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|Title=A Configuration Crawler for Virtual Appliances in Compute Clouds | |Title=A Configuration Crawler for Virtual Appliances in Compute Clouds | ||
|Year=2013 | |Year=2013 | ||
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data of virtual machine images in public compute clouds and | data of virtual machine images in public compute clouds and | ||
evaluated our approach by crawling Amazon EC2. | evaluated our approach by crawling Amazon EC2. | ||
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|Link=http://www.engineering.leeds.ac.uk/computing/conferences/IC2E2013/ | |Link=http://www.engineering.leeds.ac.uk/computing/conferences/IC2E2013/ | ||
|Forschungsgruppe=Ökonomie und Technologie der eOrganisation | |Forschungsgruppe=Ökonomie und Technologie der eOrganisation | ||
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Aktuelle Version vom 19. Dezember 2012, 16:30 Uhr
A Configuration Crawler for Virtual Appliances in Compute Clouds
A Configuration Crawler for Virtual Appliances in Compute Clouds
Published: 2013
März
Buchtitel: International Conference on Cloud Engineering (IC2E) 2013
Seiten: 9
Verlag: IEEE Computer Society
Referierte Veröffentlichung
BibTeX
Kurzfassung
Compute clouds are pools of virtual machines
that are shared in a multi-tenant environment by multiple
users. The virtual machine images are stored in one or more
repositories and are pre-configured with an operating system.
Users of the compute cloud can upload their own images or
install and configure additional software on top of existing
basic virtual machines. Today, the Amazon Elastic Compute
Cloud (EC2) counts more than 35,000 publicly available virtual
machine images. We observe, however, that the meta-data that
describes the virtual machine images is of poor quality and does
not cover vital information such as operating system configurations
or software package installations. The sprawl of poorly
documented virtual machine images poses a hurdle to sharing
and re-use among members of the compute cloud community.
We present a method that allows collecting software-related
meta-data in compute clouds through appliance introspection.
Moreover, we show how applications in the domains of selection
and configuration management benefit from rich meta-data and
interact with the method. The method has been implemented
as an automated tool, the crawler, that collects configuration
data of virtual machine images in public compute clouds and
evaluated our approach by crawling Amazon EC2.
Download: Media:IC2E.pdf
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Ökonomie und Technologie der eOrganisation