* [DOCS] Getting started refresh * Dashboard changes * Discover and Dashboard changes * [DOCS] Adds quick start * Redirects * Redirects pt 2 * Redirects pt * More redirect issues * Removed second chunk of KQL tasks * Review comments # Conflicts: # docs/getting-started/tutorial-define-index.asciidoc # docs/getting-started/tutorial-full-experience.asciidoc # docs/images/tutorial-dashboard.png # docs/images/tutorial-full-inspect1.png # docs/images/tutorial-pattern-1.png # docs/images/tutorial-visualize-bar-1.5.png # docs/images/tutorial-visualize-map-2.png # docs/images/tutorial-visualize-md-2.png # docs/images/tutorial-visualize-pie-2.png # docs/images/tutorial-visualize-pie-3.png # docs/images/tutorial-visualize-wizard-step-1.png
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docs/getting-started/quick-start-guide.asciidoc
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|
@ -0,0 +1,142 @@
|
|||
[[get-started]]
|
||||
== Quick start
|
||||
|
||||
To quickly get up and running with {kib}, 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:
|
||||
|
||||
* <<explore-the-data,Explore the data with *Discover*.>>
|
||||
|
||||
* <<view-and-analyze-the-data,Gain insight into the data with *Dashboard*.>>
|
||||
|
||||
[float]
|
||||
=== Before you begin
|
||||
When security is enabled, you must have `read`, `write`, and `manage` privileges on the `kibana_sample_data_*` indices. For more information, refer to {ref}/security-privileges.html[Security privileges].
|
||||
|
||||
[float]
|
||||
[[set-up-on-cloud]]
|
||||
== Set up on cloud
|
||||
|
||||
include::{docs-root}/shared/cloud/ess-getting-started.asciidoc[]
|
||||
|
||||
[float]
|
||||
[[gs-get-data-into-kibana]]
|
||||
== Add the sample data
|
||||
|
||||
Sample data sets come with sample visualizations, dashboards, and more to help you explore {kib} without adding your own data.
|
||||
|
||||
. From the home page, click *Try our sample data*.
|
||||
|
||||
. On the *Sample eCommerce orders* card, click *Add data*.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/add-sample-data.png[]
|
||||
|
||||
[float]
|
||||
[[explore-the-data]]
|
||||
== Explore the data
|
||||
|
||||
*Discover* displays an interactive histogram that shows the distribution of of data, or documents, over time, and a table that lists the fields for each document that matches the index. By default, all fields are shown for each matching document.
|
||||
|
||||
. Open the menu, then click *Discover*.
|
||||
|
||||
. Change the <<set-time-filter, time filter>> to *Last 7 days*.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-discover-2.png[]
|
||||
|
||||
. To focus in on the documents you want to view, use the <<kuery-query,{kib} Query Language>>. In the *KQL* search field, enter:
|
||||
+
|
||||
[source,text]
|
||||
products.taxless_price >= 60 AND category : Women's Clothing
|
||||
+
|
||||
The query returns the women's clothing orders for $60 and more.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-discover-4.png[]
|
||||
|
||||
. Hover over the list of *Available fields*, then click *+* next to the fields you want to view in the table.
|
||||
+
|
||||
For example, when you add the *category* field, the table displays the product categories for the orders.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-discover-3.png[]
|
||||
+
|
||||
For more information, refer to <<discover, *Discover*>>.
|
||||
|
||||
[float]
|
||||
[[view-and-analyze-the-data]]
|
||||
== View and analyze the data
|
||||
|
||||
A dashboard is a collection of panels that you can use to view and analyze the data. Panels contain visualizations, interactive controls, Markdown, and more.
|
||||
|
||||
. Open the menu, then click *Dashboard*.
|
||||
|
||||
. Click *[eCommerce] Revenue Dashboard*.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-dashboard.png[]
|
||||
|
||||
[float]
|
||||
[[filter-and-query-the-data]]
|
||||
=== Filter the data
|
||||
|
||||
To focus in on the data you want to view on the dashboard, use filters.
|
||||
|
||||
. From the *Controls* visualization, make a selection from the *Manufacturer* and *Category* dropdowns, then click *Apply changes*.
