Grafana: Data Visualization and Monitoring  (GRAF1)

Virtualization, Kubernetes

Are you looking to effectively visualize and monitor your data in real-time? Grafana is a powerful open-source platform for monitoring and observability, enabling you to create dynamic, interactive dashboards from a variety of data sources. This course provides a practical introduction to Grafana, including installation, data source integration, dashboard creation, and alerting. You’ll gain hands-on experience with key features and best practices for using Grafana in a professional environment. By the end of this course, participants will be able to install Grafana, configure it with different data sources, create interactive dashboards, and set up alerts to monitor key metrics.

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The course:

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  • Why Data Visualization and Grafana? 
    1. Importance of visualizing data for real-time monitoring. 
    2. Introduction to Grafana and its core features. 
    3. Use cases of Grafana in various environments. 
  • Installing Grafana 
    1. Installation on Linux. 
    2. Configuring Grafana for Kubernetes environments (optional). 
    3. Initial configuration and security settings. 
  • Data Sources 
    1. Overview of supported data sources. 
    2. Connecting Grafana with Prometheus, Loki, and PCP. 
    3. (Optional: focus on Prometheus if preferred for specific training needs). 
  • Building and Customizing Dashboards 
    1. Creating and importing dashboards. 
    2. Using variables for dynamic dashboards. 
    3. Working with panels: visualizations, graphs, and other data displays. 
    4. Best practices for building effective dashboards. 
  • Alerting in Grafana 
    1. Setting up alerting rules. 
    2. Integrating notifications: email, Slack, and other platforms. 
    3. Managing and monitoring alerting within dashboards. 
  • (Optional for Kubernetes) Grafana Operator and CRDs 
    1. Overview of the Grafana Operator for Kubernetes. 
    2. Using Custom Resource Definitions (CRD) for advanced configuration. 
    3. Managing Grafana instances in a Kubernetes environment. 
Schedule:
1 day (9:00 AM - 5:00 PM )
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