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Introduction to Monitoring and Observability

Monitoring and observability are essential practices for maintaining the health, performance, and reliability of Linux systems and applications. While they are related, they serve different purposes.

Monitoring​

Monitoring is the process of collecting, aggregating, and analyzing metrics to determine if a system is working as expected. It tells you when something is wrong.

Key Concepts​

  • Metrics: Quantitative measurements taken over time, such as CPU usage, memory consumption, or disk I/O.
  • Alerting: Automated notifications triggered when metrics cross predefined thresholds.
  • Dashboards: Visual representations of metrics for quick assessment of system health.

Observability​

Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. It tells you why something is wrong.

The Three Pillars of Observability​

  1. Logs: Immutable records of discrete events that occurred over time.
  2. Metrics: Numeric representations of data measured over intervals of time.
  3. Traces: Representations of a series of causally related distributed events that encode the end-to-end request flow through a distributed system.

Why are they important?​

  • Proactive Issue Detection: Identify problems before they impact users.
  • Capacity Planning: Understand resource usage trends to scale systems appropriately.
  • Troubleshooting: Rapidly diagnose and resolve complex issues.
  • Performance Optimization: Identify bottlenecks and improve system efficiency.

In the following sections, we will explore various tools used for monitoring and observability in Linux, such as Prometheus, Grafana, sysstat, sar, and Netdata.