Quick startedit

To quickly get up and running with Kibana, set up on Cloud, then add a sample data set that you can explore and analyze.

When you’ve finished, you’ll know how to:

Required privilegesedit

You must have read, write, and manage privileges on the kibana_sample_data_* indices. Learn how to secure access to Kibana, or refer to Security privileges for more information.

Set up on cloudedit

There’s no faster way to get started than with our hosted Elasticsearch Service on Elastic Cloud:

  1. Get a free trial.
  2. Log into Elastic Cloud.
  3. Click Create deployment.
  4. Select a solution and give your deployment a name.
  5. Click Create deployment and download the password for the elastic user.

That’s it! Now that you are up and running, it’s time to get some data into Kibana. Click Launch Kibana.

Add the sample dataedit

Sample data sets come with sample visualizations, dashboards, and more to help you explore Kibana before you ingest or add your own data.

  1. On the home page, click Try our sample data.
  2. On the Sample eCommerce orders card, click Add data.

    Add data UI for the sample data sets

Explore the dataedit

Discover displays the data in an interactive histogram that shows the distribution of data, or documents, over time, and a table that lists the fields for each document that matches the index pattern. To view a subset of the documents, you can apply filters to the data, and customize the table to display only the fields you want to explore.

  1. Open the main menu, then click Discover.
  2. Change the time filter to Last 7 days.

    Time filter menu with Last 7 days filter configured
  3. To view the sales orders for women’s clothing that are $60 or more, use the KQL search field:

    products.taxless_price >= 60 and category : Women's Clothing
    Discover tables that displays only the orders for women’s clothing that are $60 or more
  4. To view only the product categories that contain sales orders, hover over the category field, then click +.

    Discover table that displays only the product categories that contain orders

View and analyze the dataedit

A dashboard is a collection of panels that you can use to view and analyze the data. Panels contain visualizations, interactive controls, text, and more.

  1. Open the main menu, then click Dashboard.
  2. Click [eCommerce] Revenue Dashboard.

    The [eCommerce] Revenue Dashboard that comes with the Sample eCommerce order data set

Create a visualization paneledit

Create a treemap panel that shows the top sales regions and manufacturers, then add the panel to the dashboard.

  1. In the toolbar, click Edit.
  2. On the dashboard, click Create visualization.
  3. In the drag-and-drop visualization editor, open the Visualization type dropdown, then select Treemap.

    Chart type menu with Treemap selected
  4. From the Available fields list, drag the following fields to the workspace:

    • geoip.city_name
    • manufacturer.keyword

      Treemap that displays Top values of geoip.city_name and Top values or manufacturer.keyword fields
  5. Click Save and return.

    The treemap appears as the last visualization panel on the dashboard.

Interact with the dataedit

You can interact with the dashboard data using controls that allow you to apply dashboard-level filters. Interact with the [eCommerce] Controls panel to view the women’s clothing data from the Gnomehouse manufacturer.

  1. From the Manufacturer dropdown, select Gnomehouse.
  2. From the Category dropdown, select Women’s Clothing.
  3. Click Apply changes.

    The [eCommerce] Revenue Dashboard that shows only the women’s clothing data from the Gnomehouse manufacturer

Filter the dataedit

To view a subset of the data, you can apply filters to the dashboard panels. Apply a filter to view the women’s clothing data generated on Wednesday from the Gnomehouse manufacturer.

  1. Click Add filter.
  2. From the Field dropdown, select day_of_week.
  3. From the Operator dropdown, select is.
  4. From the Value dropdown, select Wednesday.
  5. Click Save.

    The [eCommerce] Revenue Dashboard that shows only the women’s clothing data generated on Wednesday from the Gnomehouse manufacturer

What’s next?edit

Add your own data. Ready to add your own data? Go to Ingest logs, metrics, and uptime data with Elastic Agent, or go to Add data to Kibana and learn about all the other ways you can add data.

Explore your own data in Discover. Ready to learn more about exploring your data in Discover? Go to Discover.

Create a dashboard with your own data. Ready to learn more about analyzing your data in Dashboard? Go to Dashboard.

Try out the machine learning features. Ready to analyze the sample data sets and generate models for its patterns of behavior? Go to Getting started with machine learning.