1. Introduction

1.1 Tutorial Goal

The goal of this tutorial is to guide you through the process of setting up Grafana and creating dashboards to visualize data. Grafana is a multi-platform open-source analytics and interactive visualization web application. It provides charts, graphs, and alerts for the web when connected to supported data sources.

1.2 Learning Outcomes

By the end of this tutorial, you will be able to:

• Install and set up Grafana
• Connect Grafana to multiple data sources
• Create and customize dashboards to visualize data

1.3 Prerequisites

• Basic understanding of data visualization
• Basic knowledge of databases
• A system with internet access

2. Step-by-Step Guide

2.1 Installing Grafana

First, you need to download and install Grafana. You can find the installation guide for various platforms on the official Grafana Installation Documentation.

2.2 Setting Up Grafana

After installation, you can access Grafana on your browser at http://localhost:3000. The default username and password are both "admin".

2.3 Adding Data Sources

To connect a data source:

1. Click on the Grafana icon in the top left corner of the screen, then select "Data Sources" in the left-hand menu.
2. Click on "Add data source", and select your data source from the list.

You'll need to provide the necessary information to connect to the data source. This can vary depending on the data source you're connecting to.

2.4 Creating Dashboards

Once your data source is connected, you can start creating dashboards:

1. Click on the Grafana icon, then select "Dashboards" > "New".
2. Select the type of visualization you want, then customize it with your data.

3. Code Examples

Grafana primarily uses a UI for creating dashboards, so there are no code snippets to provide in this context.

However, you can use Grafana's API to interact with Grafana programmatically. For example, you can create a dashboard with the API like this:

import requests

url = 'http://localhost:3000/api/dashboards/db'
headers = {
    'Authorization': 'Bearer <your_api_key>',
    'Content-Type': 'application/json'
}
data = {
    'dashboard': {
        'id': None,
        'title': 'New dashboard',
        'tags': ['temp'],
        'timezone': 'browser',
        'schemaVersion': 16,
        'version': 0
    },
    'folderId': 0,
    'overwrite': False
}

response = requests.post(url, headers=headers, json=data)

This Python script sends a POST request to the Grafana API to create a new dashboard. Replace <your_api_key> with your actual Grafana API key.

4. Summary

In this tutorial, you've learned how to install Grafana, connect it to data sources, and create dashboards for data visualization. You've also seen an example of how to interact with Grafana programmatically using the API.

For further learning, you can explore more advanced features of Grafana like alerting, annotations, and plugins. Check out the Grafana Documentation for more information.

5. Practice Exercises

Exercise 1

Create a dashboard that visualizes the CPU usage of your machine over time. Use Prometheus as your data source.

Exercise 2

Using Grafana's API, write a script that automatically creates a new dashboard with a single panel that shows the current time.

Exercise 3

Set up an alert on one of your dashboards that sends an email when a certain condition is met. For example, if the CPU usage goes over 80%.

Refer to the Grafana Documentation for instructions on how to create alerts.