Open source observability explained - the Grafana Labs stack

Introduction

This tutorial provides a comprehensive guide to open-source observability using the Grafana Labs stack. It outlines how various tools work together to achieve continuous reliability in monitoring systems. This information is valuable for developers and system administrators looking to enhance their observability practices.

Step 1: Identifying Data to Collect

Understanding what data to collect is essential for effective observability. Here's how to approach this:

• Logs with Grafana Loki

  • Use Grafana Loki to aggregate and manage logs.
  • Simplifies the process of searching through logs to find relevant information.

• Metrics with Prometheus and Grafana Mimir

  • Utilize Prometheus for collecting metrics over time.
  • Grafana Mimir can be used for long-term storage and querying of metrics data.

• Distributed Tracing with Grafana Tempo

  • Implement distributed tracing to monitor requests across services.
  • Grafana Tempo allows you to visualize the performance of microservices.

• Continuous Profiles with Grafana Pyroscope

  • Use Grafana Pyroscope for profiling your applications continuously.
  • Helps in understanding performance bottlenecks in your code.

Step 2: Collecting Data and Instrumentation

Once you know what data to collect, the next step involves gathering that data effectively.

• Source Instrumentation with Grafana Faro and OpenTelemetry

  • Grafana Faro provides a framework for source-level instrumentation.
  • OpenTelemetry can be integrated for standardizing observability data.

• Binary Instrumentation with Grafana Alloy

  • Use Grafana Alloy for instrumentation at the binary level.
  • Beneficial for applications where source code modification is impractical.

• External eBPF Instrumentation with Grafana Beyla

  • Grafana Beyla leverages eBPF to collect data without modifying application code.
  • Ideal for monitoring performance in production environments.

• Software Testing with Grafana k6

  • Employ Grafana k6 for load testing and performance evaluation.
  • Helps in identifying performance issues before deployment.

Step 3: Visualizing Data

Visual representation of data is crucial for identifying trends and anomalies.

• Visualization with Grafana

  • Use Grafana dashboards to create visual representations of logs, metrics, and traces.
  • Customize dashboards to meet specific observability needs.

• Incident Response Management with Grafana OnCall

  • Implement Grafana OnCall for managing incidents effectively.
  • Streamlines the process of incident response and ensures timely resolutions.

Conclusion

In summary, open-source observability with the Grafana Labs stack involves identifying what data to collect, implementing effective data collection methods, and visualizing the data for actionable insights. To get started, explore the various tools provided in the Grafana ecosystem and consider integrating them into your monitoring strategy. For further learning, check the official documentation linked in the resources above.