Grafana and Prometheus: Data Integration and Advanced Visualization

• Experience with system monitoring or DevOps tools
• Familiarity with Linux environments and command-line usage
• Understanding of time-series data and basic networking

Audience

• System and network administrators
• DevOps and site reliability engineers
• Monitoring and observability teams

Grafana and Prometheus are industry-standard tools used to monitor, visualize, and alert on IT infrastructure and application metrics through real-time dashboards and integrations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level IT professionals who wish to integrate Grafana with Prometheus and multiple data sources, and build actionable visualizations and alerts across distributed systems.

By the end of this training, participants will be able to:

• Install and configure Grafana and Prometheus in production-ready setups.
• Integrate multiple data sources including SQL, Elasticsearch, InfluxDB, and cloud APIs.
• Create advanced dashboards with variables, templating, transformations, and alerts.
• Apply best practices in data modeling, performance tuning, and user access control.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Grafana and Prometheus

• Architecture overview and use cases
• Installing and configuring Prometheus and Grafana
• Overview of exporters and the Prometheus query language (PromQL)

Data Source Integration

• Connecting Prometheus to Grafana
• Integrating with Elasticsearch, InfluxDB, PostgreSQL, MySQL, and Loki
• Using JSON, CSV, and external API plugins

Working with Dashboards

• Creating and importing dashboards
• Using panels: graphs, tables, heatmaps, and stat visualizations
• Creating reusable templates with variables and filters

Advanced Querying and Data Transformation

• Writing and optimizing PromQL queries
• Using transformations, math, aliases, and derived fields
• Combining multiple data sources into a single view

Alerting and Notifications

• Configuring alert rules and thresholds
• Using Alertmanager and setting alert receivers (email, Slack, webhook, etc.)
• Managing alert silences and grouping

Performance and Scaling Considerations

• Optimizing dashboard performance and caching
• Scaling Prometheus with federation and long-term storage
• Best practices for data retention and disk usage

Access Control and Collaboration

• Setting up users, roles, and teams
• Configuring permissions and secure sharing
• Version control and dashboard provisioning

Summary and Next Steps