Migrating from Confluence to Datadog
Confluence supports 3,000+ integrations — 2,250 more than Datadog. If integration breadth is a factor in your switch from Confluence to Datadog, this guide covers how to reconnect your stack after migrating.
At a Glance
- Deep native integration with Jira makes it the de facto documentation tool for teams already using Atlassian — Jira issues embed seamlessly in pages
- Extensive template library with 100+ templates for PRDs, meeting notes, retrospectives, decision logs, and more — accelerates team onboarding
- Real-time collaborative editing with inline comments, @mentions, and page watching enables asynchronous team communication at scale
- Unified observability platform — infrastructure monitoring, APM, logs, RUM, synthetics, and security all in one place, reducing tool sprawl
- 750+ out-of-the-box integrations covering virtually every cloud service, database, framework, and DevOps tool in modern stacks
- Watchdog AI automatically detects anomalies and correlates issues across the entire stack, significantly reducing mean time to resolution
You gain with Datadog
- +custom fields
Migration Steps
Audit and export your current workspace
Before touching Datadog, document what lives in Confluence: projects and tasks, custom fields, automations, integrations, and team permissions. Export a full CSV backup — most tools support this from Settings → Export. Pay particular attention to any workflow automations that your team relies on daily.
Set up your Datadog workspace
Create your Datadog workspace and replicate your project structure using tasks and projects. Start with the free tier — it covers the core workflow before you commit to a paid plan. Run with a single pilot team before migrating everyone.
Map your workflow equivalents
Find the closest Datadog equivalent for each Confluence feature your team relies on. projects and tasks in Confluence maps to tasks and projects in Datadog. Datadog supports custom fields — recreate your Confluence field schema here first. Prioritise the critical path: task creation, status tracking, and assignment.
Import your data
Datadog supports CSV import for tasks and projects and has 20+ native integrations. After importing, rebuild your key automations — Datadog's automation engine can replicate most rules you had in Confluence. Start with your most active project rather than importing everything at once.
Onboard your team
Run a 30-minute walkthrough covering the daily workflow: how to create tasks and projects, update status, and find your board. Datadog has a steeper learning curve. Budget 2–3 weeks for full adoption and schedule follow-up sessions after week one.
Run Confluence in parallel for two weeks
Keep Confluence read-only while your team works primarily in Datadog. This reduces risk and lets people reference historical context — old decisions, archived tickets, past sprint data — without slowing the migration. After two weeks with no new work going into Confluence, archive the workspace and make Datadog the official home.
Ready to switch?
Read the full Datadog review for pricing, integrations, and team fit details.