Authors:
Mauro Andreolini
;
Marcello Pietri
;
Stefania Tosi
and
Andrea Balboni
Affiliation:
University of Modena and Reggio Emilia, Italy
Keyword(s):
Monitoring Architecture, Cloud Computing, Large-scale, Scalability, Multi-tenancy.
Related
Ontology
Subjects/Areas/Topics:
Big Data Cloud Services
;
Cloud Applications Performance and Monitoring
;
Cloud Computing
;
Cloud Computing Architecture
;
Cloud Computing Enabling Technology
;
Fundamentals
;
Monitoring of Services, Quality of Service, Service Level Agreements
;
Platforms and Applications
Abstract:
Large scale cloud-based services are built upon a multitude of hardware and software resources, disseminated in one or multiple data centers. Controlling and managing these resources requires the integration of several pieces of software that may yield a representative view of the data center status. Today’s both closed and open-source monitoring solutions fail in different ways, including the lack of scalability, scarce representativity of global state conditions, inability in guaranteeing persistence in service delivery, and the impossibility of monitoring multi-tenant applications. In this paper, we present a novel monitoring architecture that addresses the aforementioned issues. It integrates a hierarchical scheme to monitor the resources in a cluster with a distributed hash table (DHT) to broadcast system state information among different monitors. This architecture strives to obtain high scalability, effectiveness and resilience, as well as the possibility of monitoring
service
s spanning across different clusters or even different data centers of the cloud provider. We evaluate the scalability of the proposed architecture through a bottleneck analysis achieved by experimental results.
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