750-900
Users assessed
Approximate user range reviewed and migrated from the legacy Atlassian Server environment.
Atlassian Cloud Migration Case Study
Legacy Atlassian Server to Cloud Migration for a Public-Sector Organization
AtlasOptima helped a Canadian public-sector organization move from a 10+ year legacy Atlassian Server environment to Atlassian Cloud through readiness assessment, app and data rationalization, sandbox validation, UAT, planned cutover, and post-migration stabilization.
This public case study is anonymized. Customer identity, internal architecture documents, and implementation artifacts are withheld unless publication approval is granted.
600K-750K
Jira issues under migration scope
80K-100K
Confluence pages under review
95
Jira projects assessed
Jira project scope reviewed for migration readiness, active use, permissions, and cleanup needs.
65
Confluence spaces assessed
Confluence spaces reviewed for required content, stale information, ownership, and migration fit.
30+
Marketplace apps reviewed
Apps were reviewed for Cloud compatibility, replacement options, retirement, or process redesign.
The migration problem
The organization was running an old Atlassian Server environment that had not been meaningfully upgraded for several years. It still supported important internal teams, but the operating risk was increasing as versions, apps, infrastructure responsibilities, and governance expectations moved further from a modern target state.
The migration goal was not simply to move data from one system to another. The real goal was to reduce legacy Server risk, avoid carrying unnecessary configuration debt into Cloud, validate critical work before production cutover, and give internal administrators a more sustainable Atlassian Cloud foundation.
Risk areas reviewed
| Risk area | Why it mattered |
|---|---|
| Security | Older Server versions increased exposure to unpatched vulnerabilities. |
| Supportability | Legacy versions were harder to maintain and could be outside practical vendor-support paths. |
| Upgrade complexity | Years of missed upgrades made direct modernization more difficult. |
| App compatibility | Marketplace apps needed Cloud compatibility, replacement, or retirement decisions. |
| Infrastructure dependency | Internal teams carried server, backup, patching, and upgrade responsibility. |
| Governance | Identity, access, auditability, and compliance controls were harder to standardize. |
How AtlasOptima structured the work
AtlasOptima used a structured migration program focused on readiness, rationalization, validation, and stabilization. That sequence helped the team understand the environment before production movement and reduce the likelihood of migrating legacy complexity that no longer served the organization.
Environment discovery
- Jira and Confluence versions, upgrade path, and compatibility risk.
- Active versus stale projects, spaces, users, groups, and permissions.
- Workflows, screens, fields, schemes, integrations, APIs, and webhooks.
Cloud architecture
- Cloud site structure, identity model, and Atlassian Guard readiness where required.
- Permission standardization, admin model, change control, auditability, and reporting.
- Cloud-compatible app strategy and data-retention decisions.
Validation and cutover
- Sandbox migration before production movement.
- Error review, UAT, permission testing, app testing, and business validation.
- Planned production cutover window followed by hypercare and issue triage.
Evidence from the migration scope
AtlasOptima helped the customer assess a broad Jira and Confluence footprint before production cutover. The evidence below should be read as selected engagement scope, not as a typical migration size or expected result.
Jira issues
Approximately 600,000-750,000 Jira issues under review and migration scope.
Confluence pages
Approximately 80,000-100,000 Confluence pages reviewed for required migration.
Marketplace apps
30+ apps reviewed; 12-18 legacy app dependencies retired, replaced, or redesigned.
Custom fields
140+ custom fields reviewed; approximately 40-50 duplicate or unused fields cleaned up.
Inactive content
35-45 stale projects or spaces archived or excluded from the migration scope.
Validation
Sandbox migration, UAT with approximately 50-60 validators, and planned weekend cutover.
Before and after
| Area | Before | After |
|---|---|---|
| Platform | 10+ year legacy Atlassian Server environment. | Modern Atlassian Cloud environment. |
| Jira data | 95 projects and approximately 600,000-750,000 issues under review. | Active and required Jira projects migrated and validated. |
| Confluence data | 65 spaces and approximately 80,000-100,000 pages under review. | Required spaces migrated and validated. |
| Apps | 30+ Marketplace apps, including legacy dependencies. | 12-18 dependencies retired, replaced, or redesigned. |
| Custom fields | 140+ fields with duplication and legacy clutter. | Approximately 40-50 unused or duplicate fields cleaned up. |
| Infrastructure | Self-managed patching, backups, upgrades, and server maintenance. | Atlassian-managed Cloud foundation with lower infrastructure burden. |
| Validation | High migration uncertainty before testing. | Sandbox migration, UAT, app testing, permission testing, and planned weekend cutover. |
Outcome
AtlasOptima helped the organization reduce legacy Atlassian Server risk and realize the value of Atlassian Cloud through a structured, secure, and validated migration approach.
The migration reduced dependency on self-managed patching, infrastructure maintenance, and major version upgrades. It also improved the foundation for identity and access governance, auditability, modern Jira and Confluence capabilities, Cloud scalability, and future Atlassian Intelligence and Rovo readiness.
What similar teams should validate
Legacy Atlassian migrations become risky when data movement starts before ownership, app strategy, permissions, identity, validation, and cleanup decisions are clear. Similar teams should answer these questions before they commit to a cutover plan.
Which projects, spaces, users, groups, apps, automations, workflows, fields, and integrations are truly in scope?
Which content is active and required, and which projects or spaces can be archived or excluded before migration?
Which Marketplace apps have Cloud equivalents, and which require replacement, retirement, or process redesign?
Which custom fields, schemes, permissions, and groups can be consolidated before migration?
Which business owners will validate key projects, spaces, apps, permissions, and reports during UAT?
Which identity, SSO, MFA, admin, audit, and governance controls need to be ready on day one in Cloud?
Common Questions
Legacy Server to Cloud Migration Questions
Questions that usually come up when public-sector or regulated teams evaluate a legacy Jira and Confluence Server move to Atlassian Cloud.
What was included in this Atlassian Server to Cloud migration case study?
The selected engagement involved a 10+ year legacy Atlassian Server environment for a Canadian public-sector organization. AtlasOptima assessed approximately 750-900 users, 95 Jira projects, 65 Confluence spaces, 600,000-750,000 Jira issues, and 80,000-100,000 Confluence pages.
How did AtlasOptima reduce migration risk before production cutover?
AtlasOptima used a controlled migration approach that included readiness assessment, app and data rationalization, sandbox migration, blocker review, user acceptance testing, permission testing, app testing, cutover planning, and post-go-live hypercare.
Are these migration results guaranteed for every Atlassian environment?
No. These are case-qualified findings from one selected engagement. Migration scope, cleanup volume, app replacement effort, UAT needs, downtime risk, and Cloud readiness depend on each organization's environment and constraints.
Need a safer path out of legacy Atlassian Server?
AtlasOptima can help assess users, projects, spaces, apps, permissions, custom fields, integrations, data quality, and validation needs before your migration plan turns into a cutover risk.