{"id":149691,"date":"2004-12-01T00:00:00","date_gmt":"2004-12-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/using-magpie-for-request-extraction-and-workload-modelling\/"},"modified":"2023-08-03T07:38:43","modified_gmt":"2023-08-03T14:38:43","slug":"using-magpie-for-request-extraction-and-workload-modelling","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/using-magpie-for-request-extraction-and-workload-modelling\/","title":{"rendered":"Using Magpie for request extraction and workload modelling"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Tools to understand complex system behaviour are essential for many performance analysis and debugging tasks, yet there are many open research problems in their development. Magpie is a toolchain for automatically extracting a system&#8217;s workload under realistic operating conditions. Using low-overhead instrumentation, we monitor the system to record fine-grained events generated by kernel, middleware and application components. The Magpie request extraction tool uses an application-specific event schema to correlate these events, and hence precisely capture the control flow and resource consumption of each and every request. By removing scheduling artefacts, whilst preserving causal dependencies, we obtain canonical request descriptions from which we can construct concise workload models suitable for performance prediction and change detection. In this paper we describe and evaluate the capability of Magpie to accurately extract requests and construct representative models of system behaviour.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tools to understand complex system behaviour are essential for many performance analysis and debugging tasks, yet there are many open research problems in their development. Magpie is a toolchain for automatically extracting a system&#8217;s workload under realistic operating conditions. Using low-overhead instrumentation, we monitor the system to record fine-grained events generated by kernel, middleware and [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-149691","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"USENIX","msr_edition":"","msr_affiliation":"","msr_published_date":"2004-12-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"209738","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/magpie-osdi.pdf","id":"209738","title":"magpie-osdi.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":209738,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/magpie-osdi.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Paul 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