Default Exporter

The DefaultExporter persists traces to your configured storage backend, making them accessible through Studio. It's automatically enabled when using the default observability configuration and requires no external services.

Production Observability

Observability data can quickly overwhelm general-purpose databases in production. For high-traffic applications, we recommend using ClickHouse for the observability storage domain via composite storage. See Production Recommendations for details.

Configuration

Prerequisites

1. Storage Backend: Configure a storage provider (libSQL, PostgreSQL, etc.)
2. Studio: Install for viewing traces locally

Basic Setup

src/mastra/index.ts

import { Mastra } from "@mastra/core";
import { Observability, DefaultExporter } from "@mastra/observability";
import { LibSQLStore } from "@mastra/libsql";

export const mastra = new Mastra({
  storage: new LibSQLStore({
    id: 'mastra-storage',
    url: "file:./mastra.db", // Required for trace persistence
  }),
  observability: new Observability({
    configs: {
      local: {
        serviceName: "my-service",
        exporters: [new DefaultExporter()],
      },
    },
  }),
});

Recommended Configuration

Include DefaultExporter in your observability configuration:

import { Mastra } from "@mastra/core";
import {
  Observability,
  DefaultExporter,
  CloudExporter,
  SensitiveDataFilter,
} from "@mastra/observability";
import { LibSQLStore } from "@mastra/libsql";

export const mastra = new Mastra({
  storage: new LibSQLStore({
    id: 'mastra-storage',
    url: "file:./mastra.db",
  }),
  observability: new Observability({
    configs: {
      default: {
        serviceName: "mastra",
        exporters: [
          new DefaultExporter(), // Persists traces to storage for Mastra Studio
          new CloudExporter(), // Sends traces to Mastra Cloud (requires MASTRA_CLOUD_ACCESS_TOKEN)
        ],
        spanOutputProcessors: [
          new SensitiveDataFilter(),
        ],
      },
    },
  }),
});

Viewing Traces

Studio

Access your traces through Studio:

1. Start Studio
2. Navigate to Observability
3. Filter and search your local traces
4. Inspect detailed span information

Tracing Strategies

DefaultExporter automatically selects the optimal tracing strategy based on your storage provider. You can also override this selection if needed.

Available Strategies

Strategy	Description	Use Case
realtime	Process each event immediately	Development, debugging, low traffic
batch-with-updates	Buffer events and batch write with full lifecycle support	Low volume Production
insert-only	Only process completed spans, ignore updates	High volume Production

Strategy Configuration

new DefaultExporter({
  strategy: "auto", // Default - let storage provider decide
  // or explicitly set:
  // strategy: 'realtime' | 'batch-with-updates' | 'insert-only'

  // Batching configuration (applies to both batch-with-updates and insert-only)
  maxBatchSize: 1000, // Max spans per batch
  maxBatchWaitMs: 5000, // Max wait before flushing
  maxBufferSize: 10000, // Max spans to buffer
});

Storage Provider Support

Different storage providers support different tracing strategies. Some providers support observability for production workloads, while others are intended primarily for local development.

If you set the strategy to 'auto', the DefaultExporter automatically selects the optimal strategy for the storage provider. If you set the strategy to a mode that the storage provider doesn't support, you will get an error message.

Providers with Observability Support

Storage Provider	Preferred Strategy	Supported Strategies	Recommended Use
ClickHouse (@mastra/clickhouse)	insert-only	insert-only	Production (high-volume)
PostgreSQL	batch-with-updates	batch-with-updates, insert-only	Production (low volume)
MSSQL	batch-with-updates	batch-with-updates, insert-only	Production (low volume)
MongoDB	batch-with-updates	batch-with-updates, insert-only	Production (low volume)
libSQL	batch-with-updates	batch-with-updates, insert-only	Default storage, good for development

Providers without Observability Support

The following storage providers do not support the observability domain. If you're using one of these providers and need observability, use composite storage to route observability data to a supported provider:

• Convex
• DynamoDB
• Cloudflare D1
• Cloudflare Durable Objects
• Upstash
• LanceDB

Strategy Benefits

• realtime: Immediate visibility, best for debugging
• batch-with-updates: 10-100x throughput improvement, full span lifecycle
• insert-only: Additional 70% reduction in database operations, perfect for analytics

Production Recommendations

Observability data grows quickly in production environments. A single agent interaction can generate hundreds of spans, and high-traffic applications can produce thousands of traces per day. Most general-purpose databases aren't optimized for this write-heavy, append-only workload.

Recommended: ClickHouse for High-Volume Production

ClickHouse is a columnar database designed for high-volume analytics workloads. It's the recommended choice for production observability because:

• Optimized for writes: Handles millions of inserts per second
• Efficient compression: Reduces storage costs for trace data
• Fast queries: Columnar storage enables quick trace lookups and aggregations
• Time-series native: Built-in support for time-based data retention and partitioning

Using Composite Storage

If you're using a provider without observability support (like Convex or DynamoDB) or want to optimize performance, use composite storage to route observability data to ClickHouse while keeping other data in your primary database.

Batching Behavior

Flush Triggers

For both batch strategies (batch-with-updates and insert-only), traces are flushed to storage when any of these conditions are met:

1. Size trigger: Buffer reaches maxBatchSize spans
2. Time trigger: maxBatchWaitMs elapsed since first event
3. Emergency flush: Buffer approaches maxBufferSize limit
4. Shutdown: Force flush all pending events

Error Handling

The DefaultExporter includes robust error handling for production use:

• Retry Logic: Exponential backoff (500ms, 1s, 2s, 4s)
• Transient Failures: Automatic retry with backoff
• Persistent Failures: Drop batch after 4 failed attempts
• Buffer Overflow: Prevent memory issues during storage outages

Configuration Examples

// Zero config - recommended for most users
new DefaultExporter();

// Development override
new DefaultExporter({
  strategy: "realtime", // Immediate visibility for debugging
});

// High-throughput production
new DefaultExporter({
  maxBatchSize: 2000, // Larger batches
  maxBatchWaitMs: 10000, // Wait longer to fill batches
  maxBufferSize: 50000, // Handle longer outages
});

// Low-latency production
new DefaultExporter({
  maxBatchSize: 100, // Smaller batches
  maxBatchWaitMs: 1000, // Flush quickly
});

Related

• Tracing Overview
• CloudExporter
• Composite Storage - Combine multiple storage providers
• Storage Configuration