What this book covers
Chapter 1, Introducing Data Visualization with Grafana, provides a brief introduction to the use of data visualization in general and specifically in Grafana. We will then move on to installing a Grafana server onto your machine, using either a native installer or a Docker container. Launching the server and connecting to it with a web browser will also be covered.
Chapter 2, Touring the Grafana Interface, will explore the workings of the major UI components after you have launched and connected to the Grafana web application. We will look at the search bar, side menu, and Home dashboard.
Chapter 3, Diving into Grafana's Time Series Visualization, will dive into the Time series panel visualization for a closer look at how to work with the major components of the main Grafana visualization. After connecting to a test data source, we will also identify common panel components in preparation for working with other visualizations.
Chapter 4, Connecting Grafana to a Prometheus Data Source, will show you how to launch the Prometheus time-series database from a Docker container, load an actual time-series dataset, and query and visualize data in Grafana.
Chapter 5, Extracting and Visualizing Data with InfluxDB and Grafana, will show how to write a simple Python Extract, Transform, and Load (ETL) script to access data from a public data server and push it to InfluxDB. We’ll also connect Grafana to InfluxDB and try out some more advanced query techniques.
Chapter 6, Shaping Data with Grafana Transformations, will introduce the concept of the Grafana data frame, and how the different Grafana transformations can shape query data. We’ll also chain transformations into a more complex data pipeline.
Chapter 7, Surveying Key Grafana Visualizations, will see us use the Table, Stat, Bar Gauge, and Gauge panel visualizations to display our weather data.
Chapter 8, Surveying Additional Grafana Visualizations, will see us modify the Python ETL script to download earthquake data. We’ll visualize the data using Geomap, Bar chart, Histogram, and Heatmap visualizations.
Chapter 9, Creating Insightful Dashboards, uses what we’ll have learned about Grafana panel visualizations and some basic information design principles to create production dashboards for visualizing weather and earthquake data.
Chapter 10, Working with Advanced Dashboard Features and Elasticsearch, explores the powerful advanced features of the dashboard, including annotations, templating with variables, and dashboard linking, as well as techniques for sharing dashboards. We’ll pull down public data from the city of San Francisco and use Logstash and Elasticsearch as the data source.
Chapter 11, Streaming Real-Time IoT Data from Telegraf Agent to Grafana Live, will present the first in a trilogy of chapters on observability by introducing the concept of real-time data streaming. We’ll build a data pipeline to stream data from an Internet of Things (IoT) simulator using standard MQTT protocols and then use InfluxDB to send the messages to Grafana Explore.
Chapter 12, Monitoring Data Streams with Grafana Alerts, will show you how to take streaming data, monitor it for anomalies with alerting rules, and connect those alerts to a set of notification channels, including email, PagerDuty, and Slack.
Chapter 13, Exploring Log Data with Grafana’s Loki, will complete the observability trilogy by showing how to capture observability metrics and logs with the combination of Promtail and Loki. We’ll perform an ad hoc analysis with Explore to check for correlations between metrics patterns and logging events.
Chapter 14, Organizing Dashboards and Folders, will show you how to label dashboards and organize them into folders to make them easier to find. We’ll also look at other dashboard features, such as starred dashboards, dashboard playlists, and the Dashboard list panel visualization.
Chapter 15, Managing Permissions for Users, Teams, and Organizations, will show you how to manage users, teams, and organizations, including access control and user addition and deletion.
Chapter 16, Authenticating Grafana Logins Using LDAP or OAuth 2 Providers, will show you how managers can connect Grafana user authentication to a variety of services. We’ll authenticate using an internal LDAP server and use OAuth 2 to authenticate using external services from GitHub, Google, and Okta.
Chapter 17, Cloud Monitoring AWS, Azure, and GCP, will show how Grafana can provide monitoring support for a variety of services provided by major cloud platforms, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
