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    Obscured by the cloud: A resource allocation framework to model cloud outage events

    Dunne, Jonathan and Malone, David (2017) Obscured by the cloud: A resource allocation framework to model cloud outage events. Journal of Systems and Software, 131. pp. 218-229. ISSN 0164-1212

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    As Small Medium Enterprises (SMEs) adopt Cloud technologies to provide high value customer offerings, uptime is considered important. Cloud outages represent a challenge to SMEs and micro teams to maintain a services platform. If a Cloud platform suffers from downtime this can have a negative effect on business revenue. Additionally, outages can divert resources from product development/delivery tasks to reactive remediation. These challenges are immediate for SMEs or micro teams with a small levels of resources. In this paper we present a framework that can model the arrival of Cloud outage events. This framework can be used by DevOps teams to manage their scarce pool of resources to resolve outages, thereby minimising impact to service delivery. We analysed over 300 Cloud outage events from an enterprise data set. We modelled the inter-arrival and service times of each outage event and found a Pareto and a lognormal distribution to be a suitable fit. We used this result to produce a special case of the G/G/1 queue system to predict busy times of DevOps personnel. We also investigated dependence between overlapping outage events. Our predictive queuing model compared favourably with observed data, 72% precision was achieved using one million simulations.

    Item Type: Article
    Keywords: Outage simulation; Resource allocation model; Queuing theory; Cloud computing;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 11643
    Identification Number:
    Depositing User: Dr. David Malone
    Date Deposited: 05 Nov 2019 17:16
    Journal or Publication Title: Journal of Systems and Software
    Publisher: Elsevier
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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