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Transformations changes (#27690) 

* Chunking out the long Transformation topic. Also, updated TOC. Local build looks fine.

* More changes.

* More re-arranging of content. Fixed links in Types and Options page.

* Capitalization changes.

* Changes to Overview section.

* Fixed merge conflicts.

* Fixed typo to fix build failure.

* Update docs/sources/panels/transformations/types-options.md

Co-authored-by: Diana Payton <52059945+oddlittlebird@users.noreply.github.com>

* Changes from Diana.

* Fixed a typo in a relref.

* Fixed broken link.

* Update link in Troubleshooting topic.

Co-authored-by: Diana Payton <52059945+oddlittlebird@users.noreply.github.com>
parent 0fe3b78a
Showing with 404 additions and 13 deletions
docs/sources/guides/whats-new-in-v7-0.md
......@@ -60,9 +60,9 @@ In the future we will add more workflows and integrations so that correlating be
The data you want to visualize can come from many different places and it is usually not in exactly the right form. Users can now transform non-time series data into tables (e.g., JSON files or even simple lookup tables) in seconds without any customization or additional overhead. They can then combine non-time series data with any other data in Grafana; data from an external database or a panel that already exists in one of their current dashboards.
By chaining a simple set of point and click [transformations]({{< relref "../panels/transformations.md" >}}), users will be able join, pivot, filter, re-name and do calculations to get the results they need. Perfect for operations across queries or data sources missing essential data transformations.
By chaining a simple set of point and click [transformations]({{< relref "../panels/transformations/_index.md" >}}), users will be able join, pivot, filter, re-name and do calculations to get the results they need. Perfect for operations across queries or data sources missing essential data transformations.
[Transformations]({{< relref "../panels/transformations.md" >}}) also adds the ability to do maths across queries. Lots of data sources do not support this natively so being able to do it in Grafana is a powerful feature.
[Transformations]({{< relref "../panels/transformations/_index.md" >}}) also adds the ability to do maths across queries. Lots of data sources do not support this natively, so being able to do it in Grafana is a powerful feature.
For users with large dashboards or with heavy queries, being able to reuse the query result from one panel in another panel can be a huge performance gain for slow queries (e.g log or sql queries). From the data source menu in the query editor, you can choose the `--dashboard--` option and then choose the query result from another panel on the same dashboard.
......@@ -80,7 +80,7 @@ We are also introducing a new shared data model for both time series and table d
- **Outer join:** Joins many time series/tables by a field. This can be used to outer join multiple time series on the _time_ field to show many time series in one table.
- **Add field from calculation:** This is a powerful transformation that allows you perform many different types of math operations and add the result as a new field. Can be used to calculate the difference between two series or fields and add the result to a new field. Or multiply one field with another another and add the result to a new field.
Learn more about this feature in [Transformations]({{< relref "../panels/transformations.md" >}}).
Learn more about this feature in [Transformations]({{< relref "../panels/transformations/_index.md" >}}).
## Field options and overrides
......
docs/sources/guides/whats-new-in-v7-2.md
......@@ -79,8 +79,8 @@ The [Field options]({{< relref "../panels/field-options.md" >}}) content has bee
Grafana 7.2 includes the following transformation enhancements:
- A new [Group By]({{< relref "../panels/transformations.md#group-by">}}) transformation that allows you to group by multiple fields and add any number of aggregations for other fields.
- The [Labels to fields]({{< relref "../panels/transformations.md#labels-to-fields">}}) transformation now allows you to pick one label and use that as the name of the value field.
- A new [Group By]({{< relref "../panels/transformations/types-options.md#group-by">}}) transformation that allows you to group by multiple fields and add any number of aggregations for other fields.
- The [Labels to fields]({{< relref "../panels/transformations/types-options.md#labels-to-fields">}}) transformation now allows you to pick one label and use that as the name of the value field.
- You can drag transformations to reorder them. Remember that transformations are processed in the order they are listed in the UI, so think before you move something!
