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Docs: Minor edits to the README and several md files (#19238)

Browse Source 
* Update README.md

Capitalized the G and S in "Getting Started," and moved "guide" to match the section title in the docs.

* Fixed sentence structure. Changed "download" to "grafana.com/get" and changed "get" to "download".

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

*  Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)

* Docs: Replace "datasources" with "data sources" (#19111)
This commit is contained in:
Brenda Harjala
2019-09-20 00:04:56 +02:00
committed by Marcus Olsson
parent b20a258b72
commit c9e566b156
62 changed files with 302 additions and 302 deletions
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docs/sources/features/datasources/_index.md
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@@ -11,15 +11,15 @@ weight = 5
# Data Source Overview
Grafana supports many different storage backends for your time series data (Data Source). Each Data Source has a specific Query Editor that is customized for the features and capabilities that the particular Data Source exposes.
Grafana supports many different storage backends for your time series data (data source). Each data source has a specific Query Editor that is customized for the features and capabilities that the particular data source exposes.
## Querying
The query language and capabilities of each Data Source are obviously very different. You can combine data from multiple Data Sources onto a single Dashboard, but each Panel is tied to a specific Data Source that belongs to a particular Organization.
The query language and capabilities of each data source are obviously very different. You can combine data from multiple data sources onto a single Dashboard, but each Panel is tied to a specific data source that belongs to a particular Organization.
## Supported Data Sources
## Supported data sources
The following datasources are officially supported:
The following data sources are officially supported:
* [Graphite]({{< relref "graphite.md" >}})
* [Prometheus]({{< relref "prometheus.md" >}})
docs/sources/features/datasources/azuremonitor.md
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@@ -16,7 +16,7 @@ weight = 5
As of Grafana 6.0, the Azure Monitor plugin has been moved into Grafana so it now ships with built-in support for Azure Monitor.
The Azure Monitor Datasource supports multiple services in the Azure cloud:
The Azure Monitor data source supports multiple services in the Azure cloud:
- **[Azure Monitor]({{< relref "#querying-the-azure-monitor-service" >}})** is the platform service that provides a single source for monitoring Azure resources.
- **[Application Insights]({{< relref "#querying-the-application-insights-service" >}})** is an extensible Application Performance Management (APM) service for web developers on multiple platforms and can be used to monitor your live web application - it will automatically detect performance anomalies.
@@ -25,7 +25,7 @@ The Azure Monitor Datasource supports multiple services in the Azure cloud:
## Adding the data source to Grafana
The datasource can access metrics from four different services. You can configure access to the services that you use. It is also possible to use the same credentials for multiple services if that is how you have set it up in Azure AD.
The data source can access metrics from four different services. You can configure access to the services that you use. It is also possible to use the same credentials for multiple services if that is how you have set it up in Azure AD.
- [Guide to setting up an Azure Active Directory Application for Azure Monitor.](https://docs.microsoft.com/en-us/azure/azure-resource-manager/resource-group-create-service-principal-portal)
- [Guide to setting up an Azure Active Directory Application for Azure Log Analytics.](https://dev.loganalytics.io/documentation/Authorization/AAD-Setup)
@@ -45,7 +45,7 @@ The datasource can access metrics from four different services. You can configur
4. Paste these four items into the fields in the Azure Monitor API Details section:
{{< docs-imagebox img="/img/docs/v62/config_1_azure_monitor_details.png" class="docs-image--no-shadow" caption="Azure Monitor Configuration Details" >}}
- The Subscription Id can be changed per query. Save the datasource and refresh the page to see the list of subscriptions available for the specified Client Id.
- The Subscription Id can be changed per query. Save the data source and refresh the page to see the list of subscriptions available for the specified Client Id.
5. If you are also using the Azure Log Analytics service, then you need to specify these two config values (or you can reuse the Client Id and Secret from the previous step).
