{"id":1559,"date":"2022-12-07T10:49:48","date_gmt":"2022-12-07T10:49:48","guid":{"rendered":"https:\/\/jbeats4zos.com\/de\/?p=1559"},"modified":"2023-01-11T17:47:36","modified_gmt":"2023-01-11T17:47:36","slug":"kibana-dashboard-system-cpu-usage","status":"publish","type":"post","link":"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/","title":{"rendered":"jBeats Kibana-Dashboard System CPU Nutzung"},"content":{"rendered":"

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jBeats4zos – Kibana Dashboards Teil 1<\/h1>\n

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In diesem und weiteren Posts zeigen wir, wie jBeats-Daten in Kibana Dashboards visualisiert werden.<\/p>\n

In diesem Post besch\u00e4ftigen wir uns mit den g\u00e4ngigen CPU-Systemkennzahlen. Den\u00a0 hier gezeigten Dashboards liegen Daten aus den\u00a0 SMF Datens\u00e4tzen Typ 70 und 72 zugrunde. Der Bericht enth\u00e4lt vorberechnete Metriken<\/a> (z.B. CP und IIP Software MSU), die von jBeats automatisch zur Verf\u00fcgung gestellt werden.<\/p>\n

In weiteren Beitr\u00e4gen dieser Reihe werden\u00a0 wir Dashboards mit Auswertungen vorstellen, die thematisch andere Aspekte des Systems im Fokus haben und auf anderen Satztypen beruhen.<\/p>\n

Grunds\u00e4tzlich k\u00f6nnen alle in jBeats verf\u00fcgbaren Satztypen f\u00fcr die Erstellung von Dashboards herangezogen werden. Auch die Erstellung eigener Dashboards ist problemlos m\u00f6glich!<\/p>\n

Eine vollst\u00e4ngige Liste aller f\u00fcr jBeats4zos verf\u00fcgbaren Satztypen finden Sie hier.<\/a><\/p>\n

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CEC-Total<\/h2>\n

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Die Abbildung oben enth\u00e4lt eine typische Sicht auf die Unternehmens-CECs.
Links oben befindet sich eine Auflistung aller CECs, die Daten an jBeats liefern. Rechts daneben befindet sich eine \u00dcbersicht der zur Verf\u00fcgfung stehenden Kapazit\u00e4ten gruppiert pro CEC.<\/p>\n

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Die unteren H\u00e4lfte des Dashboards zeigt\u00a0 Nutzungsgrafiken der CECs auf Basis System und Prozessortypen (CP, IIP) in Software MSU.
Die Grafiken zeigen die Gesamtauslastung \u00fcber die gew\u00e4hlte Zeitspanne (im Beispiel 6 Tage) gruppiert nach Systemen.
Peaks innerhalb des gew\u00e4hlten Zeitfensters werden sofort sichtbar. Die Visualisierung enth\u00e4lt die M\u00f6glichkeit die Daten durch Drilldown zu detaillieren.<\/p>\n

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Die CEC-Sicht<\/h2>\n

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Der erste Schritt, um ein Problem zu anlysieren ist die Identifizierung des CECs, der Auff\u00e4lligkeiten aufweist.
So ist die dann auch die erste Drilldown-Stufe die Sicht auf einen einzelnen CEC.<\/p>\n

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Die Auswahl des CECs erfolgt durch einfaches anklicken des Namens in der linken oberen Sektion der Gesamtsicht. Zus\u00e4tzlich besteht auch die M\u00f6glichkeit, den Betrachtungszeitraum f\u00fcr eine erste N\u00e4herung zu ver\u00e4ndern.<\/p>\n

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Workloads<\/h2>\n

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Aus der CEC-Sicht kann durch anklicken des gew\u00fcnschten Systems in die Workload-Sicht verzweigt werden. Das Dashboard beinhaltet CPU-Nutzungsdaten innerhalb des gew\u00e4hlten Systems im ausgew\u00e4hlten Zeitraum.\u00a0<\/p>\n

