Metrics

Open-Source-Lösung zur Metrikanalyse

Ob Sensordaten von Drohnen oder Informationen zur CPU-Auslastung, Elasticsearch wendet seit jeher die leistungsstarken Funktionen, die Sie an der Textsuche so schätzen, auch auf Metriken an. Und es wird immer besser.

Entdecken Sie Metrikanalysen mit Elastic. Jetzt ausprobieren

Neu Die Welt der Infrastrukturmetriken bietet eine Menge, das sich zu entdecken lohnt – von der Infrastructure-Benutzeroberfläche und Daten-Rollups bis zu Functionbeat und der zentralen Beats-Verwaltung.

Analysen von Daten aus verschiedenen Quellen an einem Ort

Ob Sie Docker-Container, Rechenzentren, Fahrzeugflotten oder die Temperatur der Marsoberfläche überwachen – es gibt für jeden Einsatzzweck einen Beat, ein Modul oder ein Plugin, mit dem all diese Daten in den Elastic Stack gebracht werden können.

Sie haben gar nicht gewusst, dass eine Suchmaschine alle diese Datenquellen verarbeiten kann? Keine Ursache, gern geschehen …
Hier können Sie direkt loslegen.

Flexible Datenanalyse

Experimentieren Sie mit Dimensionen, Tags, Kardinalität und Feldern. Elastic macht Ihnen keine Vorschriften, wie und in welchem Umfang Sie Ihre Daten analysieren sollen. Im Gegenteil: Sie können kontinuierlich und schnell Attribute (wie Hostname, IP-Adresse, Implementierung oder Farbe) untersuchen – und das in großem Umfang, nach Ihren Anforderungen, in beliebiger Reihenfolge und in der Visualisierung, die Ihnen gefällt. Und Beats und deren Module kümmern sich für Sie um das Sammeln, Parsen und Taggen der entsprechenden Daten. Sie sind auch in der Lage, Dashboards und Machine-Learning-Jobs zu erstellen.

Geschwindigkeit und Skalierbarkeit, die sich bemerkbar machen

Damit das gelingt, sind wir über das Indexieren mittels invertierter Dateien hinausgegangen. Wir haben neue Datentypen entwickelt, BKD-Bäume implementiert und ein Spaltenlayout für die Speicherung hinzugefügt. Das alles resultiert in einer effizienteren Datenstrukturierung für eine schnellere Suche sowie weniger Speichernutzung und eine geringere Datenträgerauslastung. Oder anders formuliert: Sie haben auch bei Petabytes von Daten blitzschnellen Zugriff auf Felder und Werte.

Rollups für einen besseren Überblick über Daten

Sie können sich Zusammenfassungen Ihrer Metriken anzeigen lassen, ohne dafür den Elastic Stack verlassen zu müssen. Die leistungsfähige Unterstützung von Rollups in Elasticsearch und Kibana ermöglicht Platzeinsparungen und schnellere Abfragen ohne Abstriche bei der Genauigkeit.

Jetzt ausprobieren

Mit einer Neuinstallation können Sie direkt loslegen.
  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Metricbeat

Open terminal (varies depending on your client OS) and in the Metricbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

To modify defaults, edit modules.d/system.yml.

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Metricbeat System] Overview"
What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing CPU and memory utilization, and process-level statistics.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Metricbeat

Open terminal (varies depending on your client OS) and in the Metricbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

To modify defaults, edit modules.d/apache.yml.

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Metricbeat Apache] Overview"
What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing connection statistics and HTTP worker details.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Metricbeat

Open terminal (varies depending on your client OS) and in the Metricbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

To modify defaults, edit modules.d/mongodb.yml.

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Metricbeat MongoDB] Overview"
What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing data statistics, health and status information about your MongoDB deployment.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Metricbeat

Open terminal (varies depending on your client OS) and in the Metricbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

To modify defaults, edit modules.d/docker.yml.

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Metricbeat Docker] Overview"
What just happened?
Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing data statistics, health and status information about your Docker deployment.
Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Metricbeat

Open terminal (varies depending on your client OS) and in the Metricbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

From your machine or wherever you run kubectl:

env:
  - name: ELASTIC_CLOUD_ID
    value: <cloud.id>
  - name: ELASTIC_CLOUD_AUTH
    value: elastic:<cloud.auth>
				

Replace <cloud.id> and <cloud.auth> with the values that you saved when you created a deployment in the step “Set up Elastic Cloud”

Optionally, you can enable kube-state-metrics for more detail.

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Metricbeat Kubernetes] Overview"
What just happened?
Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can monitor your Kubernetes cluster.
Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

  • Register, if you do not already have an account. Free 14-day trial available.
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Deployment, and specify the Deployment Name
  • Modify the other deployment options as needed (or not, the defaults are great to get started)
  • Click Create Deployment
  • Save the Cloud ID and the cluster Password for your records, we will refer to these as <cloud.id> and <password> below
  • Wait until deployment creation completes

Download and unpack Heartbeat (Beta)

Open terminal (varies depending on your client OS) and in the Heartbeat install directory, type:

Paste in the <password> for the elastic user when prompted

Paste in the <cloud.id> for the cluster when prompted

Open Kibana from Kibana section of the Elastic Cloud console (login: elastic/<password>)
Open dashboard:
"[Heartbeat] HTTP Monitoring"
What just happened?

