Traces
The Traces module provides distributed tracing for understanding request flow across microservices. It captures end-to-end latency, identifies bottlenecks, and correlates trace spans with logs and metrics.
Key Features
- End-to-end trace visualization — Waterfall view (timeline by span) and optional Flame graph view (nested spans by depth and duration) when span data is stored for the trace
- Flame graph API —
GET /api/traces/{trace_id}/flamereturns{ data: { trace_id, total_duration_ms, flame_spans[] } }withstart_msrelative to trace start,depth,service,status, andspan_idfor selection - Service-level latency — Aggregate latency percentiles (p50, p95, p99) per service and endpoint
- Error tracking — Surface spans with errors and link them to the originating service
- Trace-to-log correlation — Click any span to see logs emitted during that span’s execution
- Trace-to-metric correlation — View infrastructure metrics (CPU, memory) for the host/container during the trace
- Sampling controls — Configure head-based or tail-based sampling rates per service
- OpenTelemetry native — Ingest traces via OTLP, Jaeger, or Zipkin protocols
- Critical path analysis — Highlight the spans that contribute most to total request latency
How to Access
Navigate to Traces in the left sidebar. The default view shows a trace search interface with service and latency filters.
Basic Usage
- Open Traces from the sidebar (under OBSERVE)
- Filter traces by service, operation, minimum duration, or status (OK / Error)
- Click a trace row to open the detail drawer
- Switch View between Waterfall and Flame graph — waterfall shows a Gantt-style timeline; flame graph stacks spans by depth for quick hotspot scanning
- In flame view, click a block to focus span details (when
span_idis present) - Examine individual spans — click for attributes, error stack traces, and links to Logs and Services
- Use View logs for this trace from the drawer header to correlate with logs
Some roadmap items (compare two traces, latency alerts UI) may vary by deployment; use Metrics and SLO modules for alerting where integrated.