Skip to content

OpenTelemetry Collection

View as Markdown

OpenTelemetry collection exports distributed traces, logs, and metrics from Daytona SDK operations and sandbox runtimes to your observability stack. Data is sent over the OpenTelemetry Protocol (OTLP) to any OTLP-compatible collector or backend.

Daytona supports two independent telemetry paths:

  • Sandbox telemetry: collects traces, logs, and metrics from inside sandboxes, including CPU, memory, and filesystem metrics, application logs, and HTTP spans
  • SDK tracing: instruments Daytona API operations and SDK calls in your application process

You can enable one or both. SDK tracing covers the control path from your application into Daytona. Sandbox telemetry covers what runs inside the sandbox. Together they provide end-to-end visibility across both sides.

Configure a sandbox collection endpoint.

  1. Go to Daytona Dashboard ↗

  2. Navigate to OpenTelemetry section (visible to organization owners)

  3. Configure the following fields:

    • OTLP Endpoint: OpenTelemetry collector endpoint

      Example: https://otel-collector.example.com

    • Headers: authentication headers as key/value pairs

      Example: api-key = YOUR_API_KEY

Terminal window
curl 'https://app.daytona.io/api/organizations/ORGANIZATION_ID/otel-config' \
--request PUT \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
"endpoint": "https://otel-collector.example.com",
"headers": {
"api-key": "YOUR_COLLECTOR_API_KEY"
}
}'

All sandboxes automatically export their telemetry data to the specified OTLP endpoint.

View collected telemetry for a sandbox.

  1. Go to Daytona Dashboard ↗
  2. Navigate to Sandboxes section
  3. Open the Sandbox Details sheet for any sandbox
  4. Use the Logs, Traces, and Metrics tabs to inspect the collected telemetry data
# Historical resource metrics (CPU, memory, disk)
samples = sandbox.get_metrics()
for s in samples:
print(f"{s.timestamp}: CPU {s.cpu_used_pct}%")

Metrics:

  • daytona.sandbox.cpu.utilization: CPU usage percentage (0-100%)
  • daytona.sandbox.cpu.limit: CPU cores limit
  • daytona.sandbox.memory.utilization: Memory usage percentage (0-100%)
  • daytona.sandbox.memory.usage: Memory used in bytes
  • daytona.sandbox.memory.limit: Memory limit in bytes
  • daytona.sandbox.filesystem.utilization: Disk usage percentage (0-100%)
  • daytona.sandbox.filesystem.usage: Disk space used in bytes
  • daytona.sandbox.filesystem.available: Disk space available in bytes
  • daytona.sandbox.filesystem.total: Total disk space in bytes

Traces:

  • HTTP requests and responses
  • Custom spans from your application code

Logs:

  • Application logs (stdout/stderr)
  • System logs
  • Runtime errors and warnings

All sandbox telemetry is automatically annotated with the following OTel resource attributes:

  • service.name: sandbox-<id> by default. See service name to override it.
  • service.instance.id: the sandbox ID
  • daytona_organization_id: the organization the sandbox belongs to
  • daytona_region_id: the region the sandbox is running in
  • daytona_snapshot: the snapshot used to create the sandbox

Attach custom resource labels on a sandbox. Labels are a comma-separated list of key=value pairs. The labels are added as OTel resource attributes to all traces, logs, and metrics emitted by the sandbox. Use them to filter and group telemetry by custom dimensions in your observability platform.

  1. Set the DAYTONA_SANDBOX_OTEL_EXTRA_LABELS environment variable on a sandbox:
Terminal window
DAYTONA_SANDBOX_OTEL_EXTRA_LABELS="team=backend,env=staging,app=my-service"

Override the service.name resource attribute on sandbox telemetry. By default, each sandbox reports service.name as sandbox-<id>. Most observability backends treat every distinct service.name as a separate service, so a fleet of sandboxes appears as one service per sandbox. Set a shared name to group all sandboxes under a single service in your backend. Each sandbox stays identifiable through the service.instance.id attribute, which holds the sandbox ID.

