Which telemetry type is most suitable for understanding the path of a request across multiple services?

Which telemetry type is most suitable for understanding the path of a request across multiple services?

• A. Logs
• B. Metrics
• C. Traces
• D. Alerts

Answer: (C)

Understanding a request’s journey across multiple services requires end-to-end visibility of the call chain, including where the request traveled, in what order, and how long each hop took. This is exactly what traces provide. A trace follows a single request as it traverses service boundaries, with each service's work represented as a span. The trace carries a unique trace ID and span IDs so you can see the entire path, the sequence of services involved, timing at each hop, and where any errors or slowdowns occur. This makes it possible to pinpoint bottlenecks and dependencies in a distributed system. Logs capture what happened at each service, but they are per-service events in isolation and don’t automatically assemble into an end-to-end path. Metrics give aggregate numbers over time (like average latency or error rate) but miss the precise sequence and cross-service relationships. Alerts trigger notifications when thresholds are crossed, not the actual path a request took. Tracing tools (often using OpenTelemetry or similar) propagate context across services so the full request path is visible in one cohesive view, enabling quick understanding of the end-to-end flow.

Understanding a request’s journey across multiple services requires end-to-end visibility of the call chain, including where the request traveled, in what order, and how long each hop took. This is exactly what traces provide. A trace follows a single request as it traverses service boundaries, with each service's work represented as a span. The trace carries a unique trace ID and span IDs so you can see the entire path, the sequence of services involved, timing at each hop, and where any errors or slowdowns occur. This makes it possible to pinpoint bottlenecks and dependencies in a distributed system.

Logs capture what happened at each service, but they are per-service events in isolation and don’t automatically assemble into an end-to-end path. Metrics give aggregate numbers over time (like average latency or error rate) but miss the precise sequence and cross-service relationships. Alerts trigger notifications when thresholds are crossed, not the actual path a request took.

Tracing tools (often using OpenTelemetry or similar) propagate context across services so the full request path is visible in one cohesive view, enabling quick understanding of the end-to-end flow.