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Auch hier werden die Daten als gestapelte S\u00e4ulen angezeigt um sowohl Gesamtsicht als auch die Nutzung einzelner Workloads darstellen zu k\u00f6nnen.
Die Nutzung auf Ebene Workloads entstammt dem SMF-Satz Typ 72.<\/p>\n

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Serviceklassen<\/h2>\n

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Ausgehend von der Workloadsicht, kann auf die darunter liegenden Serviceklassen verzweigt werden. Die Darstellung beinhaltet auch hier wieder CPU-Nutzung aufgeteilt nach beteiligten Prozessortypen auf Ebene ServicClass.<\/p>\n

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Auf diese Weise kann erkannt werden, welche Serviceklassen die Prozessoren besonders stark nutzen und gegebenenfalls eingegriffen werden, um Ressourcen effizienter einzusetzen.<\/p>\n

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jBeats4zos – Kibana Dashboards Teil 1In diesem und weiteren Posts zeigen wir, wie jBeats-Daten in Kibana Dashboards visualisiert werden. In diesem Post besch\u00e4ftigen wir uns mit den g\u00e4ngigen CPU-Systemkennzahlen. Den\u00a0 hier gezeigten Dashboards liegen Daten aus den\u00a0 SMF Datens\u00e4tzen Typ 70 und 72 zugrunde. Der Bericht enth\u00e4lt vorberechnete Metriken (z.B. CP und IIP Software MSU), […]<\/p>\n","protected":false},"author":1,"featured_media":1734,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[16],"tags":[],"class_list":["post-1559","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-jbeats-dashboards"],"yoast_head":"\njBeats Kibana-Dashboard System CPU Nutzung - jBeats4zOS - Elasticsearch Erweiterung f\u00fcr z\/OS<\/title>\n<meta name=\"description\" content=\"In dieser Blogreihe zeigen anhand konkreter Beispiele, wie Kibana Dashbords auf Grundlage von jBeats Daten aussehen.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"jBeats Kibana-Dashboard System CPU Nutzung - jBeats4zOS - Elasticsearch Erweiterung f\u00fcr z\/OS\" \/>\n<meta property=\"og:description\" content=\"In dieser Blogreihe zeigen anhand konkreter Beispiele, wie Kibana Dashbords auf Grundlage von jBeats Daten aussehen.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\" \/>\n<meta property=\"og:site_name\" content=\"jBeats4zOS - Elasticsearch Erweiterung f\u00fcr z\/OS\" \/>\n<meta property=\"article:published_time\" content=\"2022-12-07T10:49:48+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-01-11T17:47:36+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/jbeats4zos.com\/de\/wp-content\/uploads\/sites\/17\/2022\/12\/Blog1_v4.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Verfasst von\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Gesch\u00e4tzte Lesezeit\" \/>\n\t<meta name=\"twitter:data2\" content=\"4\u00a0Minuten\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\/\/jbeats4zos.com\/de\/#\/schema\/person\/12b0fb24c8e4447fa0f6e922c2e816fb\"},\"headline\":\"jBeats Kibana-Dashboard System CPU Nutzung\",\"datePublished\":\"2022-12-07T10:49:48+00:00\",\"dateModified\":\"2023-01-11T17:47:36+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\"},\"wordCount\":1549,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/jbeats4zos.com\/de\/#organization\"},\"image\":{\"@id\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/jbeats4zos.com\/de\/wp-content\/uploads\/sites\/17\/2022\/12\/Blog1_v4.jpg\",\"articleSection\":[\"jBeats Dashboards\"],\"inLanguage\":\"de\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\",\"url\":\"https:\/\/jbeats4zos.com\/de\/kibana-dashboard-system-cpu-usage\/\",\"name\":\"jBeats Kibana-Dashboard System CPU Nutzung - 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