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Replacing an ALM system shouldn’t mean losing years of engineering history. Learn why legacy data retention matters, why common workarounds fail, and how purpose-built ALM data archiving helps organizations preserve traceability, compliance, and institutional knowledge after migration.
Client: A global leader in supply chain and logistics
Industry: Logistics, warehousing, multi-region transport operations
Team Size: 10,000+ Jira users across product, engineering, QA, support, and compliance
Instance Complexity: 2800+ Jira Data Center projects, 300K+ issues, 3M+ change events
As part of its enterprise-wide modernization initiative, the client needed to migrate from a legacy Jira Data Center (DC) instance to Jira Cloud – without disrupting global operations, ongoing releases, or SLA-driven support teams.
All this, with zero tolerance for:
Defects
Requirements
Test Cases
Artifacts
Ensure uninterrupted operations
Teams needed to keep working in Jira DC – planning, developing, resolving issues – even while data was being migrated in the background. No disruption to sprints. No access delays. No user rework.
Guarantee full-fidelity migration – beyond just issues
Everything had to come across:
Adapt and transform data on the fly
The Jira Cloud target used newer field templates, statuses, and workflows. The migration needed to:
Preserve auditability while masking PII
Several legacy Jira projects contained embedded PII in descriptions, custom fields, and comments. The client needed:
Keep source and target environments in sync
Since teams were split – some already piloting Jira Cloud, others still on DC – the solution leveraged OpsHub’s patented reverse sync technology to:
Marketplace tools and internal scripts couldn’t handle these conditions. They lacked:
That’s where OpsHub stepped in.
In high-stakes migrations like this one, OpsHub doesn’t apply a one-size-fits-all approach. Instead, based on data sensitivity, compliance needs, and timeline constraints, the right migration strategy is selected per project set.
For this client, OpsHub used a combination of Full History and History without Impersonation – allowing the migration to balance:
Below is a snapshot of OpsHub’s three-tiered migration strategies:
| Migration Approach | History Preserved | Author Attribution | Issue Key Retention | Comments, attachments, links retention | Complexity | Use Case |
|---|---|---|---|---|---|---|
|
Current State Migration |
✅(In comments) |
Service account |
❌ |
✅ |
Low |
Fast migrations, Limited audit requirements |
|
History w/o Impersonation |
✅ |
Service account (Original author in custom fields) |
✅(In custom field) |
✅ |
Moderate |
For semi regulated industries |
|
Full History Migration |
✅ |
Original user + date |
✅ |
✅ |
High |
Compliance-driven, audit-critical |
For projects with strict audit and traceability requirements – including QA, compliance, and support functions – OpsHub applied it’s patented Live++ migration approach, which included Full History Migration to retain every field change, comment, and transition with original issue id, history, user attribution and timestamps intact.
To meet the client’s mandate – move hundreds of Jira projects from Data Center to Cloud without pausing development, compromising compliance, or breaking reference integrity – OpsHub implemented its patented Live++ data migration approach tailored for high-velocity enterprise environments.
At the heart of this approach was OpsHub Migration Manager (OMM), which enabled:
Throughout the migration window, Jira DC users continued using the system as they always had – creating issues, editing them, deleting unwanted tickets, and even reorganizing items across issue types and projects.
OpsHub’s migration platform tracked these changes in real time, ensuring that the Cloud environment always reflected the latest structure and activity – no conflicts, no manual rework.
There was no freeze window.
OpsHub migrated more than just issues. The entire Jira DC context was rebuilt in Cloud – including:
Jira Cloud’s stricter validation model meant several legacy DC artifacts couldn’t be migrated 1:1.
OpsHub’s mapping engine handled:
All of this was done without manual intervention – ensuring correctness at scale.
With reporting pipelines and customer service dashboards still pointing to DC, the client couldn’t afford inconsistent or incomplete data mid-migration. OpsHub enabled reverse sync, continuously mirroring Jira Cloud changes back to DC to:
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