|
||||
+
|
||||
For example, the following dashboard shows the data for women's clothing from Gnomehouse.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-filter.png[]
|
||||
|
||||
. To manually add a filter, click *Add filter*, then specify the options.
|
||||
+
|
||||
For example, to view the orders for Wednesday, select *day_of_week* from the *Field* dropdown, select *is* from the *Operator* dropdown, then select *Wednesday* from the *Value* dropdown.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-filter2.png[]
|
||||
|
||||
. When you are done, remove the filters.
|
||||
+
|
||||
For more information, refer to <<dashboard,*Dashboard*>>.
|
||||
|
||||
[float]
|
||||
[[create-a-visualization]]
|
||||
=== Create a visualization
|
||||
|
||||
To create a treemap that shows the top regions and manufacturers, use *Lens*, then add the treemap to the dashboard.
|
||||
|
||||
. From the {kib} toolbar, click *Edit*, then click *Create new*.
|
||||
|
||||
. On the *New Visualization* window, click *Lens*.
|
||||
|
||||
. From the *Available fields* list, drag and drop the following fields to the visualization builder:
|
||||
|
||||
* *geoip.city_name*
|
||||
|
||||
* *manufacturer.keyword*
|
||||
+
|
||||
. From the visualization dropdown, select *Treemap*.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-visualization-dropdown.png[Visualization dropdown with Treemap selected]
|
||||
|
||||
. Click *Save*.
|
||||
|
||||
. On the *Save Lens visualization*, enter a title and make sure *Add to Dashboard after saving* is selected, then click *Save and return*.
|
||||
+
|
||||
The treemap appears as the last visualization on the dashboard.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-final-dashboard.gif[Final dashboard with new treemap visualization]
|
||||
+
|
||||
For more information, refer to <<lens, *Lens*>>.
|
||||
|
||||
[float]
|
||||
[[quick-start-whats-next]]
|
||||
== What's next?
|
||||
|
||||
If you are you ready to add your own data, refer to <<connect-to-elasticsearch,Add data to {kib}>>.
|
||||
|
||||
If you want to ingest your data, refer to {ingest-guide}/ingest-management-getting-started.html[Quick start: Get logs and metrics into the Elastic Stack].
|
|
@ -1,35 +0,0 @@
|
|||
[[explore-your-data]]
|
||||
=== Explore your data
|
||||
|
||||
With *Discover*, you use {ref}/query-dsl-query-string-query.html#query-string-syntax[Elasticsearch
|
||||
queries] to explore your data and narrow the results with filters.
|
||||
|
||||
. Open the menu, then go to *Discover*.
|
||||
+
|
||||
The `shakes*` index pattern appears.
|
||||
|
||||
. To make `ba*` the index, click the *Change Index Pattern* dropdown, then select `ba*`.
|
||||
+
|
||||
By default, all fields are shown for each matching document.
|
||||
|
||||
. In the *Search* field, enter the following, then click *Update*:
|
||||
+
|
||||
[source,text]
|
||||
account_number<100 AND balance>47500
|
||||
+
|
||||
The search returns all account numbers between zero and 99 with balances in
|
||||
excess of 47,500. Results appear for account numbers 8, 32, 78, 85, and 97.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-discover-2.png[Image showing the search results for account numbers between zero and 99, with balances in excess of 47,500]
|
||||
+
|
||||
. Hover over the list of *Available fields*, then
|
||||
click *Add* next to each field you want include in the table.
|
||||
+
|
||||
For example, when you add the `account_number` field, the display changes to a list of five
|
||||
account numbers.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-discover-3.png[Image showing a dropdown with five account numbers, which match the previous query for account balance]
|
||||
|
||||
Now that you know what your documents contain, it's time to gain insight into your data with visualizations.
|
|
@ -1,159 +0,0 @@
|
|||
[[explore-kibana-using-sample-data]]
|
||||
== Explore {kib} using sample data
|
||||
|
||||
Ready to get some hands-on experience with {kib}?
|
||||
In this tutorial, you’ll work with {kib} sample data and learn to:
|
||||
|
||||
* <<explore-the-data, Explore the sample data using *Discover*>>
|
||||
|
||||
* <<view-and-analyze-the-data, View and analyze the data on a dashboard>>
|
||||
|
||||
* <<filter-and-query-the-data, Filter and query the dashboard data>>
|
||||
|
||||
NOTE: If security is enabled, you must have `read`, `write`, and `manage` privileges
|
||||
on the `kibana_sample_data_*` indices. For more information, refer to
|
||||
{ref}/security-privileges.html[Security privileges].