@@ -71,7 +71,7 @@ az ad sp create-for-rbac -n "http://localhost:3000"
## Choose a Service
In the query editor for a panel, after choosing your Azure Monitor datasource, the first option is to choose a service. There are three options here:
In the query editor for a panel, after choosing your Azure Monitor data source, the first option is to choose a service. There are three options here:
- `Azure Monitor`
- `Application Insights`
@@ -121,7 +121,7 @@ Instead of hard-coding things like server, application and sensor name in you me
Note that the Azure Monitor service does not support multiple values yet. If you want to visualize multiple time series (for example, metrics for server1 and server2) then you have to add multiple queries to able to view them on the same graph or in the same table.
The Azure Monitor Datasource Plugin provides the following queries you can specify in the `Query` field in the Variable edit view. They allow you to fill a variable's options list.
The Azure Monitor data source Plugin provides the following queries you can specify in the `Query` field in the Variable edit view. They allow you to fill a variable's options list.
| Name | Description |
| -------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------- |
@@ -151,7 +151,7 @@ types of template variables.
### Azure Monitor Metrics Whitelist
Not all metrics returned by the Azure Monitor API have values. The Grafana datasource has a whitelist to only return metric names if it is possible they might have values. This whitelist is updated regularly as new services and metrics are added to the Azure cloud. You can find the current whitelist [here](https://github.com/grafana/grafana/blob/master/public/app/plugins/datasource/grafana-azure-monitor-datasource/azure_monitor/supported_namespaces.ts).
Not all metrics returned by the Azure Monitor API have values. The Grafana data source has a whitelist to only return metric names if it is possible they might have values. This whitelist is updated regularly as new services and metrics are added to the Azure cloud. You can find the current whitelist [here](https://github.com/grafana/grafana/blob/master/public/app/plugins/datasource/grafana-azure-monitor-datasource/azure_monitor/supported_namespaces.ts).
### Azure Monitor Alerting
@@ -278,7 +278,7 @@ Not implemented yet.
### Writing Analytics Queries For the Application Insights Service
If you change the service type to "Application Insights", the menu icon to the right adds another option, "Toggle Edit Mode". Once clicked, the query edit mode changes to give you a full text area in which to write log analytics queries. (This is identical to how the InfluxDB datasource lets you write raw queries.)
If you change the service type to "Application Insights", the menu icon to the right adds another option, "Toggle Edit Mode". Once clicked, the query edit mode changes to give you a full text area in which to write log analytics queries. (This is identical to how the InfluxDB data source lets you write raw queries.)
Once a query is written, the column names are automatically parsed out of the response data. You can then select them in the "X-axis", "Y-axis", and "Split On" dropdown menus, or just type them out.
docs/sources/features/datasources/cloudwatch.md
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@@ -22,7 +22,7 @@ Grafana ships with built in support for CloudWatch. You just have to add it as a
3. Click the `+ Add data source` button in the top header.
4. Select `Cloudwatch` from the *Type* dropdown.
> NOTE: If at any moment you have issues with getting this datasource to work and Grafana is giving you undescriptive errors then don't
> NOTE: If at any moment you have issues with getting this data source to work and Grafana is giving you undescriptive errors then don't
forget to check your log file (try looking in /var/log/grafana/grafana.log).
Name | Description
@@ -136,11 +136,11 @@ types of template variables.
### Query variable
CloudWatch Datasource Plugin provides the following queries you can specify in the `Query` field in the Variable
CloudWatch data source plugin provides the following queries you can specify in the `Query` field in the Variable
edit view. They allow you to fill a variable's options list with things like `region`, `namespaces`, `metric names`
and `dimension keys/values`.
In place of `region` you can specify `default` to use the default region configured in the datasource for the query,
In place of `region` you can specify `default` to use the default region configured in the data source for the query,
e.g. `metrics(AWS/DynamoDB, default)` or `dimension_values(default, ..., ..., ...)`.
Read more about the available dimensions in the [CloudWatch Metrics and Dimensions Reference](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CW_Support_For_AWS.html).
