Metrics

Analyse d’indicateurs

Que ce soit pour les données en provenance du capteur d’un drone ou la charge CPU, nous avons pris les superpouvoirs de recherche textuelle d’Elasticsearch pour les appliquer aux métriques. Et il ne cesse de s'améliorer.

Découvrez l'analyse d'indicateurs avec Elastic. Essayer

Examinez vos indicateurs à votre guise

Naviguez sans contrainte à travers vos dimensions, balises, cardinalités et champs. Elastic n'impose aucune limite et ne dicte pas la manière dont vous pouvez explorer vos données. Au contraire, vous pouvez examiner les attributs — nom d'hôte, adresse IP, déploiement, couleur — de manière rapide, continue et évolutive, et ce, en utilisant la visualisation de votre choix.

Vous ne saviez pas qu'un moteur de recherche pouvait être aussi doué avec des chiffres ? Ce n'est pas grave, maintenant vous le savez.
Commencez maintenant !

Un niveau de rapidité et d'évolutivité qui ne passe pas inaperçu

Nous sommes allés au-delà de l'index inversé, avons créé de nouveaux types de données, mis en œuvre des arbres BKD, et ajouté une structure en colonne — tout ceci pour aboutir à des données structurées de manière plus efficace pour des recherches plus rapides, tout en réduisant l'utilisation mémoire et disque. En d'autres termes : vous pouvez accéder à des champs et à des valeurs à travers des pétaoctets de données à des vitesses incroyables.

Allez-y, essayez!

Procurez-vous une nouvelle version et commencez.
In Elasticsearch install directory:
Once Elasticsearch starts, in Elasticsearch install directory (separate window):

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Kibana install directory:

Modify config/kibana.yml to set credentials for Elasticsearch

elasticsearch.username: "kibana"     
elasticsearch.password: "<kibana_pw>"
			
In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
			

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

Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
Open dashboard:
"[Metricbeat System] Overview" and click on your host.
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:
Once Elasticsearch starts, in Elasticsearch install directory (separate window):

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Kibana install directory:

Modify config/kibana.yml to set credentials for Elasticsearch

elasticsearch.username: "kibana"     
elasticsearch.password: "<kibana_pw>"
			
In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
			

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

Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
Open dashboard:
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:
Once Elasticsearch starts, in Elasticsearch install directory (separate window):

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Kibana install directory:

Modify config/kibana.yml to set credentials for Elasticsearch

elasticsearch.username: "kibana"     
elasticsearch.password: "<kibana_pw>"
			
In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
			

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

Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
Open dashboard:
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:
Once Elasticsearch starts, in Elasticsearch install directory (separate window):

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Kibana install directory:

Modify config/kibana.yml to set credentials for Elasticsearch

elasticsearch.username: "kibana"
elasticsearch.password: "<kibana_pw>"
			
In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
			

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

Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
Open dashboard:
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:
Once Elasticsearch starts, in Elasticsearch install directory (separate window):

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Kibana install directory:

Modify config/kibana.yml to set credentials for Elasticsearch

elasticsearch.username: "kibana"
elasticsearch.password: "<kibana_pw>"
            
In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
From your machine or wherever you run kubectl:
env:
  - name: ELASTICSEARCH_USERNAME
    value: elastic
  - name: ELASTICSEARCH_PASSWORD
    value: changeme
Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
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:
In Kibana install directory:

Note the password for elastic user as <es_pw>

Note the password for kibana user as <kibana_pw>

In Heartbeat install directory:

Modify heartbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<es_pw>"
            
Open browser @
http://localhost:5601 (login: elastic/<es_pw>)
Open dashboard:
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.

  • Register, if you do not already have an account
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Metricbeat

In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				

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

Open browser @
http://<kibana_url>:5601 (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
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Metricbeat

In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				

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

Open browser @
http://<kibana_url>:5601 (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
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Metricbeat

In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				

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

Open browser @
http://<kibana_url>:5601 (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
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Metricbeat

In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				
Open browser @
http://<kibana_url>:5601 (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
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Metricbeat on your local machine

In Metricbeat install directory:

Modify metricbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				

From your machine or wherever you run kubectl:

env:
  - name: ELASTICSEARCH_USERNAME
    value: elastic
  - name: ELASTICSEARCH_PASSWORD
    value: changeme
				
Open browser @
http://<kibana_url>:5601 (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
  • Log into the Elastic Cloud console
To create a cluster, in Elastic Cloud console:
  • Select Create Cluster, leave size slider at 4 GB RAM, and click Create
  • Note the Cloud ID as <cloud.id>
  • Note the cluster Password as <password>
  • In Overview >> Endpoints section note Kibana URL as <kibana_url>
  • Wait until cluster plan completes

Download and unpack Heartbeat (Beta)

In Heartbeat install directory:

Modify heartbeat.yml to set credentials for Elasticsearch output

output.elasticsearch:
  username: "elastic"
  password: "<password>"
				
Open browser @
http://<kibana_url>:5601 (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.

Exécutez des tâches de machine learning pour détecter des anomalies

Au fur et à mesure que les volumes de données augmentent, il est facile de rater des anomalies quand elles sont noyées dans la masse et quasiment impossible de surveiller toutes vos visualisations à la fois. (Nous sommes tous humains après tout.)

Les fonctionnalités de machine learning pour la Suite Elastic automatisent la détection d'anomalies à grande échelle. Elles « apprennent » le comportement normal de vos données afin d'identifier ce qui ne l'est pas, et il vous en avertit en temps réel.

Même les superordinateurs utilisent Elastic

1,2 milliards de documents, 160 Go. Il s'agit de la quantité de données que le Centre National de Calcul Scientifique pour la Recherche sur l'Énergie (NERSC) collecte tous les jours. Des indicateurs de performance clés pour la consommation d'une sous-station électrique à la température de l'air et de l'eau d'un bâtiment, des entrées/sorties réseau, ou encore une charge de système, ils indexent toutes sortes d'indicateurs afin de continuer à faire avancer les découvertes scientifiques.

Ils ne sont pas les seuls à effectuer des calculs avec Elastic. Découvrez davantage de retours clients.

Les indicateurs ne sont qu'un point de départ

Vous avez des données réseau ? Des logs d'infrastructure ? Des documents avec des tonnes de texte ? Centralisez le tout dans la Suite Elastic et enrichissez vos analyses, rationalisez vos flux de travail et simplifiez votre architecture.

Logging

Un logging rapide et évolutif qui ne vous laissera pas tomber.

En savoir plus

Recherche Web

Créez facilement une excellente expérience de recherche.

En savoir plus

Analyses de sécurité

Analyse interactive rapide et évolutive.

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APM

Obtenez un aperçu de la performance de vos applications.

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Recherche applicative

Recherchez à travers tous vos documents.

En savoir plus