About the Course

The course offers an in-depth dive into modern observability approaches based on the Grafana ecosystem. You will master the collection and analysis of telemetry (metrics, logs, distributed traces), work with Grafana Loki, Mimir, and Tempo components, learn how to create informative dashboards, configure alerts, and automate platform deployment.

Target Audience

• DevOps Engineers
• System Administrators
• Site Reliability Engineers (SRE)
• Developers looking to improve application observability

Key Benefits

The course is designed for practicing engineers aiming to implement modern monitoring and observability practices in their companies. A large volume of hands-on exercises using real-world examples with the free tier of Grafana Cloud.

Day 1. Observability Fundamentals and Working with Grafana

First half (theory)

• Concept of observability, components of the Grafana stack.
• How to instrument applications and infrastructure for telemetry collection.
• Introduction to setting up the learning environment, exploring Grafana Cloud capabilities, demo application: OpenTelemetry Astronomy Shop.

Second half (practice)

• Setting up the learning environment for working with Grafana using the free Grafana Cloud tier.
• Installing the OpenTelemetry demo application according to the guide.
• Deploying necessary services and collecting telemetry (metrics, logs, distributed traces) in real time.
• Hands-on practice with the Grafana interface, basic data display elements (timeline, service and operation list, color coding for operation duration).
Day 2. Working with Logs, Metrics, and Traces

First half (theory)

• Principles of working with logs in Grafana Loki.
• Monitoring using metrics, exploring Grafana Mimir and Prometheus.
• Features of tracing with Grafana Tempo, its architecture, and horizontal scaling principles.
• Approaches to collecting data from infrastructure (using examples).

Second half (practice)

• Hands-on log analysis using Grafana Loki.
• Setting up metric monitoring with Grafana Mimir and Prometheus, creating simple dashboards to display key metrics.
• Working with tracing in Grafana Tempo: exploring trace visualization, analyzing operation duration, identifying bottlenecks.
• Collecting data from a test infrastructure.
Day 3. Data Visualization and Automation

First half (theory)

• Integration with cloud platforms and best practices for data collection.
• Principles of data visualization, building dashboards in Grafana.
• Approaches to incident management using alerts.
• Exploring automation methods (using Terraform, Ansible), approaches to designing an observability platform.

Second half (practice)

• Creating several Grafana dashboards to display collected metrics, logs, and traces — hands-on data visualization using different chart types and panels.
• Configuring an alerting system to monitor key metrics and automatically notify about issues.
• Experiments with automating dashboard deployment using Terraform or Ansible.
• Creating a comprehensive monitoring scenario for a test application, including data collection, visualization, and alerting.