メトリックス分析
ドローンセンサーのデータからCPUの使用率まで、Elasticsearchの優れたテキスト検索機能により、メトリック情報を収集しつづけます。
どんな数値でも収集、分析、異常を検知。 今すぐトライ
どんな数値でも、制限はありません
ディメンション、タグ、ユニークな数、フィールドなどを自由に検索。ホスト名やIPアドレス、デプロイメント、カラー配色など、好みに合わせてカスタマイズできます。
検索エンジンは数値にも応用できます。
まずは、はじめてみましょう。
そのスピードとスケールを体験してください
転置インデックス以上の性能を得るため、新しいデータ種類を作成し、BKDツリーの実装、カラムストアの追加を行うことで、さらに高速な検索、メモリやディスク使用量の削減、より効率的なデータの構造化を実現しました。ペタバイト規模のデータフィールドや値へ高速にアクセスできるのです。
お試しください
To modify defaults, edit modules.d/system.yml.
Start a trial to experience Machine Learning or enable authentication.
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.
To modify defaults, edit modules.d/apache.yml.
Start a trial to experience Machine Learning or enable authentication.
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.
To modify defaults, edit modules.d/mongodb.yml.
Start a trial to experience Machine Learning or enable authentication.
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.
To modify defaults, edit modules.d/docker.yml.
Start a trial to experience Machine Learning or enable authentication.
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.
- 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.
Start a trial to experience Machine Learning or enable authentication.
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.
Start a trial to experience Machine Learning or enable authentication.
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
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
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.
- Register, if you do not already have an account
- Log into the Elastic Cloud console
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
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.
- Register, if you do not already have an account
- Log into the Elastic Cloud console
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
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.
- Register, if you do not already have an account
- Log into the Elastic Cloud console
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
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.
- Register, if you do not already have an account
- Log into the Elastic Cloud console
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
From your machine or wherever you run kubectl:
- Download metricbeat-kubernetes.yml
- Edit metricbeat-kubernetes.yml to point to your Elasticsearch instance
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.
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
- Select Create Cluster, leave cluster size slider at 4 GB RAM, and click Create
- Note the Cloud ID as <cloud.id> and 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:
Paste in the <password> for the elastic user when prompted
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.
Machine LearningのJobで、異常を検知する
データ量が大きくなるほど、ストリーミングの平均値や測定値、合計値の異常を発見するのがむずかしくなります。常に全てのデータを監視するのは不可能でしょう。
Elastic StackのMachine Learning機能は、膨大なデータの中から通常と異常を学習し、自動的に異常を検知します。
Elastic Stackは超大規模データにも対応
国立エネルギー研究科学コンピューティングセンター (National Energy Research Scientific Computing Center（NERSC）)では、一日に12億ドキュメント、160GBのデータをElastic Stackを利用し分析しています。変電所の電力使用率のKPIから建物の空気や水の温度、コンピューターディスク、ネットワークI/O、システム負荷まで、あらゆる種類のメトリックをインデックス化して、科学的発見の進歩を保とうとしています。
Elastic Stackの導入事例はこれだけではありません。 他ユーザーの事例も併せてご覧ください。