@@ -251,11 +251,11 @@ it costs $0.01 per 1,000 GetMetricStatistics or ListMetrics requests. For each q
issue a GetMetricStatistics request and every time you pick a dimension in the query editor
Grafana will issue a ListMetrics request.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure datas ources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
Using a credentials file
```yaml
docs/sources/features/datasources/elasticsearch.md
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### Index settings
![Elasticsearch Datasource Details](/img/docs/elasticsearch/elasticsearch_ds_details.png)
![Elasticsearch data source details](/img/docs/elasticsearch/elasticsearch_ds_details.png)
Here you can specify a default for the `time field` and specify the name of your Elasticsearch index. You can use
a time pattern for the index name or a wildcard.
@@ -199,17 +199,17 @@ Finally, press the `Enter` key or the `Run Query` button to display your logs.
Once the result is returned, the log panel shows a list of log rows and a bar chart where the x-axis shows the time and the y-axis shows the frequency/count.
Note that the fields used for log message and level is based on an [optional datasource configuration](#logs-beta).
Note that the fields used for log message and level is based on an [optional data source configuration](#logs-beta).
### Filter Log Messages
Optionally enter a lucene query into the query field to filter the log messages. For example, using a default Filebeat setup you should be able to use `fields.level:error` to only show error log messages.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/graphite.md
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@@ -150,11 +150,11 @@ queries via the Dashboard menu / Annotations view.
Graphite supports two ways to query annotations. A regular metric query, for this you use the `Graphite query` textbox. A Graphite events query, use the `Graphite event tags` textbox,
specify a tag or wildcard (leave empty should also work)
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/influxdb.md
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@@ -216,11 +216,11 @@ For InfluxDB you need to enter a query like in the above example. You need to ha
part. If you only select one column you will not need to enter anything in the column mapping fields. The
Tags field can be a comma separated string.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this dat asource.
```yaml
apiVersion: 1
docs/sources/features/datasources/loki.md
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@@ -18,7 +18,7 @@ weight = 6
> Viewing Loki data in dashboard panels is not supported yet, but is being worked on.
Grafana ships with built-in support for Loki, Grafana's log aggregation system.
Just add it as a datasource and you are ready to query your log data in [Explore](/features/explore).
Just add it as a data source and you are ready to query your log data in [Explore](/features/explore).
## Adding the data source to Grafana
@@ -31,8 +31,8 @@ Just add it as a datasource and you are ready to query your log data in [Explore
| Name | Description |
| --------------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| _Name_ | The datasource name. This is how you refer to the datasource in panels, queries, and Explore. |
| _Default_ | Default datasource means that it will be pre-selected for new panels. |
| _Name_ | The data source name. This is how you refer to the data source in panels, queries, and Explore. |
| _Default_ | Default data source means that it will be pre-selected for new panels. |
| _URL_ | The URL of the Loki instance, e.g., `http://localhost:3100` |
| _Maximum lines_ | Upper limit for number of log lines returned by Loki (default is 1000). Decrease if your browser is sluggish when displaying logs in Explore. |
@@ -117,10 +117,10 @@ Template variables are not yet supported by Loki.
Annotations are not yet supported by Loki.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
You can set up the datasource via config files with Grafana's provisioning system.
You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
You can set up the data source via config files with Grafana's provisioning system.
You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here is an example:
docs/sources/features/datasources/mssql.md
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@@ -577,11 +577,11 @@ EXEC dbo.sp_test_datetime @from, @to
Time series queries should work in alerting conditions. Table formatted queries are not yet supported in alert rule
conditions.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/mysql.md
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@@ -358,11 +358,11 @@ tags | Optional field name to use for event tags as a comma separated string.
Time series queries should work in alerting conditions. Table formatted queries is not yet supported in alert rule conditions.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/opentsdb.md
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@@ -34,13 +34,13 @@ Name | Description
## Query editor
Open a graph in edit mode by click the title. Query editor will differ if the datasource has version <=2.1 or = 2.2.