  1. Set the DAYTONA_SANDBOX_OTEL_SERVICE_NAME environment variable when creating a sandbox:
Terminal window
DAYTONA_SANDBOX_OTEL_SERVICE_NAME="my-agents"

The sandbox reads the variable once at startup. Changing it inside a running sandbox has no effect.

The override applies to the telemetry forwarded to your configured OTLP endpoint. Telemetry stored by Daytona and shown in the Dashboard keeps the default sandbox-<id> name. Leading and trailing whitespace is trimmed. An empty or whitespace-only value is treated as unset.

In addition to per-sandbox telemetry, Daytona exports organization-level resource metrics to your configured OTLP endpoint. These metrics are pushed every 60 seconds and provide a high-level view of resource consumption and quotas across your organization.

Organization metrics are exported automatically when you have a sandbox collection endpoint configured. No additional setup is required. The same OTLP endpoint receives both sandbox telemetry and organization metrics.

MetricUnitDescription
daytona.sandbox.used_cpuCPU coresTotal CPU currently consumed by active sandboxes
daytona.sandbox.used_ramGiBTotal memory currently consumed by active sandboxes
daytona.sandbox.used_storageGiBTotal disk currently consumed by sandboxes
daytona.sandbox.total_cpuCPU coresTotal CPU quota for the organization
daytona.sandbox.total_ramGiBTotal memory quota for the organization
daytona.sandbox.total_storageGiBTotal disk quota for the organization
daytona.sandbox.used_gpuGPU unitsTotal GPU units currently consumed by active sandboxes
daytona.sandbox.total_gpuGPU unitsTotal GPU quota for the organization

Each metric includes the following attributes for filtering and grouping:

  • organization.id (resource attribute): the organization the metrics belong to
  • region.id (data point attribute): the region the resource usage and quota applies to
  • sandbox.class (data point attribute): the sandbox class the resource usage and quota applies to

GPU metrics for shared regions are exported under the Earth region: one data point per sandbox class with region.id set to earth aggregates the shared GPU usage and quota. Data points for shared regions report 0 for daytona.sandbox.used_gpu and omit daytona.sandbox.total_gpu. Dedicated and custom regions keep their own GPU data points.

SDK tracing instruments Daytona SDK operations in your application process and exports them as OpenTelemetry traces. When enabled, the SDK creates spans for calls your application makes into Daytona, then sends those traces over OTLP to your observability backend.

Send traces to any OTLP-compatible backend:

  1. Pass the otelEnabled flag when initializing the Daytona client, or set the DAYTONA_OTEL_ENABLED environment variable to true:
Terminal window
export DAYTONA_OTEL_ENABLED=true
from daytona import Daytona, DaytonaConfig
# Using async context manager (recommended)
async with Daytona(DaytonaConfig(otel_enabled=True)) as daytona:
sandbox = await daytona.create()
# All operations will be traced
# OpenTelemetry traces are flushed on close

Or without context manager:

daytona = Daytona(DaytonaConfig(otel_enabled=True))
try:
sandbox = await daytona.create()
# All operations will be traced
finally:
await daytona.close() # Flushes traces

The SDK uses standard OpenTelemetry environment variables for configuration.

Terminal window
# OTLP endpoint (without the /v1/traces path)
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp.nr-data.net:4317
# Authentication headers (format: key1=value1,key2=value2)
OTEL_EXPORTER_OTLP_HEADERS="api-key=your-api-key-here"
Terminal window
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp.nr-data.net:4317
OTEL_EXPORTER_OTLP_HEADERS="api-key=YOUR_NEW_RELIC_LICENSE_KEY"

See the New Relic dashboard example for detailed setup steps.

Terminal window
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
Terminal window
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-<region>.grafana.net/otlp
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <BASE64_ENCODED_CREDENTIALS>"
  1. Go to Grafana Cloud Portal
  2. Open Connections
  3. Click Add new connection
  4. Search for OpenTelemetry (OTLP)
  5. Follow the wizard to create an access token. The endpoint and headers are provided in the instrumentation instructions. See the Grafana dashboard example for detailed setup steps.

