This is perfect for agentic workflows, chatbots, or multi-step LLM calls, by helping you understand and optimize your AI application’s performance.

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How Tracing Works

Obiguard uses OpenTelemetry-compliant tracing to monitor your LLM requests. By attaching a trace ID to your requests, all related LLM calls are automatically grouped in the Traces View and displayed as “spans” within a trace. A “span” represents a subgroup of LLM calls. Depending on your instrumentation, a span can refer to a group within a trace or a single LLM call.

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Trace Tree Structure

Obiguard implements tracing using a tree-like structure, similar to OpenTelemetry. Each node in this tree is a span, identified by a unique spanId and an optional spanName. Child spans reference their parent using parentSpanId. Spans without a parent become root nodes. 
traceId
├─ parentSpanId
│  ├─ spanId
│  ├─ spanName
KeyNodeKey - PythonExpected ValueRequired?
traceIdtrace_idUnique stringYES
spanIdspan_idUnique stringNO
spanNamespan_namestringNO
parentSpanIdparent_span_idUnique stringNO

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Benefits of Tracing

  • Cost Analysis: Monitor total LLM costs for each trace.
  • Debugging: Quickly review all related requests in a trace and spot issues.
  • Performance Monitoring: Gain visibility into the full request lifecycle and overall trace timing.