|
||||
|
||||
[float]
|
||||
[[add-the-sample-data]]
|
||||
=== Add the sample data
|
||||
|
||||
Add the *Sample flight data*.
|
||||
|
||||
. On the home page, click *Load a data set and a {kib} dashboard*.
|
||||
|
||||
. On the *Sample flight data* card, click *Add data*.
|
||||
|
||||
[float]
|
||||
[[explore-the-data]]
|
||||
=== Explore the data
|
||||
|
||||
Explore the documents in the index that
|
||||
match the selected index pattern. The index pattern tells {kib} which {es} index you want to
|
||||
explore.
|
||||
|
||||
. Open the menu, then go to *Discover*.
|
||||
|
||||
. Make sure `kibana_sample_data_flights` is the current index pattern.
|
||||
You might need to click *New* in the {kib} toolbar to refresh the data.
|
||||
+
|
||||
You'll see a histogram that shows the distribution of
|
||||
documents over time. A table lists the fields for
|
||||
each document that matches the index. By default, all fields are shown.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-discover1.png[]
|
||||
|
||||
. Hover over the list of *Available fields*, then click *Add* next
|
||||
to each field you want explore in the table.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-discover2.png[]
|
||||
|
||||
[float]
|
||||
[[view-and-analyze-the-data]]
|
||||
=== View and analyze the data
|
||||
|
||||
A _dashboard_ is a collection of panels that provide you with an overview of your data that you can
|
||||
use to analyze your data. Panels contain everything you need, including visualizations,
|
||||
interactive controls, Markdown, and more.
|
||||
|
||||
To open the *Global Flight* dashboard, open the menu, then go to *Dashboard*.
|
||||
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-dashboard.png[]
|
||||
|
||||
[float]
|
||||
[[change-the-panel-data]]
|
||||
==== Change the panel data
|
||||
|
||||
To gain insights into your data, change the appearance and behavior of the panels.
|
||||
For example, edit the metric panel to find the airline that has the lowest average fares.
|
||||
|
||||
. In the {kib} toolbar, click *Edit*.
|
||||
|
||||
. In the *Average Ticket Price* metric panel, open the panel menu, then select *Edit visualization*.
|
||||
|
||||
. To change the data on the panel, use an {es} {ref}/search-aggregations.html[bucket aggregation],
|
||||
which sorts the documents that match your search criteria into different categories or buckets.
|
||||
|
||||
.. In the *Buckets* pane, select *Add > Split group*.
|
||||
|
||||
.. From the *Aggregation* dropdown, select *Terms*.
|
||||
|
||||
.. From the *Field* dropdown, select *Carrier*.
|
||||
|
||||
.. Set *Descending* to *4*, then click *Update*.
|
||||
+
|
||||
The average ticket price for all four airlines appear in the visualization builder.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-edit1.png[]
|
||||
|
||||
. To save your changes, click *Save and return* in the {kib} toolbar.
|
||||
|
||||
. To save the dashboard, click *Save* in the {kib} toolbar.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-edit2.png[]
|
||||
|
||||
[float]
|
||||
[[filter-and-query-the-data]]
|
||||
==== Filter and query the data
|
||||
|
||||
To focus in on the data you want to explore, use filters and queries.
|
||||
For more information, refer to
|
||||
{ref}/query-filter-context.html[Query and filter context].
|
||||
|
||||
To filter the data:
|
||||
|
||||
. In the *Controls* visualization, select an *Origin City* and *Destination City*, then click *Apply changes*.
|
||||
+
|
||||
The `OriginCityName` and the `DestCityName` fields filter the data in the panels.
|
||||
+
|
||||
For example, the following dashboard shows the data for flights from London to Milan.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-filter.png[]
|
||||
|
||||
. To manually add a filter, click *Add filter*,
|
||||
then specify the data you want to view.
|
||||
|
||||
. When you are finished experimenting, remove all filters.