{{< docs-imagebox img="/img/docs/v72/transformations.gif" max-width="800px" caption="Group by and reordering of transformations" >}}
......
docs/sources/menu.yaml
......@@ -165,6 +165,13 @@
name: Queries
- link: /panels/transformations/
name: Transformations
children:
- link: /panels/transformations/
name: Overview
- link: /panels/transformations/apply-transformations/
name: Apply transformations
- link: /panels/transformations/types-options/
name: Transformation types and options
- link: /panels/field-options/
name: Field options
- link: /panels/panel-editor/
......
docs/sources/panels/add-a-panel.md
......@@ -58,7 +58,7 @@ Our Grafana Fundamentals tutorial is a great place to start, or you can learn mo
- Learn more about [panel editor]({{< relref "panel-editor.md" >}}) options.
- Add more [queries]({{< relref "queries.md" >}}).
- [Transform]({{< relref "transformations.md" >}}) your data.
- [Transform]({{< relref "transformations/_index.md" >}}) your data.
- [Configure]({{< relref "field-options.md" >}}) how your results are displayed in the visualization.
- If you made a graph panel, set up an [alert]({{< relref "../alerting/alerts-overview.md" >}}).
- Create [templates and variables]({{< relref "../variables/templates-and-variables.md" >}}).
docs/sources/panels/panel-editor.md
......@@ -61,7 +61,7 @@ The section contains tabs where you enter queries, transform your data, and crea
{{< docs-imagebox img="/img/docs/panel-editor/data-section-7-0.png" class="docs-image--no-shadow" max-width="1200px" >}}
- **Query tab -** Select your data source and enter queries here. For more information, refer to [Queries]({{< relref "queries.md" >}}).
- **Transform tab -** Apply data transformations. For more information, refer to [Transformations]({{< relref "transformations.md" >}}).
- **Transform tab -** Apply data transformations. For more information, refer to [Transformations]({{< relref "transformations/_index.md" >}}).
- **Alert tab -** Write alert rules. For more information, refer to [Create alerts]({{< relref "../alerting/create-alerts.md" >}}).
### Panel and field options (side pane)
......
docs/sources/panels/transformations/_index.md 0 → 100644
+++
title = "Overview"
type = "docs"
[menu.docs]
identifier = "overview"
parent = "transformations"
weight = 300
+++
# Transformations overview
Transformations process the result set of a query before it’s passed on for visualization. They allow you to rename fields, join separate time series together, do math across queries, and more. For users, with numerous dashboards or with a large volume of queries, the ability to reuse the query result from one panel in another panel can be a huge performance gain.
The transformations feature is accessible from the **Transform** tab of the Grafana panel editor.
> **Note:** Transformations is a Grafana 7.0 beta feature. Topics in this section will be frequently updated as we work on this feature.
Transformations sometimes result in data that cannot be graphed. When that happens, Grafana displays a suggestion on the visualization that you can click to switch to table visualization. This often helps you better understand what the transformation is doing to your data.
## Order of transformations
In case there are multiple transformations, Grafana applies them in the exact sequence in which they are listed. Each transformation creates a new result set that is passed onto the next transformation in the pipeline for processing.
The order in which transformations are applied can make a huge difference in how your results look. For example, if you use a Reduce transformation to condense all the results of one column into a single value, then you can only apply transformations to that single value.
## Prerequisites
Before you can configure and apply transformations:
- You must have entered a query and returned data from a data source. For more information on queries, refer to [Queries]({{< relref "../queries.md" >}}).
- You must have applied a visualization that supports queries. Examples are:
- [Bar gauge]({{< relref "../visualizations/bar-gauge-panel.md" >}})
- [Gauge]({{< relref "../visualizations/gauge-panel.md" >}})
- [Graph]({{< relref "../visualizations/graph-panel.md" >}})
- [Heatmap]({{< relref "../visualizations/heatmap.md" >}})
- [Logs]({{< relref "../visualizations/logs-panel.md" >}})
- [Stat]({{< relref "../visualizations/stat-panel.md" >}})
- [Table]({{< relref "../visualizations/table-panel.md" >}})
\ No newline at end of file
docs/sources/panels/transformations/apply-transformations.md 0 → 100644
+++
title = "Apply a transformation"
type = "docs"
[menu.docs]
identifier = "apply-transformation"
parent = "transformations"
