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Elastic Docs ›Elasticsearch Service Documentation ›Adding data to Elasticsearch

Configure Beats and Logstash with Cloud ID

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Configure Beats and Logstash with Cloud ID

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The Cloud ID reduces the number of steps required to start sending data from Beats or Logstash to your hosted Elasticsearch cluster on Elasticsearch Service. Because we made it easier to send data, you can start exploring visualizations in Kibana on Elasticsearch Service that much more quickly.

Exploring data from Beats or Logstash in Kibana after sending it to a hosted Elasticsearch cluster

The Cloud ID works by assigning a unique ID to your hosted Elasticsearch cluster on Elasticsearch Service. All deployments automatically get a Cloud ID.

You include your Cloud ID along with your Elasticsearch Service user credentials (defined in cloud.auth) when you run Beats or Logstash locally, and then let Elasticsearch Service handle all of the remaining connection details to send the data to your hosted cluster on Elasticsearch Service safely and securely.

The Cloud ID and `elastic` user information shown when you create a deployment

What are Beats and Logstash?

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Not sure why you need Beats or Logstash? Here’s what they do:

  • Beats is our open source platform for single-purpose data shippers. The purpose of Beats is to help you gather data from different sources and to centralize the data by shipping it to Elasticsearch. Beats install as lightweight agents and ship data from hundreds or thousands of machines to your hosted Elasticsearch cluster on Elasticsearch Service. If you want more processing muscle, Beats can also ship to Logstash for transformation and parsing before the data gets stored in Elasticsearch.
  • Logstash is an open source, server-side data processing pipeline that ingests data from a multitude of sources simultaneously, transforms it, and then sends it to your favorite place where you stash things, here your hosted Elasticsearch cluster on Elasticsearch Service. Logstash supports a variety of inputs that pull in events from a multitude of common sources — logs, metrics, web applications, data stores, and various AWS services — all in continuous, streaming fashion.

Before you begin

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To use the Cloud ID, you need:

  • A deployment with an Elasticsearch cluster to send data to.
  • Beats or Logstash, installed locally wherever you want to send data from.

  • To configure Beats or Logstash, you need:

    • The unique Cloud ID for your deployment, available from the deployment overview page.

    • A user ID and password that has permission to send data to your cluster.

      In our examples, we use the elastic superuser that every Elasticsearch cluster comes with. The password for the elastic user is provided when you create a deployment (and can also be reset if you forget it). On a production system, you should adapt these examples by creating a user that can write to and access only the minimally required indices. For each Beat, review the specific feature and role table, similar to the one in Metricbeat documentation.

Configure Beats with your Cloud ID

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The following example shows how you can send operational data from Metricbeat to Elasticsearch Service by using the Cloud ID. Any of the available Beats will work, but we had to pick one for this example.

For others, you can learn more about getting started with each Beat.

To get started with Metricbeat and Elasticsearch Service:

  1. Log in to the Elasticsearch Service Console.
  2. Create a new deployment and copy down the password for the elastic user.
  3. On the deployment overview page, copy down the Cloud ID.
  4. Set up the Beat of your choice, such as Metricbeat version 7.17.

  5. Configure the Beat output to send to Elastic Cloud.

    Make sure you replace the values for cloud.id and cloud.auth with your own information.

  6. Open Kibana and explore!

Metricbeat creates a data view (formerly index pattern) with defined fields, searches, visualizations, and dashboards that you can start exploring in Kibana. Look for information related to system metrics, such as CPU usage, utilization rates for memory and disk, and details for processes.

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