{"id":1890,"date":"2018-01-31T16:06:34","date_gmt":"2018-01-31T17:06:34","guid":{"rendered":"http:\/\/sites.uac.pt\/amendes\/?p=1890"},"modified":"2018-01-31T16:06:34","modified_gmt":"2018-01-31T17:06:34","slug":"multivariate-time-series-vms","status":"publish","type":"post","link":"https:\/\/sites.uac.pt\/amendes\/estatistica\/multivariate-time-series-vms\/","title":{"rendered":"How To Use Multivariate Time Series Techniques For Capacity Planning on VMs"},"content":{"rendered":"<div id=\"attachment_1083\" style=\"width: 310px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/how-to-use-multivariate-time-series-techniques-for-capacity\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-1083\" class=\"size-medium wp-image-1083\" src=\"http:\/\/sites.uac.pt\/amendes\/files\/2013\/10\/dataScience-300x54.png\" alt=\"clique na imagem para seguir o link\" width=\"300\" height=\"54\" srcset=\"https:\/\/sites.uac.pt\/amendes\/files\/2013\/10\/dataScience-300x54.png 300w, https:\/\/sites.uac.pt\/amendes\/files\/2013\/10\/dataScience.png 657w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><p id=\"caption-attachment-1083\" class=\"wp-caption-text\">clique na imagem para seguir o link<\/p><\/div>\n<p><span style=\"color: #ff0000\">M\u00e9todos multivariados para s\u00e9ries cronol\u00f3gicas com VMs<\/span><\/p>\n<p dir=\"ltr\"><span style=\"background-color: transparent;border-bottom-color: #454545;border-bottom-style: none;border-bottom-width: 0px;border-left-color: #454545;border-left-style: none;border-left-width: 0px;border-right-color: #454545;border-right-style: none;border-right-width: 0px;border-top-color: #454545;border-top-style: none;border-top-width: 0px;font-size: 15.6px;margin-bottom: 0px;margin-left: 0px;margin-right: 0px;margin-top: 0px;padding-bottom: 0px;padding-left: 0px;padding-right: 0px;padding-top: 0px;vertical-align: baseline\">Capacity planning is an arduous, ongoing task for many operations teams, especially for those who rely on Virtual Machines (VMs) to power their business. At Pivotal, we have developed a data science model capable of forecasting hundreds of thousands of models to automate this task using a multivariate time series approach. Open to reuse for other areas such as industrial equipment or vehicles engines, this technique can be applied broadly to anything where regular monitoring data can be collected.<\/span><\/p>\n<p><span> <\/span><\/p>\n<p><span style=\"background-color: transparent;border-bottom-color: #454545;border-bottom-style: none;border-bottom-width: 0px;border-left-color: #454545;border-left-style: none;border-left-width: 0px;border-right-color: #454545;border-right-style: none;border-right-width: 0px;border-top-color: #454545;border-top-style: none;border-top-width: 0px;font-size: 15.6px;margin-bottom: 0px;margin-left: 0px;margin-right: 0px;margin-top: 0px;padding-bottom: 0px;padding-left: 0px;padding-right: 0px;padding-top: 0px;vertical-align: baseline\"><span style=\"background-color: transparent;border-bottom-color: #454545;border-bottom-style: none;border-bottom-width: 0px;border-left-color: #454545;border-left-style: none;border-left-width: 0px;border-right-color: #454545;border-right-style: none;border-right-width: 0px;border-top-color: #454545;border-top-style: none;border-top-width: 0px;font-size: 15.6px;margin-bottom: 0px;margin-left: 0px;margin-right: 0px;margin-top: 0px;padding-bottom: 0px;padding-left: 0px;padding-right: 0px;padding-top: 0px;vertical-align: baseline\"><br \/>\n<\/span><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>M\u00e9todos multivariados para s\u00e9ries cronol\u00f3gicas com VMs Capacity planning is an arduous, ongoing task for many operations teams, especially for those who rely on Virtual Machines (VMs) to power their business. At Pivotal, we have developed a data science model capable of forecasting hundreds of thousands of models to automate this task using a multivariate [&hellip;]<\/p>\n","protected":false},"author":159,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[103,102,109,105],"tags":[191,120],"class_list":["post-1890","post","type-post","status-publish","format-standard","hentry","category-data-mining","category-estatistica","category-investigacao-operacional","category-materiais-ensino","tag-machine-learning","tag-previsao"],"_links":{"self":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1890","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/users\/159"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/comments?post=1890"}],"version-history":[{"count":2,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1890\/revisions"}],"predecessor-version":[{"id":1892,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1890\/revisions\/1892"}],"wp:attachment":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/media?parent=1890"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/categories?post=1890"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/tags?post=1890"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}