Open a graph in edit mode by click the title. Query editor will differ if the data source has version <=2.1 or = 2.2.
In the former version, only tags can be used to query OpenTSDB. But in the latter version, filters as well as tags
can be used to query opentsdb. Fill Policy is also introduced in OpenTSDB 2.2.
![](/img/docs/v43/opentsdb_query_editor.png)
> Note: While using OpenTSDB 2.2 datasource, make sure you use either Filters or Tags as they are mutually exclusive. If used together, might give you weird results.
> Note: While using OpenTSDB 2.2 data source, make sure you use either Filters or Tags as they are mutually exclusive. If used together, might give you weird results.
### Auto complete suggestions
@@ -88,11 +88,11 @@ Query | Description
For details on OpenTSDB metric queries checkout the official [OpenTSDB documentation](http://opentsdb.net/docs/build/html/index.html)
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/postgres.md
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@@ -104,7 +104,7 @@ You may also enter arbitrary SQL expressions in the metric column field that eva
In the `SELECT` row you can specify what columns and functions you want to use.
In the column field you may write arbitrary expressions instead of a column name like `column1 * column2 / column3`.
The available functions in the query editor depend on the PostgreSQL version you selected when configuring the datasource.
The available functions in the query editor depend on the PostgreSQL version you selected when configuring the data source.
If you use aggregate functions you need to group your resultset. The editor will automatically add a `GROUP BY time` if you add an aggregate function.
The editor tries to simplify and unify this part of the query. For example:<br>
@@ -363,11 +363,11 @@ tags | Optional field name to use for event tags as a comma separated string.
Time series queries should work in alerting conditions. Table formatted queries are not yet supported in alert rule
conditions.
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/prometheus.md
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@@ -143,11 +143,11 @@ The step option is useful to limit the number of events returned from your query
Since 4.6.0 Grafana exposes metrics for Prometheus on the `/metrics` endpoint. We also bundle a dashboard within Grafana so you can get started viewing your metrics faster. You can import the bundled dashboard by going to the data source edit page and click the dashboard tab. There you can find a dashboard for Grafana and one for Prometheus. Import and start viewing all the metrics!
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here are some provisioning examples for this datasource.
Here are some provisioning examples for this data source.
```yaml
apiVersion: 1
docs/sources/features/datasources/stackdriver.md
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@@ -15,7 +15,7 @@ weight = 4
> Available as a beta feature in Grafana v5.3.x and v5.4.x.
> Officially released in Grafana v6.0.0
Grafana ships with built-in support for Google Stackdriver. Just add it as a datasource and you are ready to build dashboards for your Stackdriver metrics.
Grafana ships with built-in support for Google Stackdriver. Just add it as a data source and you are ready to build dashboards for your Stackdriver metrics.
## Adding the data source to Grafana
@@ -29,8 +29,8 @@ Grafana ships with built-in support for Google Stackdriver. Just add it as a dat
| Name | Description |
| --------------------- | ----------------------------------------------------------------------------------- |
| _Name_ | The datasource name. This is how you refer to the datasource in panels & queries. |
| _Default_ | Default datasource means that it will be pre-selected for new panels. |
| _Name_ | The data source name. This is how you refer to the data source in panels & queries. |
| _Default_ | Default data source means that it will be pre-selected for new panels. |
| _Service Account Key_ | Service Account Key File for a GCP Project. Instructions below on how to create it. |
## Authentication
@@ -39,7 +39,7 @@ There are two ways to authenticate the Stackdriver plugin - either by uploading
### Using a Google Service Account Key File
To authenticate with the Stackdriver API, you need to create a Google Cloud Platform (GCP) Service Account for the Project you want to show data for. A Grafana datasource integrates with one GCP Project. If you want to visualize data from multiple GCP Projects then you need to create one datasource per GCP Project.
