Monitoring

Track AI usage, performance, and errors with SDK integration and tracing.

Monitoring gives you full visibility into your production AI system. Integrate the @know-your-ai SDK to automatically capture every AI interaction and surface it in dashboards and traces.

SDK integration

Add the @know-your-ai SDK to your application to start capturing events.

1. Install the SDK package
2. Configure your DSN (Data Source Name) from the product settings
3. The SDK automatically captures: provider, model, token usage, cost, latency, errors, and trace/span data

Monitoring dashboard

The monitoring dashboard aggregates SDK events with key metrics:

• Total requests — Count of AI interactions over time
• Error count — Failed requests and error rates
• Average duration — Response time metrics
• Token usage — Input, output, and cached tokens
• Cost tracking — Estimated cost per interaction
• Latency breakdown — TTFB, throughput, p95 percentiles
• Provider distribution — Usage split by AI provider
• Model distribution — Usage split by model version

Tracing

The tracing view provides a full span-tree visualization for debugging AI interactions.

Supported span types:

Span type	Description
Generation	LLM call with input/output
Agent	Agent orchestration step
Tool	Tool/function call
Chain	Chained processing step
Retriever	RAG retrieval step
Evaluator	Evaluation judgment
Guardrail	Safety/content filter
Event	Custom event

Each span includes:

• Trace, session, and user context
• Input/output data
• Tool calls and errors
• Duration and timing
• Filterable by status, model, and time range

Token usage charts

Track token usage over time with configurable views:

• Input tokens, output tokens, and total
• Configurable granularity: hour, day, month
• Time ranges: 24 hours, 7 days, 30 days, 90 days
• Server response time charts

Related docs

Evaluation

Build the signals you monitor in production.

Workspace

Keep environments isolated and clean.