observability-integrator

Designing observability for Kotlin Spring services requires defining operational questions and SLO targets before instrumenting logs, metrics, and traces. This approach ensures telemetry provides clear signals for incident response rather than vanity metrics.

Managing telemetry cardinality in async Kotlin coroutine architectures involves applying strict operational guardrails during instrumentation. This ensures trace propagation and PII redaction are handled correctly while maintaining production-grade performance and cost efficiency.

Instrumenting distributed traces across async and coroutine-based Spring services requires aligning telemetry with operational questions. This ensures technical requirements for trace propagation and health monitoring are met without compromising performance.

OpenTelemetry works with Kotlin Spring services by aligning telemetry instrumentation with operational questions and SLO targets. This ensures logs, metrics, and traces provide actionable signals for health monitoring and incident response.

You need to align telemetry with operational questions whenever instrumenting a new Kotlin Spring service to ensure production-grade performance. This prevents high cardinality costs and ensures metrics, logs, and traces support SLO monitoring and incident response.

Trace propagation breaks in Kotlin coroutine environments due to async context switching, but applying strict operational guardrails during instrumentation fixes this. This ensures distributed traces remain intact while maintaining cost efficiency.