weight = 300
+++
# Apply transformations
You can apply transformations from the Transform tab of the Grafana panel editor, which is located next to the Queries tab. See also, [Debug transformations](#debug-transformations).
To apply a transformation:
1. Navigate to the panel where you want to add one or more transformations.
1. Click the panel title and then click **Edit**.
1. Click the **Transform** tab.
1. Click a transformation to select it.
A transformation row displays. You can configure the transformation options here. For more information, refer to [Transformation types and options]({{< relref "types-options.md" >}}).
1. Click **Add transformation** to apply another transformation.
This next transformation acts on the result set returned by the previous transformation.
{{< docs-imagebox img="/img/docs/transformations/transformations-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Delete a transformation
To remove a transformation that is no longer needed, click the trash can icon.
## Debug transformations
To see the input and the output result sets of the transformation, click the bug icon on the right side of the transformation row
Grafana displays the transformation debug view below the transformation row.
{{< docs-imagebox img="/img/docs/transformations/debug-transformations-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
docs/sources/panels/transformations/prereq.md 0 → 100644
+++
title = "Prerequisites"
type = "docs"
[menu.docs]
identifier = "transformations_prerequisites"
parent = "transformations"
weight = 300
+++
# Prerequisites
Before you can configure and apply transformations:
- You must have entered a query and returned data from a data source. For more information on queries, refer to [Queries]({{< relref "../queries.md" >}}).
- You must have applied a visualization that supports queries. Examples are:
- [Bar gauge]({{< relref "../visualizations/bar-gauge-panel.md" >}})
- [Gauge]({{< relref "../visualizations/gauge-panel.md" >}})
- [Graph]({{< relref "../visualizations/graph-panel.md" >}})
- [Heatmap]({{< relref "../visualizations/heatmap.md" >}})
- [Logs]({{< relref "../visualizations/logs-panel.md" >}})
- [Stat]({{< relref "../visualizations/stat-panel.md" >}})
- [Table]({{< relref "../visualizations/table-panel.md" >}})
docs/sources/panels/transformations/types-options.md 0 → 100644
+++
title = "Transformation Types and Options"
type = "docs"
[menu.docs]
identifier = "transformation_types_and_options"
parent = "transformations"
weight = 300
+++
# Transformation types and options
Grafana comes with the following transformations:
- [Reduce](#reduce)
- [Filter by name](#filter-by-name)
- [Filter data by query](#filter-data-by-query)
- [Organize fields](#organize-fields)
- [Outer join](#join-by-field-outer-join)
- [Series to rows](#series-to-rows)
- [Add field from calculation](#add-field-from-calculation)
- [Labels to fields](#labels-to-fields)
- [Group by](#group-by)
- [Merge](#merge)
Keep reading for detailed descriptions of each type of transformation and the options available for each, as well as suggestions on how to use them.
## Reduce
Apply a _Reduce_ transformation when you want to simplify your results down to one value. Reduce removes the time component. If visualized as a table, it reduces a column down to one row (value).
In the **Calculations** field, enter one or more calculation types. Click to see a list of calculation choices. For information about available calculations, refer to the [Calculation list]({{< relref "../calculations-list.md" >}}).
Once you select at least one calculation, Grafana reduces the results down to one value using the calculation you select. If you select more than one calculation, then more than one value is displayed.
Here's an example of a table with time series data. Before I apply the transformation, you can see all the data organized by time.
{{< docs-imagebox img="/img/docs/transformations/reduce-before-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
After I apply the transformation, there is no time value and each column has been reduced to one row showing the results of the calculations that I chose.
{{< docs-imagebox img="/img/docs/transformations/reduce-after-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Merge
> **Note:** This transformation is only available in Grafana 7.1+.
Use this transformation to combine the result from multiple queries into one single result. This is helpful when using the table panel visualization. Values that can be merged are combined into the same row. Values are mergeable if the shared fields contains the same data. For information, refer to [Table panel]({{< relref "../visualizations/table-panel.md" >}}).
