Data sources writing guide

Open source

Last reviewed: September 15, 2025

Data sources writing guide

Grafana offers almost 400 data sources to Grafana users, both open source and enterprise. While many are maintained by Grafana, others are maintained by Grafana Champions and other users or companies that partner with Grafana Labs.

Enterprise plugins reside in the grafana/plugins-private repository, which is a private repository. Other plugins have their own separate repos, and you need to clone each repo to work on data source documentation updates. These repositories are sometimes also private.

General writing guidance

Use active voice and present tense. Refer to Voice and tone guidelines for more information.
Refer to Style conventions for guidance on writing techniques.
Refer to the Style guide for content style guidelines.

Structure documentation with topics

In the past, a data source document tended to be one long document containing background, requirements, configuration options, query editor options and templates and variables. To make information easier to find, the technical writing team, with agreement from product management and engineering, decided to refactor the documentation into separate topics. If a customer wants to know how to configure the data source, it’s easier to go directly to that topic page rather than wade through one long document where lots of scrolling is required.

Introduction document

This document introduces the data source and serves as the “landing page” that users encounter first.

File structure:

File name: _index.md
Location: Main data source directory

This document should include the following information:

What is this data source?
- Provide a clear, concise description of the data source.
- Include some primary use cases and capabilities.
What’s unique about this data source in general? Introduce these features or concepts. For example, Prometheus uses exemplars.
What’s unique about working with this data source in Grafana?
Is there native support for this data source or does the user need to install a plugin?
What are the best practices when working with this data source?
Are there any requirements or prerequisites for adding the data source.
- Example of a prerequisite: Salesforce requires a Salesforce Connected App.
- Include minimum version requirements.
What are any known limitations the user needs to be aware of?
Link to configure, query editor, etc,
- configure the data source topic
- query editor topic
- templates and variable topic
- other data source-related topics
What can the user do after they’ve configured this data source?
- Add links to relevant documentation, such as for using variables or annotations, or configuring alerting.
Any details regarding pre-made dashboards for the data source, and how to find these dashboards
Add a “Next steps” section at the end of the page with links to the following:
- Add annotations
- Add transformations
- Set up alerting
- Additional things you can do with the specific data source
Standard text:

“Get the most out of the data source

Once you have connected the data source, you can:

Use the [query editor](add link tot he data source’s query editor doc) to create and edit queries.
Create a wide variety of visualizations.
Configure and use Templates and variables.
Add Transformations.
Set up alerting; refer to Alerts overview.
Add Annotations.


If the data source requires plugin installation, add this to the end of this introduction document.

