Mastra Observability

Observe and evaluateyour AI agent performance

Mastra Observability monitors LLM operations, traces agent decision paths, and helps you debug complex workflows. Seamlessly integrate with any OpenTelemetry-compatible platform.

AI agent and workflow monitoring

When errors occur, Mastra shows you exactly what happened. Every LLM call logs token usage, latency, prompts and completions. Every agent run captures decision paths, tool calls and memory operations.

Monitoring

Performance and Cost Monitoring

Track token usage, latency and performance across every agent run.
docs
Logs

Logging and Debugging

View persistent log and trace data for debugging agents and workflows.
docs

Agent tracing and telemetry

Mastra traces every step of agent execution and sends telemetry to any observability provider. Decorator-based instrumentation captures the full callstack locally and in production. Mastra supports any OpenTelemetry-compatible platform, including MLflow, Langfuse, Braintrust, Datadog, New Relic and SigNoz.

OTel Support

OTel Support

Connect to any OpenTelemetry-compatible observability provider, including Datadog and SigNoz.
docs
Tracing

Tracing

Capture agent decision paths, tool calls and memory operations automatically.
docs

build custom agent evals

Mastra Scorers give you quantifiable metrics for measuring agent quality, automatically running in the background, and stored in your database. Get insights into performance, compare different approaches, and identify areas for improvement in your AI systems.

Agent Evaluation

Agent Evaluation

Score agent outputs using model-graded, rule-based and statistical evaluation methods.
docs
CI/CD

CI/CD

Capture real-time results and monitor your agents' performance over time.
docs

Python trains,
TypeScript ships.

npm create mastraContact Sales

Frequently asked questions