Heartbeat is designed to do distributed uptime checks from each of your hosts to ensure that they can each reach every endpoint they are supposed to. This is amazing for service-oriented architectures. In this case, you've asked Heartbeat to check the uptime for the two local ports corresponding to the Elasticsearch and Kibana defaults. Heartbeat then sends this data to Elasticsearch and you can see the data in the Kibana dashboard.

Didn't work for you?

Heartbeat was set to use the default ports for Elasticsearch and Kibana in this example. See the documentation for configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Metricbeat install directory:
Ctrl + C to Copy

To modify defaults, edit modules.d/system.yml.

What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing CPU and memory utilization, and process-level statistics.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Metricbeat install directory:
Ctrl + C to Copy
Ctrl + C to Copy

To modify defaults, edit modules.d/apache.yml.

What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing connection statistics and HTTP worker details.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Metricbeat install directory:
Ctrl + C to Copy
Ctrl + C to Copy

To modify defaults, edit modules.d/mongodb.yml.

What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing data statistics, health and status information about your MongoDB deployment.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Metricbeat install directory:
Ctrl + C to Copy
Ctrl + C to Copy

To modify defaults, edit modules.d/docker.yml.

What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can start viewing data statistics, health and status information about your Docker deployment.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Filebeat install directory:
Ctrl + C to Copy
Ctrl + C to Copy
From your machine or wherever you run kubectl:
  • Download metricbeat-kubernetes.yml
  • Edit metricbeat-kubernetes.yml and specify the host for your Elasticsearch server (If you are connecting back to your host from kubernetes running locally then set ELASTICSEARCH_HOST to host.docker.internal). There is a DaemonSet and a singleton, edit the HOST for both:
  - name: ELASTICSEARCH_HOST
    value: host.docker.internal
			

Optionally, you can enable kube-state-metrics for more detail.

Ctrl + C to Copy
What just happened?

Metricbeat created an index pattern in Kibana with defined fields, searches, visualizations, and dashboards. In a matter of minutes you can monitor your Kubernetes cluster.

Didn't work for you?

Metricbeat modules have defaults and configurations for each system they connect to. See the documentation for supported versions and configuration options.

In Elasticsearch install directory:
Ctrl + C to Copy
In Kibana install directory:
Ctrl + C to Copy
In Heartbeat install directory:
Ctrl + C to Copy
What just happened?

Heartbeat is designed to do distributed uptime checks from each of your hosts to ensure that they can each reach every endpoint they are supposed to. This is amazing for service-oriented architectures. In this case, you've asked Heartbeat to check the uptime for the two local ports corresponding to the Elasticsearch and Kibana defaults. Heartbeat then sends this data to Elasticsearch and you can see the data in the Kibana dashboard.

Didn't work for you?

Heartbeat was set to use the default ports for Elasticsearch and Kibana in this example. See the documentation for configuration options.

Mit Machine-Learning-Jobs Anomalien entdecken

Je mehr Daten verarbeitet werden müssen, desto leichter kann es passieren, dass problematische Datenpunkte unter der Vielzahl an Durchschnittswerten, Messungen und Gesamtwerten übersehen werden. Und es ist nicht praxisgerecht zu verlangen, dass alle Visualisierungen permanent analysiert werden müssen.

Die Machine-Learning-Funktionen im Elastic Stack automatisieren die Erkennung von Anomalien in großem Umfang. Das System lernt, was bei Ihren Daten normal ist, sodass es Sie benachrichtigen kann, wenn die Dinge nicht so laufen, wie sie sollten.

Sogar Supercomputer nutzen Elastic

1,2 Milliarden Dokumente, 160 GB – so viele Daten werden im National Energy Research Scientific Computing Center (NERSC) Tag für Tag erfasst. Dabei werden die unterschiedlichsten Arten von Metriken indiziert und für wissenschaftliche Untersuchungen genutzt: von KPIs zum Stromverbrauch in Umspannwerken und der Luft- und Wassertemperatur in Gebäuden über die Auslastung von Festplatten bis hin zu Angaben zu Netzwerk-I/O und Systemlast.

Aber das NERSC ist nicht die einzige Organisation, die Elastic für ihre Zahlen nutzt. Hier finden Sie weitere Kundenbeispiele.

Metriken sind nur eine Möglichkeit

Haben Sie auch Netzwerkdaten? Infrastruktur-Logs? Dokumente mit Unmengen von Text? Zentralisieren Sie all diese Daten im Elastic Stack zusammen mit Ihren Metriken und nutzen Sie diese Fülle an Informationen, um Analysen anzureichern, Workflows zu optimieren und Ihre Architektur zu vereinfachen.

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