|
||||
|
||||
[[query-the-data]]
|
||||
To query the data:
|
||||
|
||||
. To view all flights out of Rome, enter the following in the *KQL* query bar, then click *Update*:
|
||||
+
|
||||
[source,text]
|
||||
OriginCityName: Rome
|
||||
|
||||
. For a more complex query with AND and OR, enter:
|
||||
+
|
||||
[source,text]
|
||||
OriginCityName:Rome AND (Carrier:JetBeats OR Carrier:"Kibana Airlines")
|
||||
+
|
||||
The dashboard panels update to display the flights out of Rome on JetBeats and
|
||||
{kib} Airlines.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/tutorial-sample-query.png[]
|
||||
|
||||
. When you are finished exploring, remove the query by
|
||||
clearing the contents in the *KQL* query bar, then click *Update*.
|
||||
|
||||
[float]
|
||||
=== Next steps
|
||||
|
||||
Now that you know the {kib} basics, try out the <<create-your-own-dashboard, Create your own dashboard>> tutorial, where you'll learn to:
|
||||
|
||||
* Add a data set to {kib}
|
||||
|
||||
* Define an index pattern
|
||||
|
||||
* Discover and explore data
|
||||
|
||||
* Create and add panels to a dashboard
|
||||
|
||||
|
|
@ -1,193 +0,0 @@
|
|||
[[tutorial-visualizing]]
|
||||
=== Visualize your data
|
||||
|
||||
Shape your data using a variety
|
||||
of {kib} supported visualizations, tables, and more. In this tutorial, you'll create four
|
||||
visualizations that you'll use to create a dashboard.
|
||||
|
||||
To begin, open the menu, go to *Dashboard*, then click *Create new dashboard*.
|
||||
|
||||
[float]
|
||||
[[compare-the-number-of-speaking-parts-in-the-play]]
|
||||
=== Compare the number of speaking parts in the plays
|
||||
|
||||
To visualize the Shakespeare data and compare the number of speaking parts in the plays, create a bar chart using *Lens*.
|
||||
|
||||
. Click *Create new*, then click *Lens* on the *New Visualization* window.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-wizard-step-1.png[Image showing different options for your new visualization]
|
||||
|
||||
. Make sure the index pattern is *shakes*.
|
||||
|
||||
. Display the play data along the x-axis.
|
||||
|
||||
.. From the *Available fields* list, drag and drop *play_name* to the *X-axis* field.
|
||||
|
||||
.. Click *Top values of play_name*.
|
||||
|
||||
.. From the *Order direction* dropdown, select *Ascending*.
|
||||
|
||||
.. In the *Label* field, enter `Play Name`.
|
||||
|
||||
. Display the number of speaking parts per play along the y-axis.
|
||||
|
||||
.. From the *Available fields* list, drag and drop *speaker* to the *Y-axis* field.
|
||||
|
||||
.. Click *Unique count of speaker*.
|
||||
|
||||
.. In the *Label* field, enter `Speaking Parts`.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-bar-1.5.png[Bar chart showing the speaking parts data]
|
||||
|
||||
. *Save* the chart with the name `Bar Example`.
|
||||
+
|
||||
To show a tooltip with the number of speaking parts for that play, hover over a bar.
|
||||
+
|
||||
Notice how the individual play names show up as whole phrases, instead of
|
||||
broken up into individual words. This is the result of the mapping
|
||||
you did at the beginning of the tutorial, when you marked the `play_name` field
|
||||
as `not analyzed`.
|
||||
|
||||
[float]
|
||||
[[view-the-average-account-balance-by-age]]
|
||||
=== View the average account balance by age
|
||||
|
||||
To gain insight into the account balances in the bank account data, create a pie chart. In this tutorial, you'll use the {es}
|
||||
{ref}/search-aggregations.html[bucket aggregation] to specify the pie slices to display. The bucket aggregation sorts the documents that match your search criteria into different
|
||||
categories and establishes multiple ranges of account balances so that you can find how many accounts fall into each range.
|
||||
|
||||
. Click *Create new*, then click *Pie* on the *New Visualization* window.
|
||||
|
||||
. On the *Choose a source* window, select `ba*`.
|
||||
+
|
||||
Since the default search matches all documents, the pie contains a single slice.
|
||||
|
||||
. In the *Buckets* pane, click *Add > Split slices.*
|
||||
|
||||
.. From the *Aggregation* dropdown, select *Range*.
