JIRA SYNCHRONIZER
Migrate Jira data and keep it in sync
The Jira Synchronizer moves issues, comments, attachments, tests and workflows between Jira instances — as a migration or as continuous one-way replication. Instead of a big-bang move, each transfer runs through verifiable stages: fetch source data, prepare the target, write, verify and document the run. Mappings for fields, statuses, users and links keep the target semantically intact.
Pipeline, not big bang
Each run follows defined stages: fetch source state, prepare the target, write new and changed issues, handle deleted tickets, verify the result and store the run protocol. Which stages are active and in what order is configured per scope. Dry runs are available, individual stages can be repeated.
Fields, statuses, users, links
Jira instances rarely look the same. Custom fields, statuses, users, issue types, workflows and links have to be translated in a way that still makes sense. The Jira Synchronizer maps those differences through configurable templates: required fields per issue type, defaults, ignore lists and value transforms are tunable.
Test management included
Teams running their tests with Xray usually lose the relationships between test, plan, set and execution in a standard migration. The Jira Synchronizer carries tests, test plans, test sets, test executions and pre-conditions across — including test steps, datasets, statuses and links.
Scalable and traceable
Under the hood: Spring Boot with a reactive stack, MongoDB as the cache and persistent state, a scheduler for recurring runs, and a web UI showing live status per scope. Each run produces a protocol as a Confluence page — with all notes, anomalies and skipped tickets.
Migration, consolidation, archival
Typical projects: a legacy Jira landscape is being retired — the synchronizer moves issues onto the target step by step, with dry runs upfront and staged cut-over waves. Multiple Jira instances are merged into one. Old tickets need to leave the productive Jira without losing history.