To authenticate with the Stackdriver API, you need to create a Google Cloud Platform (GCP) Service Account for the Project you want to show data for. A Grafana data source integrates with one GCP Project. If you want to visualize data from multiple GCP Projects then you need to create one data source per GCP Project.
#### Enable APIs
@@ -68,7 +68,7 @@ Click on the links above and click the `Enable` button:
{{< docs-imagebox img="/img/docs/v53/stackdriver_service_account_choose_role.png" class="docs-image--no-shadow" caption="Choose role" >}}
5. Click the Create button. A JSON key file will be created and downloaded to your computer. Store this file in a secure place as it allows access to your Stackdriver data.
6. Upload it to Grafana on the datasource Configuration page. You can either upload the file or paste in the contents of the file.
6. Upload it to Grafana on the data source Configuration page. You can either upload the file or paste in the contents of the file.
{{< docs-imagebox img="/img/docs/v53/stackdriver_grafana_upload_key.png" class="docs-image--no-shadow" caption="Upload service key file to Grafana" >}}
@@ -222,9 +222,9 @@ Example Result: `monitoring.googleapis.com/uptime_check/http_status has this val
| `{{metric.label.xxx}}` | returns the metric label value | `{{metric.label.instance_name}}` | `grafana-1-prod` |
| `{{resource.label.xxx}}` | returns the resource label value | `{{resource.label.zone}}` | `us-east1-b` |
## Configure the Datasource with Provisioning
## Configure the data source with provisioning
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page](/administration/provisioning/#datasources)
Here is a provisioning example using the JWT (Service Account key file) authentication type.
docs/sources/features/explore/index.md
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@@ -19,13 +19,13 @@ One of the major new features of Grafana 6.0 is the new query-focused Explore wo
Grafana's dashboard UI is all about building dashboards for visualization. Explore strips away all the dashboard and panel options so that you can focus on the query. Iterate until you have a working query and then think about building a dashboard.
For infrastructure monitoring and incident response, you no longer need to switch to other tools to debug what went wrong. Explore allows you to dig deeper into your metrics and logs to find the cause. Grafana's new logging datasource, [Loki](https://github.com/grafana/loki) is tightly integrated into Explore and allows you to correlate metrics and logs by viewing them side-by-side. This creates a new debugging workflow where you can:
For infrastructure monitoring and incident response, you no longer need to switch to other tools to debug what went wrong. Explore allows you to dig deeper into your metrics and logs to find the cause. Grafana's new logging data source, [Loki](https://github.com/grafana/loki) is tightly integrated into Explore and allows you to correlate metrics and logs by viewing them side-by-side. This creates a new debugging workflow where you can:
1. Receive an alert
2. Drill down and examine metrics
3. Drill down again and search logs related to the metric and time interval (and in the future, distributed traces).
If you just want to explore your data and do not want to create a dashboard then Explore makes this much easier. Explore will show the results as both a graph and a table enabling you to see trends in the data and more detail at the same time (if the datasource supports both graph and table data).
If you just want to explore your data and do not want to create a dashboard then Explore makes this much easier. Explore will show the results as both a graph and a table enabling you to see trends in the data and more detail at the same time (if the data source supports both graph and table data).
## How to Start Exploring
@@ -37,13 +37,13 @@ If you want to start with an existing query in a panel then choose the Explore o
{{< docs-imagebox img="/img/docs/v60/explore_panel_menu.png" class="docs-image--no-shadow" caption="Screenshot of the new Explore option in the panel menu" >}}
Choose your datasource in the dropdown in the top left. Prometheus has a custom Explore implementation, the other datasources (for now) use their standard query editor.
Choose your data source in the dropdown in the top left. Prometheus has a custom Explore implementation, the other data sources (for now) use their standard query editor.
The query field is where you can write your query and explore your data. There are three buttons beside the query field, a clear button (X), an add query button (+) and the remove query button (-). Just like the normal query editor, you can add and remove multiple queries.