|
||||
|
||||
.. From the *Field* dropdown, select *balance*.
|
||||
|
||||
.. Click *Add range* until there are six rows of fields, then define the following ranges:
|
||||
+
|
||||
[source,text]
|
||||
0 999
|
||||
1000 2999
|
||||
3000 6999
|
||||
7000 14999
|
||||
15000 30999
|
||||
31000 50000
|
||||
|
||||
. Click *Update*.
|
||||
+
|
||||
The pie chart displays the proportion of the 1,000 accounts that fall into each of the ranges.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-pie-2.png[Pie chart displaying accounts that fall into each of the ranges, scaled to 1000 accounts]
|
||||
|
||||
. Add another bucket aggregation that displays the ages of the account holders.
|
||||
|
||||
.. In the *Buckets* pane, click *Add*, then click *Split slices*.
|
||||
|
||||
.. From the *Sub aggregation* dropdown, select *Terms*.
|
||||
|
||||
.. From the *Field* dropdown, select *age*, then click *Update*.
|
||||
+
|
||||
The break down of the ages of the account holders are displayed
|
||||
in a ring around the balance ranges.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-pie-3.png[Final pie chart showing all of the changes]
|
||||
|
||||
. Click *Save*, then enter `Pie Example` in the *Title* field.
|
||||
|
||||
[float]
|
||||
[role="xpack"]
|
||||
[[visualize-geographic-information]]
|
||||
=== Visualize geographic information
|
||||
|
||||
To visualize geographic information in the log file data, use <<maps,Maps>>.
|
||||
|
||||
. Click *Create new*, then click *Maps* on the *New Visualization* window.
|
||||
|
||||
. To change the time, use the time filter.
|
||||
|
||||
.. Set the *Start date* to `May 18, 2015 @ 12:00:00.000`.
|
||||
|
||||
.. Set the *End date* to `May 20, 2015 @ 12:00:00.000`.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/gs_maps_time_filter.png[Image showing the time filter for Maps tutorial]
|
||||
|
||||
.. Click *Update*
|
||||
|
||||
. Map the geo coordinates from the log files.
|
||||
|
||||
.. Click *Add layer > Clusters and grids*.
|
||||
|
||||
.. From the *Index pattern* dropdown, select *logstash*.
|
||||
|
||||
.. Click *Add layer*.
|
||||
|
||||
. Specify the *Layer Style*.
|
||||
|
||||
.. From the *Fill color* dropdown, select the yellow to red color ramp.
|
||||
|
||||
.. In the *Border width* field, enter `3`.
|
||||
|
||||
.. From the *Border color* dropdown, select *#FFF*, then click *Save & close*.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-map-2.png[Example of a map visualization]
|
||||
|
||||
. Click *Save*, then enter `Map Example` in the *Title* field.
|
||||
|
||||
. Add the map to your dashboard.
|
||||
|
||||
.. Open the menu, go to *Dashboard*, then click *Add*.
|
||||
|
||||
.. On the *Add panels* flyout, click *Map Example*.
|
||||
|
||||
[float]
|
||||
[[tutorial-visualize-markdown]]
|
||||
=== Add context to your visualizations with Markdown
|
||||
|
||||
Add context to your new visualizations with Markdown text.
|
||||
|
||||
. Click *Create new*, then click *Markdown* on the *New Visualization* window.
|
||||
|
||||
. In the *Markdown* text field, enter:
|
||||
+
|
||||
[source,markdown]
|
||||
# This is a tutorial dashboard!
|
||||
The Markdown widget uses **markdown** syntax.
|
||||
> Blockquotes in Markdown use the > character.
|
||||
|
||||
. Click *Update*.
|
||||
+
|
||||
The Markdown renders in the preview pane.
|
||||
+
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-visualize-md-2.png[Image showing example markdown editing field]
|
||||
|
||||
. Click *Save*, then enter `Markdown Example` in the *Title* field.
|
||||
|
||||
[role="screenshot"]
|
||||
image::images/tutorial-dashboard.png[Final visualization with bar chart, pie chart, map, and markdown text field]
|
||||
|
||||
[float]
|
||||
=== Next steps
|
||||
|
||||
Now that you have the basics, you're ready to start exploring your own system data with {kib}.
|
||||
|
||||
* To add your own data to {kib}, refer to <<connect-to-elasticsearch,Add data to {kib}>>.
|
||||
|
||||
* To search and filter your data, refer to {kibana-ref}/discover.html[Discover].
|
||||
|
||||
* To create a dashboard with your own data, refer to <<dashboard, Dashboard>>.
|
||||
|
||||
* To create maps that you can add to your dashboards, refer to <<maps,Maps>>.
|
||||
|
||||
* To create presentations of your live data, refer to <<canvas,Canvas>>.
|
Before Width: | Height: | Size: 558 KiB After Width: | Height: | Size: 82 KiB |
Before Width: | Height: | Size: 208 KiB After Width: | Height: | Size: 648 KiB |
|
@ -67,7 +67,7 @@ You can read more at {ref}/rollup-job-config.html[rollup job configuration].
|
|||
=== Try it: Create and visualize rolled up data
|
||||
|
||||
This example creates a rollup job to capture log data from sample web logs.
|
||||
To follow along, add the <<gs-get-data-into-kibana, sample web logs data set>>.
|
||||
To follow along, add the sample web logs data set.
|
||||
|
||||
In this example, you want data that is older than 7 days in the target index pattern `kibana_sample_data_logs`
|
||||
to roll up once a day into the index `rollup_logstash`. You’ll bucket the
|
||||
|
|
|
@ -75,7 +75,7 @@ This page has moved. Please see <<reporting-getting-started>>.
|
|||
[role="exclude",id="add-sample-data"]
|
||||
== Add sample data
|
||||
|
||||
This page has moved. Please see <<gs-get-data-into-kibana>>.
|
||||
This page has moved. Please see <<get-started>>.
|
||||
|
||||
[role="exclude",id="tilemap"]
|
||||
== Coordinate map
|
||||
|
@ -128,3 +128,9 @@ This content has moved. See
|
|||
|
||||
This content has moved. See
|
||||
{ref}/ccr-getting-started.html#ccr-getting-started-remote-cluster[Connect to a remote cluster].
|
||||
|
||||
[role="exclude",id="tutorial-define-index"]
|
||||
== Define your index patterns
|
||||
|
||||
This content has moved. See
|
||||
<<get-started, Quick start>>.
|
||||
|
|
|
@ -11,7 +11,7 @@ To start working with your data in {kib}, you can:
|
|||
|
||||
* Connect {kib} with existing {es} indices.
|
||||
|
||||
If you're not ready to use your own data, you can add a <<gs-get-data-into-kibana, sample data set>>
|
||||
If you're not ready to use your own data, you can add a <<get-started, sample data set>>
|
||||
to see all that you can do in {kib}.
|
||||
|
||||
[float]
|
||||
|
|
|
@ -39,7 +39,7 @@ Create the *Host Overview* drilldown shown above.
|
|||
|
||||
*Set up the dashboards*
|
||||
|
||||
. Add the <<gs-get-data-into-kibana, sample web logs>> data set.
|
||||
. Add the sample web logs data set.
|
||||
|
||||
. Create a new dashboard, called `Host Overview`, and include these visualizations
|
||||
from the sample data set:
|
||||
|
|
|
@ -36,7 +36,7 @@ The following panels support URL drilldowns:
|
|||
|
||||
This example shows how to create the "Show on Github" drilldown shown above.
|
||||
|
||||
. Add the <<gs-get-data-into-kibana, sample web logs>> data set.
|
||||
. Add the sample web logs data set.
|
||||
. Open the *[Logs] Web traffic* dashboard. This isn’t data from Github, but it should work for demonstration purposes.
|
||||
. In the dashboard menu bar, click *Edit*.
|
||||
. In *[Logs] Visitors by OS*, open the panel menu, and then select *Create drilldown*.
|
||||
|
|
|
@ -1,61 +0,0 @@
|
|||
[[get-started]]
|
||||
= Get started
|
||||
|
||||
[partintro]
|
||||
--
|
||||
|
||||
Ready to try out {kib} and see what it can do? The quickest way to get started with {kib} is to set up on Cloud, then add a sample data set to explore the full range of {kib} features.
