Multi-layered Monitoring and Adaptation

Guinea, Sam; Kecskeméti, Gábor; Marconi, Annapaola; Wetzstein, Branimir

doi:10.1007/978-3-642-25535-9_24

Cited by 45 publications

(31 citation statements)

References 12 publications

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“…Customization of service-based systems monitoring infrastructure is also considered in [13,18], where different components can be optimally selected to monitor the terms of SLAs, or in [24], where monitoring components at different architectural levels can be combined to provide an integrated monitoring facility to external client. In these works, customization is not considered at the fine-grained level considered in this paper.…”

Section: Related Workmentioning

confidence: 99%

Patterns and tools for business process monitoring customization

Comuzzi

Angelov

2015

SOCA

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In a cross-organizational service-based process provisioning scenario, one provider is likely to execute a given business process to serve several customers. Each customer may hold different expectations about the way this process can be monitored. We present a solution allowing the provider to support the requirements of different customers on the monitoring of a given process, i.e., offering them the opportunity to customize the way a process will be monitored. We propose a multi-dimensional classification model of patterns for process monitoring and rules to compose the patterns to design customized monitoring infrastructures. The fit for purpose of the patterns is evaluated empirically, whereas the feasibility of our solution is demonstrated by a tool supporting process monitoring customization adhering to our pattern design and composition methodology.

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Section: Related Workmentioning

confidence: 99%

Patterns and tools for business process monitoring customization

Comuzzi

Angelov

2015

SOCA

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“…However, these solutions were mainly developed independently of each other, prior to the emergence of the cloud as mainstream computing paradigm. Thus, the current state-of-the-art neither leverages the capabilities provided by the cloud, nor does it address the coordination of adaptation actions across cloud applications and infrastructure, giving rise to potential conflicts and diminishing service quality [17]. CloudWave will radically improve the state of art by introducing a cloud-ready solution where adaptation is done through real-time effective coordination across all layers of the service delivery environment.…”

Section: A Innovation Pillarsmentioning

confidence: 99%

CloudWave: Where adaptive cloud management meets DevOps

Bruneo

Fritz

Keidar-Barner

et al. 2014

2014 IEEE Symposium on Computers and Communications (ISCC)

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The transition to cloud computing offers a large number of benefits, such as lower capital costs and a highly agile environment. Yet, the development of software engineering practices has not kept pace with this change. The design and runtime behavior of cloud based services and the underlying cloud infrastructure are largely decoupled from one another, which limits both the efficiency of the cloud environment and the Quality of Service which can be delivered to the hosted applications. This paper describes the innovative concepts being developed by CloudWave to utilize the principles of DevOps to create an execution analytics cloud infrastructure where, through the use of programmable monitoring and online data abstraction, much more relevant information for the optimization of the ecosystem is obtained. Required optimizations are subsequently negotiated between the applications and the cloud infrastructure to obtain coordinated adaption of the ecosystem. Additionally, the project is developing the technology for a Feedback Driven Development Standard Development Kit which will utilize the data gathered through execution analytics to supply developers with a powerful mechanism to shorten application development cycles. Abstract-The transition to cloud computing offers a large number of benefits, such as lower capital costs and a highly agile environment. Yet, the development of software engineering practices has not kept pace with this change. Moreover, the design and runtime behavior of cloud based services and the underlying cloud infrastructure are largely decoupled from one another.This paper describes the innovative concepts being developed by CloudWave to utilize the principles of DevOps to create an execution analytics cloud infrastructure where, through the use of programmable monitoring and online data abstraction, much more relevant information for the optimization of the ecosystem is obtained. Required optimizations are subsequently negotiated between the applications and the cloud infrastructure to obtain coordinated adaption of the ecosystem. Additionally, the project is developing the technology for a Feedback Driven Development Standard Development Kit which will utilize the data gathered through execution analytics to supply developers with a powerful mechanism to shorten application development cycles.

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“…In the S-Cube project [54], the researchers have proposed several techniques to address monitoring issues. In [24], the authors propose a framework that integrates monitoring across the software and infrastructure layers. A variation of the MAPE control loop is introduced into the framework that acknowledges the multi-faceted nature of SBSs.…”

Section: Related Workmentioning

confidence: 99%

Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

Han

Yang

et al. 2014

IIEEE Trans. Software Eng.

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Abstract-When operating in volatile environments, service-based systems (SBSs) that are dynamically composed from component services must be monitored in order to guarantee timely and successful delivery of outcomes in response to user requests. However, monitoring consumes resources and very often impacts on the quality of the SBSs being monitored. Such resource and system costs need to be considered in formulating monitoring strategies for SBSs. The critical path of a composite SBS, i.e., the execution path in the service composition with the maximum execution time, is of particular importance in cost-effective monitoring as it determines the response time of the entire SBS. In volatile operating environments, the critical path of an SBS is probabilistic, as every execution path can be critical with a certain probability, i.e., its criticality. As such, it is important to estimate the criticalities of different execution paths when deciding which parts of the SBS to monitor. Furthermore, cost-effective monitoring also requires management of the trade-off between the benefit and cost of monitoring. In this paper, we propose CriMon, a novel approach to formulating and evaluating monitoring strategies for SBSs. CriMon first calculates the criticalities of the execution paths and the component services of an SBS and then, based on those criticalities, generates the optimal monitoring strategy considering both the benefit and cost of monitoring. CriMon has two monitoring strategy formulation methods, namely local optimisation and global optimisation. In-lab experimental results demonstrate that the response time of an SBS can be managed cost-effectively through CriMon-based monitoring. The effectiveness and efficiency of the two monitoring strategy formulation methods are also evaluated and compared.

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Multi-layered Monitoring and Adaptation

Cited by 45 publications

References 12 publications

Patterns and tools for business process monitoring customization

Patterns and tools for business process monitoring customization

CloudWave: Where adaptive cloud management meets DevOps

Formulating Cost-Effective Monitoring Strategies for Service-Based Systems

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