observability-modeling

What problem does it solve?

Observability-modeling helps teams define telemetry semantics up front so systems emit logs, metrics, traces, and events that answer concrete diagnostic questions when something goes wrong.

Core Features & Use Cases

• Diagnostic-question-driven design: start from the questions you need answered, then map each question to the signals required to answer it.
• Signal semantics and correlation: define stable attribute/event/span naming and correlation identifiers across async and external boundaries.
• Operational safety considerations: plan for cardinality limits, privacy redaction, sampling rules, and actionable alert signals tied to symptoms.

Quick Start

Ask your team to design observability by listing the diagnostic questions for a key workflow, mapping each to required telemetry signals (logs/metrics/traces/events), and defining correlation IDs and stable attribute semantics before instrumenting.