Standard text:

```markdown
Always ensure your plugin version is up-to-date to access all current features. Navigate to **Plugins and data > Plugins** to check for updates.

Configure document

The Configure document describes how to configure the data source and should serve as a comprehensive setup guide for users.

File structure:

File name: configure.md
Location: Main data source directory
menuTitle: Configure
title: Configure the data source

This document should include:

Introduction paragraph.

Standard text:

This document provides instructions for configuring the <DATA SOURCE NAME> data source and explains available configuration options.
For general information on managing data sources, refer to [Data source management](/docs/grafana/latest/administration/data-source-management/).

“Before you begin” section. Include any prerequisites necessary before configuring the data source.
- Native support availability.
- Plugin installation requirements with a link to installation instructions. This applies to any non-core data source.
- Note that the Organization administrator role is required to add a data source.
- Is a separate account needed for the data source?
- Any prerequisites that may be unique to the data source. For example, Salesforce requires that a specific account be created prior to connecting to Grafana.
- Know your authentication method such as, API key, OAuth 2.0, or certificates. Have your security keys and certificates handy.

Explain how to configure the specific data source using the UI section.

Step-by-step setup instructions using the UI.
Describe each configuration option or setting.
Include examples like connection strings.
If the data source supports private data source connect (PDC):

Standard text:

- **Private data source connect** - _Only for Grafana Cloud users._ Private data source connect, or PDC, allows you to establish a private, secured connection between a Grafana Cloud instance, or stack, and data sources secured within a private network.
Click the drop-down to locate the URL for PDC.
For more information regarding Grafana PDC, refer to [Private data source connect (PDC)](https://grafana.com/docs/grafana-cloud/connect-externally-hosted/private-data-source-connect/) and [Configure Grafana private data source connect (PDC)](https://grafana.com/docs/grafana-cloud/connect-externally-hosted/private-data-source-connect/configure-pdc/) for instructions on setting up a PDC connection.
Click **Manage private data source connect ** to open your PDC connection page and view your configuration details.

Describe the success message or expected validation outcome.
How to provision the data source with YAML section.
Standard text:

You can define and configure the data source in YAML files as part of the Grafana provisioning system. For more information about provisioning and available configuration options, refer to [Provision Grafana](https://grafana.com/docs/grafana/latest/administration/provisioning/#data-sources).

Add instructions for provisioning via YAML.
Include a working example or examples.
How to provision the data source with Terraform section (if applicable).
- Reference the Grafana Terraform Provider.
- Provide an example Terraform configuration.
Troubleshooting configuration issues section.
- List common issues and how to resolve them.
- What can users try before contacting support?
- How to confirm a working connection in Explore.

Query editor document

The query editor is part of the Explore page. It’s the section where you create the query, either by a visual query builder or via a field where you add your query and some additional query options. Some query editors don’t include a visual query builder, such as MongoDB or Jira. Datadog and Prometheus have very detailed query builders.

File structure:

File name: query-editor.md
Location: Main data source directory
menuTitle: Query editor
title: Query editor

This document should include:

Where to access the query editor. For example, in Grafana Explore or dashboard panels.

Standard text:

  Grafana provides a query editor for the <INSERT NAME> data source, which allows you to query, visualize, and alert on logs and metrics stored in Amazon CloudWatch.
  It's located on the [Explore](/docs/grafana/latest/explore/) page.
  For general documentation on querying data sources in Grafana, refer to [Query and transform data](/docs/grafana/latest/panels-visualizations/query-transform-data/).

Available query modes.
- Visual query builder or raw query (Builder and Code mode).
- What query types are supported?
  - Table
  - Time series
Explain how to build queries using the editor.
Describe each query editor option. This should include a description of each query type, an explanation of what each component or field is, and include examples where appropriate. -Highlight data source-specific components or syntax. Provide examples for each component where applicable.
Include example queries of different complexities.
Any other information useful when working with the query editor, such as information on aggregations or aggregating data.
Are Grafana macros supported?
- Provide a table of supported macros with examples.
- Provide an example of a query with a macro.
Recorded queries
- Does this data source support recorded queries?
- If yes, how to configure and use them.
Validating and troubleshooting queries
- How to check syntax and test queries.
- What to do when queries fail.

Template variables document

This document explains templates and variables associated with the data source.

File structure:

File name: template-variables.md
Location: Main data source directory
menuTitle: Template variables
title: template variables

This document should include the following information:

What are variables?

Standard text:

Instead of hard-coding details such as server, application, and sensor names in metric queries, you can use variables.
Grafana lists these variables in drop-down selection boxes at the top of the dashboard to help you change the data displayed in your dashboard.
Grafana refers to such variables as template variables.

For an introduction to templating and template variables, refer to [Template variables](https://grafana.com/docs/grafana/latest/dashboards/variables/#templates) and [Add variables](https://grafana.com/docs/grafana/latest/dashboards/variables/add-template-variables/#add-variables).

What types of variables are supported with this data source?
- Query variables, custom variables, interval variables, or any other kinds of variables.
Provide syntax and examples.
Provide usage tips and options.
Common issues with variables and how to fix them.

Annotations document

Add annotations, graphs, and dashboards to provide contextual information about specific points in time. This document describes how annotations work with this data source.

File structure:

File name: annotations.md
Location: Main data source directory
menuTitle: Annotations
title: Annotations and

This document should include the following information:

Overview - What are annotations in Grafana?

Standard text:

Annotations in Grafana are visual markers that you can add to your graphs and dashboards to provide context about specific events or time periods. They appear as vertical lines or regions on your time-series charts, helping you correlate metrics with real-world events.

For general information on annotations, refer to [Annotate visualizations](/docs/grafana/latest/dashboards/build-dashboards/annotate-visualizations/).

What types of annotations can you create for this data source?
Are there any limitations to using annotations with this data source?
Querying for annotations
- Field requirements: time, text, tags, optional timeEnd
Provide one or two example annotation queries.
Configuration
- How to add annotation queries to a dashboard.
- UI steps and important settings.
Troubleshooting
- Common problems and how to resolve them.

Grafana Alerting document

Can you use this data source with Grafana Alerting? Create alerts for metrics data or log entries and configure Grafana Alerting to alert on that information.

File structure:

File name: alerting.md
Location: Main data source directory
menuTitle: Grafana Alerting
title: Alerting and

This document should include the following information:

Standard text:

Grafana Alerting is a powerful system for monitoring your metrics and receiving notifications when certain conditions are met. It's designed to help you proactively identify and respond to issues in your infrastructure and applications.

For general information on alerting in Grafana refer to [Grafana Alerting](/docs/grafana/latest/alerting/).

What kinds of alerts can you create with this data source?
Setup
- Describe how to create an alert rule using this data source.
- List all query types compatible with alerts.
- Describe UI steps for creating and configuring alerts.
- List any notification types unique to the data source.
- Special considerations for this data source.
Troubleshooting
- Known limitations or common alerting issues.
- Tips for debugging alert rules.

Troubleshoot document

This document provides troubleshooting steps users can try before opening a support case. If support is still needed, users can reference this list to show what they’ve already attempted.

File structure:

File name: troubleshooting.md
Location: Main data source directory
menuTitle: Troubleshoot
title: Troubleshoot issues with the data source

This document should include the following information:

Standard text:

This document provides troubleshooting guidance for the <DATA SOURCE NAME> data source, covering common configuration problems, error messages, and other frequently encountered issues.

Common connection issues when configuring the data source.
- List any common connection issues with this data source.
- Provide a list of connection error messages and how to troubleshoot them.
- Possible causes - Why might this happen?
Logs and diagnostics.
- Where can the user find relevant logs to help with troubleshooting?
- Explain how to interpret common error messages in logs.
- Add step-by-step resolutions. Provide the specific actions to take.
Troubleshooting checklist.
- Include a troubleshooting checklist that users can work through systematically and attach to support cases when needed.

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