ToolStack
Migration Guide

Migrating from Jira to Datadog

Datadog fits scaleup and enterprise teams best and has a steep learning curve. If you're moving from Jira, the first week is the hardest — new UI, different terminology, rebuilt automations. This guide compresses that learning curve with a step-by-step migration plan.

At a Glance

Jira
4.3/5 · 7,500 G2 reviews
  • Industry standard for software development teams — most PMs will encounter Jira in their career
  • Deepest configurability of any project management tool with custom fields, workflows, and screens
  • 3,000+ marketplace integrations covering virtually every tool in the product stack
Datadog
4.5/5 · 600 G2 reviews
  • 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
Full side-by-side comparison: Jira vs Datadog

You leave behind

  • roadmapping
  • sprint planning
  • backlog management

Migration Steps

1

Audit and export your current workspace

Before touching Datadog, document what lives in Jira: issues, epics, and sprints, custom fields, automations, integrations, and team permissions. Export a full CSV backup — most tools support this from Settings → Export. Pay particular attention to any custom fields and workflow automations that your team relies on daily.

2

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.

3

Map your workflow equivalents

Find the closest Datadog equivalent for each Jira feature your team relies on. issues, epics, and sprints in Jira maps to tasks and projects in Datadog. Datadog supports custom fields — recreate your Jira field schema here first. Prioritise the critical path: task creation, status tracking, and assignment.

4

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 Jira. Start with your most active project rather than importing everything at once.

5

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.

6

Run Jira in parallel for two weeks

Keep Jira 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 Jira, archive the workspace and make Datadog the official home.

Ready to switch?

Read the full Datadog review for pricing, integrations, and team fit details.

Read Datadog Review →Compare Jira vs Datadog