Datadog exposes a native OTLP intake endpoint, so you can send telemetry directly to Datadog without a Datadog Agent.

Terminal window
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp.datadoghq.com
OTEL_EXPORTER_OTLP_HEADERS="dd-api-key=YOUR_DATADOG_API_KEY"
OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
  1. Enter the OTLP endpoint for your Datadog site and add a single header dd-api-key with your Datadog API key:
Datadog SiteOTLP Endpoint
US1 (datadoghq.com)https://otlp.datadoghq.com
EU (datadoghq.eu)https://otlp.datadoghq.eu
US3https://otlp.us3.datadoghq.com
US5https://otlp.us5.datadoghq.com
AP1https://otlp.ap1.datadoghq.com

Use the base endpoint without a /v1/... path. The path is appended automatically.

  1. Generate an API key under Datadog > Organization Settings > API Keys. See the Datadog dashboard example for an importable dashboard and verification steps.

Metrics appear under Metrics > Summary (search for daytona.sandbox), where you can also confirm the exact tag keys (for example, service, region.id).

Parseable exposes a native OTLP HTTP endpoint, so you can send SDK traces directly to a Parseable dataset.

Terminal window
OTEL_EXPORTER_OTLP_ENDPOINT=https://parseable.example.com
OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer <parseable-api-key>,X-P-Stream=daytona-sdk-traces"
  1. Enter the base URL of your Parseable instance as the OTLP endpoint. Do not append /v1/traces. The path is appended automatically.

  2. Replace <parseable-api-key> with a Parseable API key that has ingest access.

    The X-P-Stream header sets the Parseable dataset that receives the traces.

See the Parseable x Daytona integration guide for detailed setup steps, including routing sandbox telemetry to Parseable through an OpenTelemetry Collector.

Complete example of OpenTelemetry tracing with the Daytona SDK:

import asyncio
import os
from daytona import Daytona, DaytonaConfig
# Set OTEL configuration
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://otlp.nr-data.net:4317"
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = "api-key=YOUR_API_KEY"
async def main():
# Initialize Daytona with OTEL enabled
async with Daytona(DaytonaConfig(otel_enabled=True)) as daytona:
# Create a sandbox - this operation will be traced
sandbox = await daytona.create()
print(f"Created sandbox: {sandbox.id}")
# Execute code - this operation will be traced
result = await sandbox.process.code_run("""
import numpy as np
print(f"NumPy version: {np.__version__}")
""")
print(f"Execution result: {result.result}")
# Upload a file - this operation will be traced
await sandbox.fs.upload_file("local.txt", "/home/daytona/remote.txt")
# Delete sandbox - this operation will be traced
await daytona.delete(sandbox)
# Traces are automatically flushed when exiting the context manager
if __name__ == "__main__":
asyncio.run(main())

The Daytona SDK automatically instruments the following operations:

  • create(): sandbox creation and initialization
  • get(): retrieving sandbox instances
  • list(): listing sandboxes
  • start(): starting sandboxes
  • stop(): stopping sandboxes
  • delete(): deleting sandboxes
  • All sandbox, snapshot and volume operations
  • All API calls to the Daytona backend
  • Request duration and response status codes
  • Error information for failed requests

Each trace includes the following metadata:

  • Service name and version
  • HTTP method, URL, and status code
  • Request and response duration
  • Error details (if applicable)

Verify the exporter before digging into application code:

  1. Check that environment variables are set correctly
  2. Verify your OTLP endpoint is reachable
  3. Confirm API keys and headers are valid
  4. Check your observability platform for incoming traces
  5. Look for connection errors in application logs

Symptom: SDK operations run successfully, but no traces appear in the observability backend.

Cause: Tracing is disabled, the OTLP endpoint or headers are wrong, or the Daytona client exits without flushing pending spans.

Solution:

  1. Ensure otelEnabled: true is set in the Daytona client configuration, or set DAYTONA_OTEL_ENABLED=true
  2. Verify the OTLP endpoint and headers match your backend
  3. Close or dispose the Daytona instance so traces flush before the process exits

See SDK tracing.