Towards Cross-Layer Monitoring of Multi-Cloud Service-Based Applications

Zeginis, Chrysostomos; Kritikos, Kyriakos; Garefalakis, Panagiotis; Konsolaki, Konstantina; Magoutis, Kostas; Plexousakis, Dimitris

doi:10.1007/978-3-642-40651-5_16

Cited by 23 publications

(23 citation statements)

References 10 publications

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“…The main non-functional application goal is to capture warning (identified by we) or critical events (identified by ce) and interrelate them to discover event patterns leading to SLO violations. The architecture presented in our previous work [5] for cross-layer multi-cloud SBA monitoring is realized and enhanced with specific techniques and algorithms to support proactive adaptation. In this multi-cloud framework (Fig.…”

Section: Motivating Examplementioning

confidence: 99%

“…In [2] we have investigated the need for cross-layer adaptation, as current techniques are mainly fragmented by considering a single SBA layer, while the few cross-layer ones [3,4] do not consider multi-cloud aspects. Concerning monitoring, in [5] we have presented a multi-cloud SBA framework. This paper goes a step further supporting multicloud SBA adaptation by focusing on an efficient method for processing the huge amount of monitored events and discovering frequent patterns leading to SLO violations.…”

Section: Introductionmentioning

confidence: 99%

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Event Pattern Discovery for Cross-Layer Adaptation of Multi-cloud Applications

Zeginis

Kritikos

Plexousakis

2014

Advanced Information Systems Engineering

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Section: Motivating Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Event Pattern Discovery for Cross-Layer Adaptation of Multi-cloud Applications

Zeginis

Kritikos

Plexousakis

2014

Advanced Information Systems Engineering

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“…Zeginis et al [18] proposed a cloud provider side framework for monitoring the performance of service-based application deployed on multi-clouds. The framework performs monitoring at the IaaS, PaaS and SaaS layers in clouds.…”

Section: B Understanding Multi-cloud Application Behavior Under Denimentioning

confidence: 99%

DoLen: User-Side Multi-cloud Application Monitoring

Quoc

Yazdanov

Fetzer

2014

2014 International Conference on Future Internet of Things and Cloud

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Cloud computing is a popular platform offering computation, storage and communication resources as a service. Monitoring the performance and behavior of multi-cloud applications in a scenario where applications are deployed on multiple cloud providers is a challenge for cloud computing research community. In this paper, we propose a framework that allows monitoring in near real-time resource utilization including CPU, memory, disk activity and network traffic of applications deployed in multiple clouds. We conducted various experiments using a cluster to simulate three clouds, showing the framework's ability to analyze resource consumption of Hadoop applications deployed in clouds in near real-time. We also performed VMto-VM attacks to evaluate anomaly detection capacity of the proposed framework.

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“…The self-adaptation goal is to alleviate the software management efforts in managing highly changing and evolving environments. During run-time, the monitoring component observes the CSBS behavior and detects or predicts any problematic situation such as failures and SLA violations [22]. If a problematic condition is detected, the analysis component analyzes the situation to discover more information such as the impact, or the cause of the failure.…”

Section: Introductionmentioning

confidence: 99%

Towards Self-adaptation Planning for Complex Service-Based Systems

Ismail

Cardellini

2014

Lecture Notes in Computer Science

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Abstract.A complex service-based system (CSBS), which comprises a multi-layer structure possibly spanning multiple organizations, operates in a highly dynamic and heterogeneous environment. At run time the quality of service provided by a CSBS may suddenly change, so that violations of the Service Level Agreements (SLAs) established within and across the boundaries of organizations can occur. Hence, a key management choice is to design the CSBS as a self-adaptive system, so that it can properly plan adaptation decisions to maintain the overall quality defined in the SLAs. However, the challenge in planning the CSBS adaptation is the uncertainty effect of adaptation actions that can variously affect the multiple layers of the CSBS. In a dynamic and constantly evolving environment, there is no guarantee that the adaptation action taken at a given layer can have an overall positive effect. Furthermore, the complexity of the cross-layer interactions makes the decision making process a non-trivial task. In this paper, we address the problem by proposing a multi-layer adaptation planning with local and global adaptation managers. The local manager is associated with a single planning model, while the global manager is associated with a multiple planning model. Both planning models are based on Markov Decision Processes (MDPs) that provide a suitable technique to model decisions under uncertainty. We present an example of scenario to show the practicality of the proposed approach.

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Towards Cross-Layer Monitoring of Multi-Cloud Service-Based Applications

Cited by 23 publications

References 10 publications

Event Pattern Discovery for Cross-Layer Adaptation of Multi-cloud Applications

Event Pattern Discovery for Cross-Layer Adaptation of Multi-cloud Applications

DoLen: User-Side Multi-cloud Application Monitoring

Towards Self-adaptation Planning for Complex Service-Based Systems

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