|
||||
|
||||
[float]
|
||||
[[set-up-on-cloud]]
|
||||
== Set up on cloud
|
||||
|
||||
include::{docs-root}/shared/cloud/ess-getting-started.asciidoc[]
|
||||
|
||||
[float]
|
||||
[[gs-get-data-into-kibana]]
|
||||
== Get data into {kib}
|
||||
|
||||
The easiest way to get data into {kib} is to add a sample data set.
|
||||
|
||||
{kib} has several sample data sets that you can use before loading your own data:
|
||||
|
||||
* *Sample eCommerce orders* includes visualizations for tracking product-related information,
|
||||
such as cost, revenue, and price.
|
||||
|
||||
* *Sample flight data* includes visualizations for monitoring flight routes.
|
||||
|
||||
* *Sample web logs* includes visualizations for monitoring website traffic.
|
||||
|
||||
To use the sample data sets:
|
||||
|
||||
. Go to the home page.
|
||||
|
||||
. Click *Load a data set and a {kib} dashboard*.
|
||||
|
||||
. Click *View data* and view the prepackaged dashboards, maps, and more.
|
||||
|
||||
[role="screenshot"]
|
||||
image::getting-started/images/add-sample-data.png[]
|
||||
|
||||
NOTE: The timestamps in the sample data sets are relative to when they are installed.
|
||||
If you uninstall and reinstall a data set, the timestamps change to reflect the most recent installation.
|
||||
|
||||
[float]
|
||||
== Next steps
|
||||
|
||||
* To get a hands-on experience creating visualizations, follow the <<explore-kibana-using-sample-data, add sample data>> tutorial.
|
||||
|
||||
* If you're ready to load an actual data set and build a dashboard, follow the <<create-your-own-dashboard, Create your own dashboard>> tutorial.
|
||||
|
||||
--
|
||||
|
||||
include::{kib-repo-dir}/getting-started/tutorial-sample-data.asciidoc[]
|
||||
|
||||
include::{kib-repo-dir}/getting-started/tutorial-full-experience.asciidoc[]
|
||||
|
||||
include::{kib-repo-dir}/getting-started/tutorial-define-index.asciidoc[]
|
||||
|
||||
include::{kib-repo-dir}/getting-started/tutorial-discovering.asciidoc[]
|
||||
|
||||
include::{kib-repo-dir}/getting-started/tutorial-visualizing.asciidoc[]
|
|
@ -2,6 +2,8 @@ include::introduction.asciidoc[]
|
|||
|
||||
include::whats-new.asciidoc[]
|
||||
|
||||
include::{kib-repo-dir}/getting-started/quick-start-guide.asciidoc[]
|
||||
|
||||
include::setup.asciidoc[]
|
||||
|
||||
include::monitoring/configuring-monitoring.asciidoc[leveloffset=+1]
|
||||
|
@ -11,8 +13,6 @@ include::monitoring/monitoring-kibana.asciidoc[leveloffset=+2]
|
|||
|
||||
include::security/securing-kibana.asciidoc[]
|
||||
|
||||
include::getting-started.asciidoc[]
|
||||
|
||||
include::discover.asciidoc[]
|
||||
|
||||
include::dashboard/dashboard.asciidoc[]
|
||||
|
|
|
@ -155,6 +155,6 @@ and start exploring data in minutes.
|
|||
You can also <<install, install {kib} on your own>> — no code, no additional
|
||||
infrastructure required.
|
||||
|
||||
Our <<create-your-own-dashboard, Getting Started>> and in-product guidance can
|
||||
Our <<get-started, Quick start>> and in-product guidance can
|
||||
help you get up and running, faster. Click the help icon image:images/intro-help-icon.png[]
|
||||
in the top navigation bar for help with questions or to provide feedback.
|
||||
|
|
|
@ -28,7 +28,7 @@ To complete this tutorial, you'll need the following:
|
|||
* **A space**: In this tutorial, use `Dev Mortgage` as the space
|
||||
name. See <<spaces-managing, spaces management>> for
|
||||
details on creating a space.
|
||||
* **Data**: You can use <<gs-get-data-into-kibana, sample data>> or
|
||||
* **Data**: You can use <<get-started, sample data>> or
|
||||
live data. In the following steps, Filebeat and Metricbeat data are used.
|
||||
|
||||
[float]
|
||||
|
|