In the example below, we have two queries returning table data. It is visualized as two separate tables before applying the transformation.
Query A:
| Time | Job | Uptime |
| ------------------- | ------- | --------- |
| 2020-07-07 11:34:20 | node | 25260122 |
| 2020-07-07 11:24:20 | postgre | 123001233 |
Query B:
| Time | Job | Errors |
| ------------------- | ------- | ------ |
| 2020-07-07 11:34:20 | node | 15 |
| 2020-07-07 11:24:20 | postgre | 5 |
Here is the result after applying the Merge transformation.
| Time | Job | Errors | Uptime |
| ------------------- | ------- | ------ | --------- |
| 2020-07-07 11:34:20 | node | 15 | 25260122 |
| 2020-07-07 11:24:20 | postgre | 5 | 123001233 |
## Filter by name
Use this transformation to remove portions of the query results.
Grafana displays the **Identifier** field, followed by the fields returned by your query.
You can apply filters in one of two ways:
- Enter a regex expression.
- Click a field to toggle filtering on that field. Filtered fields are displayed with dark gray text, unfiltered fields have white text.
In the example below, I removed the Min field from the results.
Here is the original query table. (This is streaming data, so numbers change over time and between screenshots.)
{{< docs-imagebox img="/img/docs/transformations/filter-name-table-before-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
Here is the table after I applied the transformation to remove the Min field.
{{< docs-imagebox img="/img/docs/transformations/filter-name-table-after-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
Here is the same query using a Stat visualization.
{{< docs-imagebox img="/img/docs/transformations/filter-name-stat-after-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Filter data by query
Use this transformation in panels that have multiple queries, if you want to hide one or more of the queries.
Grafana displays the query identification letters in dark gray text. Click a query identifier to toggle filtering. If the query letter is white, then the results are displayed. If the query letter is dark, then the results are hidden.
In the example below, the panel has three queries (A, B, C). I removed the B query from the visualization.
{{< docs-imagebox img="/img/docs/transformations/filter-by-query-stat-example-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Organize fields
Use this transformation to rename, reorder, or hide fields returned by the query.
> **Note:** This transformation only works in panels with a single query. If your panel has multiple queries, then you must either apply an Outer join transformation or remove the extra queries.
Grafana displays a list of fields returned by the query. You can:
- Change field order by hovering your cursor over a field. The cursor turns into a hand and then you can drag the field to its new place.
- Hide or show a field by clicking the eye icon next to the field name.
- Rename fields by typing a new name in the **Rename <field>** box.
In the example below, I hid the value field and renamed Max and Min.
{{< docs-imagebox img="/img/docs/transformations/organize-fields-stat-example-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Join by field (outer join)
Use this transformation to join multiple time series from a result set by field.
This transformation is especially useful if you want to combine queries so that you can calculate results from the fields.
In the example below, I have a template query displaying time series data from multiple servers in a table visualization. I can only view the results of one query at a time.
{{< docs-imagebox img="/img/docs/transformations/join-fields-before-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
I applied a transformation to join the query results using the time field. Now I can run calculations, combine, and organize the results in this new table.
{{< docs-imagebox img="/img/docs/transformations/join-fields-after-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Add field from calculation
Use this transformation to add a new field calculated from two other fields. Each transformation allows you to add one new field.
- **Mode -** Select a mode:
- **Reduce row -** Apply selected calculation on each row of selected fields independently.
- **Binary option -** Apply basic math operation(sum, multiply, etc) on values in a single row from two selected fields.
- **Field name -** Select the names of fields you want to use in the calculation for the new field.
- **Calculation -** Select a calculation to use when Grafana creates the new field. Click in the field to see a list of calculation choices. For information about available calculations, refer to the [Calculation list]({{< relref "../calculations-list.md" >}}).
