To debug a backend error, use logs to find what the application recorded and a distributed trace to see which operations handled the request. Start with the time, route, status and any request or trace ID; locate the matching request, inspect its spans, then correlate suspicious operations with their logs and service metrics. A trace narrows the search—it does not, by itself, prove the root cause.
What logs and traces tell you
A log entry records an event, often with details such as a message, severity, timestamp and application fields. A trace represents a logical request as a set of spans: individual operations and their causal relationships. Those spans may show the incoming server request, calls to other services, database work or other instrumented activity. Together, logs and traces help answer both “what happened?” and “where in the request path did it happen?” OpenTelemetry’s trace documentation explains traces and spans; its log data model describes how log records can include execution and resource context.
Trace context can be carried between processes and across network boundaries so operations can be associated with the same request. OpenTelemetry’s default propagator uses W3C Trace Context, including the HTTP traceparent header; tracestate can carry vendor-specific values. The W3C standard defines the format, but propagation does not guarantee that every library, proxy, queue or service in your system is instrumented. Check each boundary you rely on. OpenTelemetry’s context propagation guide and the W3C Trace Context Recommendation, published 23 November 2021, describe the mechanism.
Investigate an error from the request to the operation
- Bound the event. Record the approximate UTC time, environment, affected route or operation, response status, and any request ID or trace ID from the report. Search a narrow time range first; widen it if ingestion delay or clock differences could put the event outside that window. Keep the emitting service or workload in view so similarly timed events from different components are not confused.
- Find the request in structured logs. Filter by stable fields such as service, route or operation, severity, status and time. JSON or other structured records expose individual fields for queries; plain-text messages are harder to filter reliably. Field names are not universal, so query the schema your application actually emits. Google Cloud’s structured logging guide shows one platform’s approach, not a portable field-name standard.
- Open or reconstruct the trace. Search by trace ID when available. Otherwise, use the request’s time and service context to find a likely trace, taking care with busy systems where several requests may overlap. Follow the parent/child span relationships from the incoming request through downstream calls and other instrumented work. The path can reveal where processing failed, stopped, or took unexpectedly long.
- Inspect the suspicious span. Check its operation name, service or resource, start and end times, status, relevant attributes, and any exception or event information recorded. A span marked Error means an error was recorded for that operation; it does not explain the underlying code or business cause. Use the attributes and events as clues, then verify them against logs and code context.
- Correlate the span with logs. Look for trace context—and, where supported, a span ID—in application log records. OpenTelemetry describes correlation using
TraceId,SpanId, time and resource context. Backend behavior varies. For example, Google Cloud documents atracefield and conditions involving matching trace values and timestamp ordering when grouping entries; do not assume that field name or behavior applies elsewhere. See OpenTelemetry’s log data model and Google Cloud’s log correlation guidance. - Check whether the error is isolated. Compare the request with service metrics, especially request volume, latency and error rates around the same time. One failed span may reflect an individual input or dependency problem; a simultaneous shift in service-level metrics can indicate broader impact. CloudWatch documents viewing metrics alongside an application trace in its application traces guide.
What to check when logs or spans are missing
Missing correlated data may be a telemetry problem rather than evidence that the operation did not occur. Check the path in order: whether the service emitted the data, whether collectors and exporters delivered it, whether your selected time range includes the event, and whether identifiers and context propagated as expected.
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- No matching log entry: Confirm the application writes logs for that event and that the backend received them. Check the actual field names and whether the query uses the correct service, environment and time range.
- A trace stops at a service boundary: Check instrumentation and context propagation in the service that should come next, as well as any proxy, queue or other intermediary on that path. Context propagation enables correlation only when the participating components preserve and use it.
- Only a few flat spans appear: The service may have instrumentation for the request boundary but not for internal operations or dependencies. Inspect coverage for database calls, outbound requests and queue work before treating the visible spans as the complete execution path.
- A trace exists but logs do not link to it: Verify that the application includes trace context in its log records and that the backend’s correlation requirements are met. Legacy system logs may lack trace context or represent it inconsistently; resource details and timestamps can help narrow a search, but time alone is weaker evidence than matching identifiers.
OpenTelemetry’s logging specification describes trace, span, time and resource context, including the limitations of legacy logs. Google Cloud’s correlation documentation illustrates why platform-specific matching rules matter.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep diagnostic telemetry safe
Log enough context to investigate failures, but do not record passwords, access tokens, encryption keys, database connection strings, payment details or sensitive personal information directly. Sanitize, mask, hash or encrypt values where appropriate, and restrict access to stored logs and traces. OWASP’s Logging Cheat Sheet gives guidance on protecting sensitive data in logging systems.
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