Scenario: a Bitbucket and Jira shop

Teams on the Atlassian stack (Bitbucket for code, Jira for tickets) are often the teams that already log time, because Jira worklogs are right there in the workflow. That changes which effort method fits, so this walkthrough differs from the GitHub + Jira scenario in more than the code host.

The goal

Jira contributes tickets, worklogs and sprints; Bitbucket contributes commits and pull requests. Together they give EngLedger logged time with code evidence behind it, the strongest position for effort reporting, because hours are claimed and corroborated.

1. Connect Jira. Follow the Jira guide. Select the projects where engineering work and worklogs live.

2. Connect Bitbucket. Follow the Bitbucket guide. EngLedger creates a connection per workspace your account can access; deselect repositories that aren't product engineering.

3. Add people and link identities. Same Atlassian account usually means the same email across Jira and Bitbucket, so email auto-linking tends to catch nearly everyone. Sweep the leftovers on the Identities page (see people and identities).

4. Choose the worklogs effort method (if the logging is real). In Settings, pick worklogs as the effort method if your team logs time consistently. Logged hours are actual claims, not estimates, which auditors and finance prefer. If logging is patchy, commit sessions give a more consistent (if narrower) picture: the effort model covers the trade-off honestly.

5. Keep Jira keys in branches and commits. Bitbucket teams usually branch per issue (ENG-123-fix-billing), which is exactly what EngLedger's linker reads: keys in branch names, commit messages and PR titles connect code to tickets automatically.

6. Set classification rules. Defaults classify by issue type from day one; refine with rules on labels, components or projects (see classification rules).

7. Read the first reports. The Cost Report and Capitalisation Effort Split give the headline numbers. Because this stack has both worklogs and commits, also open the Data Quality report: it cross-checks the two, flagging logged time with no commits behind it and commits with no logged time, the gaps to close before a period is audit-ready.

Worth knowing on this stack

• Bitbucket's API ceiling (1,000 requests/hour) is lower than other providers', so the initial backfill of a large workspace may take a few sync windows. Incremental syncs settle well inside the limit.
• If a Jira token expires, the integration stops and shows Needs reauth rather than silently retrying: reconnect from the Integrations page. The troubleshooting page covers the states.

From here, add teams and initiatives for reporting structure, or follow the R&D capitalisation workflow to period close. The full integration list is on integrates-with.