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Observability Overview

Mastra provides comprehensive observability features designed specifically for AI applications. Monitor LLM operations, trace agent decisions, and debug complex workflows with specialized tools that understand AI-specific patterns.

Key Features​

Tracing​

Specialized tracing for AI operations that captures:

  • Model interactions: Token usage, latency, prompts, and completions
  • Agent execution: Decision paths, tool calls, and memory operations
  • Workflow steps: Branching logic, parallel execution, and step outputs
  • Automatic instrumentation: Zero-configuration tracing with decorators

Quick Start​

Configure Observability in your Mastra instance:

src/mastra/index.ts
import { Mastra } from "@mastra/core";
import { PinoLogger } from "@mastra/loggers";
import { LibSqlStorage } from "@mastra/libsql";
import { Observability } from "@mastra/observability";

export const mastra = new Mastra({
  // ... other config
  logger: new PinoLogger(),
  storage: new LibSQLStore({
    id: 'mastra-storage',
    url: "file:./mastra.db", // Storage is required for tracing
  }),
  observability: new Observability({ // Enables Tracing
    default: { enabled: true },
  }),
});

With this basic setup, you will see Traces and Logs in both Studio and in Mastra Cloud.

We also support various external tracing providers like Langfuse, Braintrust, and any OpenTelemetry-compatible platform (Datadog, New Relic, SigNoz, etc.). See more about this in the Tracing documentation.

What's Next?​

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