Docs: Sync latest master docs with 7.5.x (#33156)
* Docs: Sync latest master docs with 7.5.x * remove some remaining next aliases and links * Docs: Removed v8 doc changes * fixed merge issue
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Torkel Ödegaard
@@ -8,9 +8,7 @@ aliases = ["/docs/grafana/latest/guides/what-is-grafana"]
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This section provides a high-level look at Grafana, the Grafana process, and Grafana features. It's a good place to learn how to use the Grafana software.
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## What is Grafana?
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Grafana is open source visualization and analytics software. It allows you to query, visualize, alert on, and explore your metrics no matter where they are stored. In plain English, it provides you with tools to turn your time-series database (TSDB) data into beautiful graphs and visualizations.
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{{< docs/shared "basics/what-is-grafana.md" >}}
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After creating a dashboard like you do in [Getting started]({{< relref "getting-started.md" >}}), there are many possible things you might do next. It all depends on your needs and your use case.
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@@ -74,16 +72,6 @@ Refer to [Provisioning]({{< relref "../administration/provisioning.md" >}}) for
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When organizations have one Grafana and multiple teams, they often want the ability to both keep things separate and share dashboards. You can create a team of users and then set [permissions]({{< relref "../permissions/_index.md" >}}) on folders, dashboards, and down to the [data source level]({{< relref "../enterprise/datasource_permissions.md" >}}) if you're using [Grafana Enterprise]({{< relref "../enterprise/_index.md" >}}).
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## Grafana Cloud
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{{< docs/shared "basics/grafana-cloud.md" >}}
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Grafana Cloud is a highly available, fast, fully managed OpenSaaS logging and metrics platform. Everything you love about Grafana, but Grafana Labs hosts it for you and handles all the headaches.
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[Learn more about Grafana Cloud](https://grafana.com/cloud/) or try the [Grafana Cloud Linux host Quickstart](/docs/grafana-cloud/quickstart/).
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## Grafana Enterprise
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[Grafana Enterprise]({{< relref "../enterprise/_index.md" >}}) is a commercial edition of Grafana that includes additional features not found in the open source version.
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Building on everything you already know and love about Grafana, Grafana Enterprise adds enterprise data sources, advanced authentication options, more permission controls, 24x7x365 support, and training from the core Grafana team.
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[Learn more about Grafana Enterprise](https://grafana.com/enterprise). To purchase Enterprise or obtain a trial license, contact the Grafana Labs [Sales Team](https://grafana.com/contact?about=support&topic=Grafana%20Enterprise).
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{{< docs/shared "basics/grafana-enterprise.md" >}}
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@@ -12,16 +12,12 @@ Prometheus is an open source systems monitoring system for which Grafana provide
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You can also configure a [Grafana Cloud](https://grafana.com/docs/grafana-cloud/) instance to display system metrics without having to host Grafana yourself.
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## Step 1. Install Grafana and build your first dashboard
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Use the instructions in [Getting started with Grafana]({{< relref "getting-started.md" >}}) to:
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- Install Grafana.
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- Log in to Grafana.
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- Create your first dashboard.
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{{< docs/shared "getting-started/first-step.md" >}}
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## Step 2. Download Prometheus and node_exporter
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Prometheus, like Grafana, can be installed on many different operating systems. Refer to the [Prometheus download page](https://prometheus.io/download/), which lists all stable versions of Prometheus components. Download the following components:
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- [Prometheus](https://prometheus.io/download/#prometheus)
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- [node_exporter](https://prometheus.io/download/#node_exporter)
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@@ -9,51 +9,27 @@ weight = 400
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# Getting started with Grafana and MS SQL Server
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Microsoft SQL Server is a popular relational database management system that is widely used in development and production environments. This topic walks you through the steps to create a series of dashboards in Grafana to display metrics from a MS SQL Server database. You can also configure the MS SQL Server data source on a [Grafana Cloud](https://grafana.com/docs/grafana-cloud/) instance without having to host Grafana yourself.
