setup-tracing

Configure OpenTelemetry tracing for AI agents by injecting Coval-compatible OTLP exporters into existing telemetry providers, which automatically captures conversation flows, tool calls, and latency metrics. This standardizes span naming and batch processing to ensure reliable trace ingestion.

Monitoring LLM tool-call performance in production voice agents requires instrumenting the agent with standardized OpenTelemetry tracing. This captures latency metrics and conversation flows without manually rewriting core application logic, sending the data directly to the Coval platform.

OpenTelemetry instrumentation works with WebSocket and SIP voice agent architectures, alongside PSTN and chat services. It automatically detects the connection type and configures the correct correlation headers, such as X-Simulation-Id, to ensure reliable trace ingestion.

Track STT and TTS latency for AI voice services by setting up automated tracing instrumentation. This captures latency metrics and correlates them with conversation flows using injected correlation headers, making the performance data visible within the Coval observability platform.

You can add observability to your AI agent without rewriting core application logic by running automated instrumentation. This injects OTLP exporters into existing telemetry providers and manages correlation paths, capturing performance metrics seamlessly.