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Studio observability

Studio includes these observability views:

  • Metrics for aggregate performance data
  • Traces for individual request inspection
  • Logs for browsing internal and application logs

All require an observability storage backend to be configured.

Metrics
Direct link to Metrics

A dashboard that summarizes agent, workflow, and tool performance over a configurable time range (last 24 hours to 30 days). The top row shows total agent runs, model cost, token consumption, and average scorer performance. Below that, detailed cards break down model usage and cost per model, token usage per agent, trace volume with completed and error counts, latency percentiles (p50 and p95), and scorer trends over time.

Visit the metrics overview for more details.

note

Metrics require a separate OLAP store for observability. Relational databases like PostgreSQL, LibSQL, etc. are not supported for metrics. In-memory storage resets on restart.

Traces
Direct link to Traces

When you run an agent or workflow, the Observability tab displays traces that highlight the key AI operations such as model calls, tool executions, and workflow steps. Follow these traces to see how data moves, where time is spent, and what's happening under the hood.

Tracing filters out low-level framework details so your traces stay focused and readable. Visit the tracing overview for more details.

Logs
Direct link to Logs

Browse internal Mastra logs forwarded to your observability storage. Logs provide full-text search (across message content, entity names, and trace IDs), date presets (last 24 hours to 30 days), and multi-select filters for level, entity type, and entity name. Selecting a log opens a detail panel showing the full message, structured data, and metadata. If the log is correlated with a trace, you can navigate directly to the trace and span timeline.

Log forwarding is enabled by default when you configure observability. See logging for level configuration, query examples, and customization details.

Quickstart
Direct link to Quickstart

For detailed instructions, follow the observability instructions. To get up and running quickly, add the @mastra/observability package to your project and configure it with LibSQL and DuckDB for a local development setup that supports both traces and metrics.

npm install @mastra/observability @mastra/libsql @mastra/duckdb

Then add the following to your src/mastra/index.ts:

src/mastra/index.ts
import { Mastra } from '@mastra/core/mastra'
import { LibSQLStore } from '@mastra/libsql'
import { DuckDBStore } from '@mastra/duckdb'
import { MastraCompositeStore } from '@mastra/core/storage'
import {
  Observability,
  DefaultExporter,
  CloudExporter,
  SensitiveDataFilter,
} from '@mastra/observability'

export const mastra = new Mastra({
  storage: new MastraCompositeStore({
    id: 'composite-storage',
    default: new LibSQLStore({
      id: 'mastra-storage',
      url: 'file:./mastra.db',
    }),
    domains: {
      observability: await new DuckDBStore().getStore('observability'),
    },
  }),
  observability: new Observability({
    configs: {
      default: {
        serviceName: 'mastra',
        exporters: [
          new DefaultExporter(), // Persists traces to storage for Mastra Studio
          new CloudExporter(), // Sends observability data to hosted Mastra Studio (if MASTRA_CLOUD_ACCESS_TOKEN is set)
        ],
        spanOutputProcessors: [
          new SensitiveDataFilter(), // Redacts sensitive data like passwords, tokens, keys
        ],
      },
    },
  }),
})
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