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## Step 1. Install Grafana and build your first dashboard
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Use the instructions in [Getting started with Grafana]({{< relref "getting-started.md" >}}) to:
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- Install Grafana.
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- Log in to Grafana.
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- Create your first dashboard.
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{{< docs/shared "getting-started/first-step.md" >}}
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> **Note:** You must install Grafana 5.1+ in order to use the integrated MS SQL data source.
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## Step 2. Download MS SQL Server
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MS SQL Server can be installed on many different operating systems. Refer to the [MS SQL Server downloads page](https://www.microsoft.com/en-us/sql-server/sql-server-downloads), for a complete list of all available options.
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Alternately, if you are working on Mac or Linux, then you can install MS SQL Server using the resources available in [grafana/grafana](https://github.com/grafana/grafana) GitHub repository (recommended). Here you will find a collection of supported data sources, including MS SQL Server, along with test data and pre-configured dashboards for use.
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> **Note:** Installing MS SQL Server on Windows from the [grafana/grafana](https://github.com/grafana/grafana/tree/master/devenv) GitHub repository is not supported at this time.
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MS SQL Server can be installed on Windows or Linux operating systems and also on Docker containers. Refer to the [MS SQL Server downloads page](https://www.microsoft.com/en-us/sql-server/sql-server-downloads), for a complete list of all available options.
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## Step 3. Install MS SQL Server
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You can install MS SQL Server on the host running Grafana or on a remote server. To install the software from the [downloads page](https://www.microsoft.com/en-us/sql-server/sql-server-downloads), follow their setup prompts.
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Otherwise, follow the instructions below to install and configure MS SQL Server from the [grafana/grafana](https://github.com/grafana/grafana/tree/master) repository.
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1. Clone the [grafana/grafana](https://github.com/grafana/grafana/tree/master) repository to your local system.
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1. Install Docker or verify that it is installed on your machine.
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1. Within your local `grafana` repository, change directory to [devenv](https://github.com/grafana/grafana/tree/master/devenv).
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1. Run the bash command to setup data sources and dashboards.
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```
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./setup.sh
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```
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1. Restart the Grafana server.
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1. Change directory back to [master](https://github.com/grafana/grafana/tree/master/devenv).
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1. Run the make command to create the MS SQL Server database.
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```
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make devenv sources=mssql
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```
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This creates an image of the SQL Server database and runs it as a Docker container.
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If you are on a Windows host but want to use Grafana and MS SQL data source on a Linux environment, refer to the [WSL to set up your Grafana development environment](https://grafana.com/blog/2021/03/03/.how-to-set-up-a-grafana-development-environment-on-a-windows-pc-using-wsl). This will allow you to leverage the resources available in [grafana/grafana](https://github.com/grafana/grafana) GitHub repository. Here you will find a collection of supported data sources, including MS SQL Server, along with test data and pre-configured dashboards for use.
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## Step 4. Adding the MS SQL data source
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To add MS SQL Server data source:
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1. In the Grafana side menu, hover your cursor over the **Configuration** (gear) icon and then click **Data Sources**.
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1. Filter by `mssql` and select the **Microsoft SQL Server** option.
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2. Click **Add data source** in the top right header to open the configuration page.
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3. Enter the information specified in the table below, then click **Save & Test**.
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1. Click **Add data source** in the top right header to open the configuration page.
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1. Enter the information specified in the table below, then click **Save & Test**.
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Name | Description
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------------ | -------------
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@@ -73,6 +49,7 @@ Optionally, play around this dashboard and customize it to:
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- Change frequency of data polling.
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- Change the period for which the data is displayed.
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- Rearrange and resize panels.
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## Step 5. Start building dashboards
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Now that you have gained some idea of using the pre-packaged MS SQL data source and some test data, the next step is to setup your own instance of MS SQL Server database and data your development or sandbox area. In the previous steps, if you followed along the path of deploying your own instance of MS SQL Server, you are already on your way.
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