- **Alias -** (Optional) Enter the name of your new field. If you leave this blank, then the field will be named to match the calculation.
- **Replace all fields -** (Optional) Select this option if you want to hide all other fields and display only your calculated field in the visualization.
In the example below, I added two fields together and named them Sum.
{{< docs-imagebox img="/img/docs/transformations/add-field-from-calc-stat-example-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Labels to fields
> **Note:** In order to apply this transformation, your query needs to returns labeled fields.
When you select this transformation, Grafana automatically transforms all labeled data into fields.
Example: Given a query result of two time series
1: labels Server=Server A, Datacenter=EU
2: labels Server=Server B, Datacenter=EU
This would result in a table like this
| Time | Server | Datacenter | Value |
| ------------------- | -------- | ---------- | ----- |
| 2020-07-07 11:34:20 | Server A | EU | 1 |
| 2020-07-07 11:34:20 | Server B | EU | 2 |
**Value field name**
If you selected Server as in the **Value field name**, then you would get one field for every value of the Server label.
| Time | Datacenter | Server A | Server B |
| ------------------- | ---------- | -------- | -------- |
| 2020-07-07 11:34:20 | EU | 1 | 2 |
For this example, I manually defined labels in the Random Walk visualization of TestData DB.
{{< docs-imagebox img="/img/docs/transformations/labels-to-fields-before-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
After I apply the transformation, my labels appear in the table as fields.
{{< docs-imagebox img="/img/docs/transformations/labels-to-fields-after-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
## Group by
> **Note:** This transformation is only available in Grafana 7.2+.
This transformation groups the data by a specified field (column) value and processes calculations on each group. Click to see a list of calculation choices. For information about available calculations, refer to the [List of calculations]({{< relref "../calculations-list.md" >}}).
Here's an example of original data.
| Time | Server ID | CPU Temperature | Server Status |
| ------------------- | --------- | --------------- | ------------- |
| 2020-07-07 11:34:20 | server 1 | 80 | Shutdown |
| 2020-07-07 11:34:20 | server 3 | 62 | OK |
| 2020-07-07 10:32:20 | server 2 | 90 | Overload |
| 2020-07-07 10:31:22 | server 3 | 55 | OK |
| 2020-07-07 09:30:57 | server 3 | 62 | Rebooting |
| 2020-07-07 09:30:05 | server 2 | 88 | OK |
| 2020-07-07 09:28:06 | server 1 | 80 | OK |
| 2020-07-07 09:25:05 | server 2 | 88 | OK |
| 2020-07-07 09:23:07 | server 1 | 86 | OK |
This transformation goes in two steps. First you specify one or multiple fields to group the data by. This will group all the same values of those fields together, as if you sorted them. For instance if we group by the Server ID field, then it would group the data this way:
| Time | Server ID | CPU Temperature | Server Status |
| ------------------- | ------------ | --------------- | ------------- |
| 2020-07-07 11:34:20 | **server 1** | 80 | Shutdown |
| 2020-07-07 09:28:06 | **server 1** | 80 | OK |
| 2020-07-07 09:23:07 | **server 1** | 86 | OK |
|
| 2020-07-07 10:32:20 | server 2 | 90 | Overload
| 2020-07-07 09:30:05 | server 2 | 88 | OK
| 2020-07-07 09:25:05 | server 2 | 88 | OK
|
| 2020-07-07 11:34:20 | **_server 3_** | 62 | OK
| 2020-07-07 10:31:22 | **_server 3_** | 55 | OK
| 2020-07-07 09:30:57 | **_server 3_** | 62 | Rebooting
All rows with the same value of Server ID are grouped together.
After choosing which field you want to group your data by, you can add various calculations on the other fields, and apply the calculation to each group of rows. For instance, we could want to calculate the average CPU temperature for each of those servers. So we can add the _mean_ calculation applied on the CPU Temperature field to get the following:
| Server ID | CPU Temperature (mean) |
| --------- | ---------------------- |
| server 1 | 82 |
| server 2 | 88.6 |
| server 3 | 59.6 |
And we can add more than one calculation. For instance:
- For field Time, we can calculate the _Last_ value, to know when the last data point was received for each server
- For field Server Status, we can calculate the _Last_ value to know what is the last state value for each server
- For field Temperature, we can also calculate the _Last_ value to know what is the latest monitored temperature for each server
We would then get :
| Server ID | CPU Temperature (mean) | CPU Temperature (last) | Time (last) | Server Status (last) |
| --------- | ---------------------- | ---------------------- | ------------------- | -------------------- |
