opentelemetry

Distributed tracing helps debug intermittent latency by configuring custom spans to pinpoint exact operations causing delays. You can correlate these spans with structured logs to identify performance bottlenecks and system failures without deploying new code.

Trace context propagation is the mechanism of passing trace IDs across service boundaries to maintain a unified request view. You need it for performance monitoring in distributed systems to accurately correlate high-cardinality metrics and diagnose throughput issues.

Configuring Prometheus metrics and structured JSON logging for Ktor microservices involves integrating OpenTelemetry to manage observability. This setup enables high-cardinality metric collection and health check readiness probes to monitor service performance.

Yes, the observability stack supports high-cardinality metric collection and health check readiness probes. It manages OpenTelemetry, Prometheus, and Grafana integrations to satisfy these specific requirements within Ktor-based microservices.

Incomplete traces in Grafana often result from misconfigured trace context propagation or missing spans in OpenTelemetry. Analyze the current trace configuration to identify gaps and suggest improvements for your existing observability stack.