Observability Best Practices

This guide provides a comprehensive overview of best practices for observability.

Observability is the ability to understand the internal state of a system based on its external outputs – logs, metrics, and traces. Effective observability allows you to quickly identify and diagnose problems, understand system behavior, and optimize performance.

Tracking Requests Through a Distributed System.

Span: A single operation within a trace.

Trace: A collection of spans for one request.

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Duration: Time to Completion

USE Method (Infrastructure): Utilizing the Unified Service Event format for detailed logging.

Utilization: Measuring resource consumption during operations.

Frequently asked questions

What is observability?

Observability is the ability to understand the internal state of a system based on its external outputs – logs, metrics, and traces.

What is a trace in the context of distributed systems?

A trace represents a single user request as it flows through your system, capturing all related spans to provide complete visibility.

How can I effectively monitor high-volume systems?

For high-volume systems, consider using sampling techniques (1-10%) to reduce data volume while still capturing key events. This allows you to analyze trends without overwhelming your monitoring tools.

What types of data should I store for observability?

Prioritize storing all error traces, representative samples of successful traces, traces related to new features, and traces used for performance analysis. Typically, retention periods range from 7 to 30 days.

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