or containers 12 to achieve inter‐data center strong data consistency and performance 25 .…”

Section: Related Workmentioning

confidence: 99%

“…Work has explored place virtual desktops 45 and service‐oriented solutions, 46,48 web solutions 11,12,25 or diverse 47 applications across data centers. Works have explored either a static 12,47 or dynamic 11,25,45,48 deployments using VMs 11,25,45‐48 or containers 12 to achieve inter‐data center strong data consistency and performance 25 . Other works have considered high availability and performance even after complete or partial Cloud outages 12 factoring in budget and performance issues 46 or performance issues alone, for example, References 11,45,47,48.…”

Section: Related Workmentioning

confidence: 99%

“…However the resources that deliver this platform may be deployed in distant Cloud data centers. Geographical distance typically increases network latency, 11‐13 which ultimately has negative impacts on businesses with poor user experience resulting in lost revenues 14 and on given service level objectives (SLOs) that have been set. Such increased latencies incur delays in the response times of user requests that are often unacceptable for zero‐tolerance‐to‐delay web applications, for example, e‐commerce web sites.…”

Section: Introductionmentioning

confidence: 99%

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Elastic deployment of container clusters across geographically distributed cloud data centers for web applications

Aldwyan

Sinnott

Jayaputera

2021

Concurrency and Computation

Self Cite

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Containers such as Docker provide a lightweight virtualization technology. They have gained popularity in developing, deploying and managing applications in and across Cloud platforms. Container management and orchestration platforms such as Kubernetes run application containers in virtual clusters that abstract the overheads in managing the underlying infrastructures to simplify the deployment of container solutions. These platforms are well suited for modern web applications that can give rise to geographic fluctuations in use based on the location of users. Such fluctuations often require dynamic global deployment solutions. A key issue is to decide how to adapt the number and placement of clusters to maintain performance, whilst incurring minimum operating and adaptation costs. Manual decisions are naive and can give rise to: over‐provisioning and hence cost issues; improper placement and performance issues, and/or unnecessary relocations resulting in adaptation issues. Elastic deployment solutions are essential to support automated and intelligent adaptation of container clusters in geographically distributed Clouds. In this article, we propose an approach that continuously makes elastic deployment plans aimed at optimizing cost and performance, even during adaptation processes, to meet service level objectives (SLOs) at lower costs. Meta‐heuristics are used for cluster placement and adjustment. We conduct experiments on the Australia‐wide National eResearch Collaboration Tools and Resources Research Cloud using Docker and Kubernetes. Results show that with only a 0.5 ms sacrifice in SLO for the 95th percentile of response times we are able to achieve up to 44.44% improvement (reduction) in cost compared to a naive over‐provisioning deployment approach.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Elastic deployment of container clusters across geographically distributed cloud data centers for web applications

Aldwyan

Sinnott

Jayaputera

2021

Concurrency and Computation

Self Cite

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“…Yasser Aldwyan [2] have presented an approach for achieving availability and performance when deploying web applications in distributed Clouds. A genetic algorithm for data center (DC) selection that factors in proximity to users and inter-DC latencies is presented.…”

Section: Literature Reviewmentioning

confidence: 99%

An Incremental Snapshot System using Smart Backup for Persistent Disks in Cloud

Veena¹,

Aravindhar

Sudha³

et al. 2021

Preprint

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Periodical snapshots also called persistent disk snapshots are an essential feature associated with every cloud-hosted virtual instance, which minimizes the risk of unexpected data loss in the server and unavailability issues. The conventional method of creating a snapshot of a production-level server is done by temporarily disabling write access to data during the backup, either by stopping the accessing applications or by using the locking API provided by the operating system to enforce exclusive read access. This is not tolerable for high-availability always-online systems, in which service stoppages are not bearable. In order to solve this downtime issue in high-availability systems, the backup can be performed in a smarter way as incremental snapshots in which a read-only copy of the dataset frozen at a point in time is stored as snapshot by allowing applications to continue processing and writing their data to the instance. Also, incremental snapshots work in a way that only blocks which are different from the former snapshots are processed and stored in the subsequent one.This smart backup will reduce the overall space requirement of the snapshot system by storing only the differences in file storage blocks. Also, when implemented this will save energy and infrastructure requirements of the cloud provider as well as the cost and time of the end-user to create a low- latency server.

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Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design

Vitali

2022

Advanced Information Systems Engineering

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Data centers energy demand is increasing. While a great deal of effort has been made to reduce the amount of CO2 generated by large cloud providers, too little has been done from the application perspective. We claim that application developers can impact the environmental footprint by enhancing the application design with additional features. Following the proposed Sustainable Application Design Process (SADP), the application design is enriched with information that can be leveraged by cloud providers to manage application execution in an energyaware manner. This exploratory work aims to emphasize the awareness on the sustainability of applications by proposing a methodology for its evaluation. To this end, we first suggest possible actions to enrich the application design towards sustainability, and finally describe how this additional information can be leveraged in the application workflow. We discuss the feasibility of our methodology by referring to existing tools and technologies capable of supporting the design features proposed in a production environment.

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Latency-aware failover strategies for containerized web applications in distributed clouds

Cited by 18 publications

References 11 publications

Elastic deployment of container clusters across geographically distributed cloud data centers for web applications

Elastic deployment of container clusters across geographically distributed cloud data centers for web applications

An Incremental Snapshot System using Smart Backup for Persistent Disks in Cloud

Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design

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