Metrics

Metriken

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

Entdecken Sie Metrikanalysen mit Elastic. Probieren Sie es aus.

Neu Größere Bandbreite Ihrer Metrik-Lösung: mit dem Azure Monitoring-Modul und Optimierungen in Metricbeat. Weitere Informationen

Analysieren Sie Ihre Zahlen flexibel und nach Ihren Wünschen

Experimentieren Sie mit Dimensionen, Tags, Kardinalität und Feldern. Elastic schreibt Ihnen nicht vor, wie Sie Ihre Daten zu durchsuchen haben, und es gibt auch keine Einschränkungen. Im Gegenteil: Sie können kontinuierlich und schnell nach Attributen suchen (z. B. Hostname, IP-Adresse, Implementierung oder Farbe) – und das in großem Umfang, nach Ihren Anforderungen, in beliebiger Reihenfolge und in der Visualisierung, die Ihnen gefällt.

Sie wussten gar nicht, dass eine Suchmaschine so gut mit Zahlen umgehen kann? Kein Problem, jetzt wissen Sie es ja.
Hier können Sie direkt loslegen.

Geschwindigkeit und Skalierbarkeit, die sich bemerkbar machen

Damit das gelingt, sind wir über die Indizierung mittels invertierter Dateien hinausgegangen. Wir haben neue Datentypen entwickelt, BKD-Bäume implementiert und ein Spaltenlayout für die Speicherung hinzufügt. Das alles resultiert in einer effizienteren Datenstrukturierung für eine schnellere Suche sowie weniger Speichernutzung und eine geringere Datenträgerauslastung. Oder anders formuliert: Sie können in bemerkenswerter Geschwindigkeit auf Felder und Werte aus einem Petabyte an Daten zugreifen.

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: <cloud.auth>
				

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 Auffälligkeiten entdecken

Wenn Daten skaliert werden, kann es leicht passieren, dass problematische Datenpunkte unter der Vielzahl an Durchschnittswerten, Messungen und Gesamtwerten übersehen werden. Und es ist unpraktisch, alle Visualisierungen permanent zu analysieren. (Schließlich sind wir alle nur Menschen.)

Die Machine-Learning-Funktionen im Elastic Stack automatisieren die Erkennung von Auffälligkeiten in großem Umfang. Das System lernt, was bei Ihren Daten normal ist, und erkennt auch Anomalitäten, um Sie anschließend zu benachrichtigen.

Sogar Supercomputer nutzen Elastic

1,2 Milliarden Dokumente, 160 GB – diese Datenmenge erfasst das National Energy Research Scientific Computing Center (NERSC) Tag für Tag. Dabei werden die unterschiedlichsten Arten von Metriken indiziert und für wissenschaftliche Untersuchungen genutzt: KPIs zum Stromverbrauch in Umspannwerken, Luft- und Wassertemperatur in Gebäuden, Auslastung von Festplatten, Netzwerkein-/ausgabe und Systemlast.

Das sind nicht die einzigen Unternehmen, die mit Elastic ihre Zahlen durchsuchen. Hier finden Sie weitere Kundenbeispiele.

Metriken sind nur eine Möglichkeit

Haben Sie auch Netzwerkdaten? Infrastruktur-Logs? Dokumente mit einer Unmenge an Text? Zentralisieren Sie all diese Daten im Elastic Stack, zusammen mit Ihren Kennzahlen, für umfassendere Analysen, optimierte Workflows und eine vereinfachte Architektur.

Logging

Schnelles und skalierbares Logging – ohne Unterbrechung.

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Website-Suche

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Interaktive Untersuchung – schnell und skalierbar.

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APM

Erhalte Einblicke in deine Application-Performance.

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App Suche

Suche nach Dokumenten, Geodaten usw.

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