<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Operational Lessons from Chameleon</dc:title><dc:creator>Keahey, Kate; Anderson, Jason; Ruth, Paul; Colleran, Jacob; Hammock, Cody; Stubbs, Joe; Zhen, Zhuo</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Chameleon is a large-scale, deeply reconfigurable testbed built to support Computer Science experimentation. Unlike traditional systems of this kind, Chameleon has been configured using an adaptation of a mainstream open source infrastructure cloud system called OpenStack. We show that operating cloud systems requires both more skill and extra effort on the part of the operators - in particular where those systems are expected to evolve quickly - which can make systems of this kind expensive to run. We discuss three ways in which those operations costs can be managed: innovative mon- itoring and automation of systems tasks, building “operator co-ops”, and collaborating with users.</dc:description><dc:publisher/><dc:date>2019-01-01</dc:date><dc:nsf_par_id>10107209</dc:nsf_par_id><dc:journal_name>Proceedings of the Humanware Advancing Research in the Cloud</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/</dc:doi><dcq:identifierAwardId>1743358</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>