| server 1 | 82 | 80 | 2020-07-07 11:34:20 | Shutdown |
| server 2 | 88.6 | 90 | 2020-07-07 10:32:20 | Overload |
| server 3 | 59.6 | 62 | 2020-07-07 11:34:20 | OK |
This transformation allows you to extract some key information out of your time series and display them in a convenient way.
## Series to rows
> **Note:** This transformation is only available in Grafana 7.1+.
Use this transformation to combine the result from multiple time series data queries into one single result. This is helpful when using the table panel visualization.
The result from this transformation will contain three columns: Time, Metric, and Value. The Metric column is added so you easily can see from which query the metric originates from. Customize this value by defining Label on the source query.
In the example below, we have two queries returning time series data. It is visualized as two separate tables before applying the transformation.
Query A:
| Time | Temperature |
| ------------------- | ----------- |
| 2020-07-07 11:34:20 | 25 |
| 2020-07-07 10:31:22 | 22 |
| 2020-07-07 09:30:05 | 19 |
Query B:
| Time | Humidity |
| ------------------- | -------- |
| 2020-07-07 11:34:20 | 24 |
| 2020-07-07 10:32:20 | 29 |
| 2020-07-07 09:30:57 | 33 |
Here is the result after applying the Series to rows transformation.
| Time | Metric | Value |
| ------------------- | ----------- | ----- |
| 2020-07-07 11:34:20 | Temperature | 25 |
| 2020-07-07 11:34:20 | Humidity | 22 |
| 2020-07-07 10:32:20 | Humidity | 29 |
| 2020-07-07 10:31:22 | Temperature | 22 |
| 2020-07-07 09:30:57 | Humidity | 33 |
| 2020-07-07 09:30:05 | Temperature | 19 |
docs/sources/panels/visualizations/bar-gauge-panel.md
......@@ -19,7 +19,7 @@ This panel can show one or more bar gauges depending on how many series, rows, o
Bar gauge visualizations allow you to apply:
- [Data transformations]({{< relref "../transformations.md" >}})
- [Data transformations]({{< relref "../transformations/prereq.md" >}})
- [Field options and overrides]({{< relref "../field-options.md" >}})
- [Thresholds]({{< relref "../thresholds.md" >}})
......
docs/sources/panels/visualizations/gauge-panel.md
......@@ -17,7 +17,7 @@ Gauge is a single value panel that can repeat a gauge for every series, column o
Gauge visualizations allow you to apply:
- [Data transformations]({{< relref "../transformations.md" >}})
- [Data transformations]({{< relref "../transformations/prereq.md" >}})
- [Field options and overrides]({{< relref "../field-options.md" >}})
- [Thresholds]({{< relref "../thresholds.md" >}})
......
docs/sources/panels/visualizations/graph-panel.md
......@@ -15,7 +15,7 @@ This visualization is the most-used in the Grafana ecosystem. It can render as a
## Data and field options
Graph visualizations allow you to apply:
- [Data transformations]({{< relref "../transformations.md" >}})
- [Data transformations]({{< relref "../transformations/prereq.md" >}})
- [Alerts]({{< relref "../../alerting/alerts-overview.md" >}}) - This is the only type of visualization that allows you to set alerts.
- [Thresholds]({{< relref "../thresholds.md" >}})
......
docs/sources/panels/visualizations/stat-panel.md
......@@ -19,7 +19,7 @@ The Stat panel shows a one large stat value with an optional graph sparkline. Yo
Stat visualizations allow you to apply:
- [Data transformations]({{< relref "../transformations.md" >}})
- [Data transformations]({{< relref "../transformations/prereq.md" >}})
- [Field options and overrides]({{< relref "../field-options.md" >}})
- [Thresholds]({{< relref "../thresholds.md" >}})
......
docs/sources/panels/visualizations/table-panel.md
......@@ -21,7 +21,7 @@ The table panel is very flexible, supporting multiple modes for time series and
Table visualizations allow you to apply:
- [Data transformations]({{< relref "../transformations.md" >}})
- [Data transformations]({{< relref "../transformations/prereq.md" >}})
- [Field options and overrides]({{< relref "../field-options.md" >}})
- [Thresholds]({{< relref "../thresholds.md" >}})
......
docs/sources/troubleshooting/_index.md
......@@ -23,7 +23,7 @@ For more information, refer to [Enable debug logging in Grafana CLI]({{< relref
Order of transformations matters. If the final data output from multiple transformations looks wrong, try changing the transformation order. Each transformation transforms data returned by the previous transformation, not the original raw data.
For more information, refer to [Debug transformations]({{< relref "../panels/transformations.md#debug-transformations" >}}).
For more information, refer to [Debug transformations]({{< relref "../panels/transformations/apply-transformations.md" >}}).
## Text missing with server-side image rendering (RPM-based Linux)
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