Datadog Org migration checklist
Playbook 2 min read

Datadog Org migration checklist

By Nicolas Narbais

Before completing your migration, review the following checklist to ensure a smooth transition. 💡Checkout our complete article if something is unclear. ✅ Pla

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Before completing your migration, review the following checklist to ensure a smooth transition.

💡

Checkout our complete article if something is unclear.

✅ Plan & Preparation:

  • Define the migration timeline and key milestones.
  • Identify all assets (dashboards, monitors, users, logs, integrations) that need migration.
  • Determine whether the migration is to a new or existing organization.

✅ Data & Configuration Transfer:

  • Use the Datadog Sync CLI to migrate dashboards, monitors, and configurations.
  • Ensure tagging and naming conventions are consistent across the old and new organizations.
  • Set up dual shipping or log forwarding for continuity during migration.

✅ Agent & Integration Updates:

  • Update Datadog Agents with the new API key and destination.
  • Reconfigure cloud integrations (AWS, GCP, Azure, MongoDB Atlas, etc.).
  • Verify that webhooks, alerting channels, and notification settings are properly migrated.

✅ Telemetry History & Performance Considerations:

  • Document how teams will access historical data from the old organization.
  • Ensure machine learning-based monitors have sufficient data for proper function.
  • Monitor API rate limits if using custom scripts to export/import metrics.

✅ Testing & Validation:

  • Verify that dashboards display the correct data in the new organization.
  • Validate that monitors and alerts trigger as expected.
  • Check that logs are being ingested properly and search functionality works.

✅ Communication & Post-Migration Support:

  • Notify stakeholders about the transition and any expected changes.
  • Provide updated documentation on the new setup.
  • Set up a support channel to resolve migration-related issues.

Written by Nicolas Narbais

I write about observability, OpenTelemetry, Tsuga, Datadog, and the practical work of making monitoring useful for engineering teams. I am also building Digitam to help teams reduce telemetry waste and improve observability outcomes.

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