A multidimensional model for monitoring cloud services

The complexity of monitoring cloud environments and the lack of standards so far urge for a careful analysis, systematizing and understanding of key points involved when assessing the services provided. In this context, this paper proposes a layered model for Cloud Services monitoring, identifying the multiple dimensions of monitoring, while combining the perspectives of service providers and customers. This process involves the identification of relevant parameters and metrics for each monitoring dimension, focusing on monitoring of resources, quality of service, security and service contracts. Taking a stratified view of the problem, this study contributes to achieve a clearer and more efficient approach to cloud services monitoring.Fundação para a Ciência e a Tecnologia (FCT

Enhanced IPFIX flow processing mechanism for overlay network monitoring

Cloud computing is an emerging technology. People are adopting cloud at a faster rate, due to this cloud network traffic is increasing at a pace which is challenging to manage. Monitoring tool is an essential aspect of cloud computing and becomes more apparent with the acquired of cloud services. Overlay network provides new path to converge network and run as an independent virtual network on top of physical network. Currently, cloud overlay network technologies in cloud infrastructure have visibility gaps, which mean cloud provider and consumers miss out the major performance issues for troubleshooting of overlay network traffic. Hence, to keep a close watch on network and catch potential problems, a network monitoring tool required, to track and report more in-depth for not only see the hidden traffic but also presents the related information of cloud overlay network technologies specifically suited to the modern cloud-scale data center. Therefore, this study proposes an enhanced IP Flow Information Export (IPFIX) mechanism for cloud overlay network monitoring by adopting flexible flow based technique. Furthermore, the solution provided in this research consist of diverse mechanisms: enhanced packet filtering mechanisms using property match filtering technique and hash-based filtering technique. Virtual Extensible Local Area Network (VXLAN) based flow classification mechanisms using 6-tuple flow pattern and adoptable flow patterns. IPFIX message template mechanisms, which is comprise set of fields for data records within the IPFIX flow processing system. The findings demonstrate that the proposed mechanism can capture multi-tenant overlay network traffic to identify, track, analyze and continuously monitor the performance of cloud overlay network services. The proposed mechanisms are resource efficient where the combination of VFMFM+6tuple+VXLAN Message consume 4.63% less CPU, while the combination of VHFM+AFCM+AFCM Message consume 11.45% less CPU than Standard IPFIX. The contributions of this study would help cloud network operators and end-users to quickly and proactively resolve any overlay network based on performance issues with end-to end visibility and actionable insights

A Virtual-Machines-MIB

Resumo: Este trabalho apresenta a Virtual-Machines-MIB, uma MIB para a gerˆencia de m´aquinas virtuais baseada no Simple Network Management Protocol (SNMP). A Virtual-Machines- MIB define uma interface padronizada para a gerˆencia de m´aquinas virtuais, permitindo que a mesma ferramenta possa gerenciar, atrav´es do protocolo SNMP, diferentes monitores de m´aquinas virtuais, como KVM, Xen e VMWare. Diferente da maior parte das MIB's existentes, a Virtual-Machines-MIB permite ao gerente n˜ao apenas monitorar aspectos da m´aquina f´?sica e das VM's, mas tamb´em executar a?c˜oes de controle, como criar, excluir, reiniciar, ligar, desligar e congelar VM's. Tamb´em ´e poss´?vel alterar o nome, a quantidade de mem´oria RAM e de CPU's das VM's, al´em de alterar as unidades de armazenamento das mesmas. Resultados pr´aticos s˜ao apresentados utilizando ferramentas de gerˆencia SNMP comuns para gerenciar diferentes monitores de m´aquinas virtuais. Para isso, foram criados agentes SNMP que oferecem suporte `a Virtual-Machines-MIB e instalados em m´aquinas com o KVM e o Xen. Os agentes foram criados com base no agente SNMP de dom´?nio p´ublico NET-SNMP, que foi estendido para que passe a oferecer suporte `a Virtual-Machines-MIB utilizando as fun?c˜oes da libvirt

Cross-layer multi-cloud real-time application QoS monitoring and benchmarking as-a-service framework

Cloud computing provides on-demand access to affordable hardware (e.g., multi-core CPUs, GPUs, disks, and networking equipment) and software (e.g., databases, application servers and data processing frameworks) platforms with features such as elasticity, pay-per-use, low upfront investment and low time to market. This has led to the proliferation of business criti-cal applications that leverage various cloud platforms. Such applications hosted on sin-gle/multiple cloud platforms have diverse characteristics requiring extensive monitoring and benchmarking mechanisms to ensure run-time Quality of Service (QoS) (e.g., latency and throughput). The process of monitoring and benchmarking cloud applications is as yet a criti-cal issue to be further studied and addressed. Current monitoring and benchmarking approaches do not provide a holistic view of per-formance QoS for distributed applications cross cloud layers on multi-cloud environments. Furthermore, current monitoring frameworks are limited to monitoring tasks and do not in-corporate benchmarking abilities. In other words, there is no unified framework that com-bines monitoring and benchmarking functionalities. To gain the ability of both monitoring and benchmarking all under one framework will empower the cloud user to gain more in-depth control and awareness of cloud services. The Thesis identifies and discusses the major research dimensions and design issues relat-ed to developing techniques that can monitor and benchmark an application’s components cross-layers on multi-clouds. Furthermore, the thesis discusses to what extent such research dimensions and design issues are handled by current academic research papers as well as by the existing commercial monitoring tools. Moreover, the Thesis addresses an important research challenge of how to undertake cross-layer cloud monitoring and benchmarking in multi-cloud environments to provide es-sential information for effective cloud applications QoS management. It proposes, develops, implements and validates CLAMBS: Cross-Layer Multi-Cloud Application Monitoring and Benchmarking, as-a-Service Framework. The core contributions made by this thesis are the development of the CLAMBS framework and underlying monitoring and benchmarking tech-niques which are capable of: i) performing QoS monitoring of application components (e.g. ii database, web server, application server, etc.) that may be deployed across multiple cloud platforms (e.g. Amazon EC2, and Microsoft Azure); and ii) giving visibility into the QoS of in-dividual application components, which is not supported by current monitoring and bench-marking frameworks. Experiments are conducted on real-world multi-cloud platforms to em-pirically evaluate the framework and the results validate that CLAMBS can effectively monitor and benchmark applications running cross-layers on multi-clouds. The thesis presents implementation and evaluation details of the proposed CLAMBS framework. It demonstrates the feasibility and scalability of the proposed framework in real-world environments by implementing a proof-of-concept prototype on multi-cloud platforms. Finally, it presents a model for analysing the communication overheads introduced by various components (e.g. agents and manager) of CLAMBS in multi cloud environments