## Split and Compare
The Split feature is an easy way to compare graphs and tables side-by-side or to look at related data together on one page. Click the split button to duplicate the current query and split the page into two side-by-side queries. It is possible to select another datasource for the new query which for example, allows you to compare the same query for two different servers or to compare the staging environment to the production environment.
The Split feature is an easy way to compare graphs and tables side-by-side or to look at related data together on one page. Click the split button to duplicate the current query and split the page into two side-by-side queries. It is possible to select another data source for the new query which for example, allows you to compare the same query for two different servers or to compare the staging environment to the production environment.
{{< docs-imagebox img="/img/docs/v60/explore_split.png" class="docs-image--no-shadow" caption="Screenshot of the new Explore option in the panel menu" >}}
@@ -110,7 +110,7 @@ If you switch from a Prometheus query to a logs query (you can do a split first
`grafana_alerting_active_alerts{job="grafana"}`
after switching to the Logs datasource, the query changes to:
after switching to the Logs data source, the query changes to:
`{job="grafana"}`
docs/sources/features/panels/graph.md
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@@ -38,7 +38,7 @@ Repeat a panel for each value of a variable. Repeating panels are described in
## Metrics
The metrics tab defines what series data and sources to render. Each datasource provides different
The metrics tab defines what series data and sources to render. Each data source provides different
options.
## Axes
docs/sources/features/panels/heatmap.md
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@@ -60,9 +60,9 @@ Data format | Description
### Bucket bound
When Data format is *Time series buckets* datasource returns series with names representing bucket bound. But depending
on datasource, a bound may be *upper* or *lower*. This option allows to adjust a bound type. If *Auto* is set, a bound
option will be chosen based on panels' datasource type.
When Data format is *Time series buckets* data source returns series with names representing bucket bound. But depending
on data source, a bound may be *upper* or *lower*. This option allows to adjust a bound type. If *Auto* is set, a bound
option will be chosen based on panels' data source type.
### Bucket Size
@@ -77,9 +77,9 @@ If you have a data that is already organized into buckets you can use the `Time
requires that your metric query return regular time series and that each time series has a numeric name that represent
the upper or lower bound of the interval.
There are a number of datasources supporting histogram over time like Elasticsearch (by using a Histogram bucket
There are a number of data sources supporting histogram over time like Elasticsearch (by using a Histogram bucket
aggregation) or Prometheus (with [histogram](https://prometheus.io/docs/concepts/metric_types/#histogram) metric type
and *Format as* option set to Heatmap). But generally, any datasource could be used if it meets the requirements:
and *Format as* option set to Heatmap). But generally, any data source could be used if it meets the requirements:
returns series with names representing bucket bound or returns series sorted by the bound in ascending order.
With Elasticsearch you control the size of the buckets using the Histogram interval (Y-Axis) and the Date Histogram interval (X-axis).
docs/sources/features/panels/table_panel.md
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@@ -22,7 +22,7 @@ To view table panels in action and test different configurations with sample dat
## Querying Data
The table panel displays the results of a query specified in the **Metrics** tab.
The result being displayed depends on the datasource and the query, but generally there is one row per datapoint, with extra columns for associated keys and values, as well as one column for the numeric value of the datapoint.
The result being displayed depends on the data source and the query, but generally there is one row per datapoint, with extra columns for associated keys and values, as well as one column for the numeric value of the datapoint.
You can change the behavior in the section **Data to Table** below.
### Merge Multiple Queries per Table
@@ -35,7 +35,7 @@ In this example usage and capacity are metrics that will have corresponding data
In its simplest case, both queries return time-series data with a numeric value and a timestamp.
If the timestamps are the same, datapoints will be matched and rendered on the same row.
Some datasources return keys and values (labels, tags) associated with the datapoint.
Some data sources return keys and values (labels, tags) associated with the datapoint.
These are being matched as well if they are present in both results and have the same value.
The following datapoints will end up on the same row with one time column, two label columns ("host" and "job") and two value columns: