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Atlassian Data Center and Atlassian Cloud differ most in who operates the underlying environment and how much control your organization retains over it. Data Center gives your team responsibility for infrastructure, security operations, and maintenance; Cloud changes that boundary, but still requires your organization to assess security, privacy, compliance, and app suitability. The right choice depends on your requirements—not on a universal claim that one option is safer or easier. For Jira, Jira Service Management, and Confluence, Atlassian’s announced Data Center lifecycle also makes a migration plan a current planning issue.
What is the difference between Atlassian Data Center and Cloud?
Data Center is a self-managed deployment: your organization operates the environment in which its Atlassian products run. Atlassian provides product releases and application-level security fixes, but administrators must deploy updates, configure the products and surrounding systems, and protect the infrastructure. Atlassian’s Data Center security checklist states that “Atlassian doesn’t take responsibility for self-managed hardware infrastructure.”
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Cloud changes the operating model and the boundary of responsibility. Atlassian’s guidance asks customers to understand the shared-responsibility model and determine how their requirements are met by Atlassian or by product capabilities. It does not remove the need for customer assessment, especially for security, privacy, legal obligations, identity, and Marketplace apps.
| Decision area | Data Center | Cloud |
|---|---|---|
| Environment operations | Your organization manages its self-managed environment and infrastructure. | Responsibility is shared differently; assess the relevant controls and requirements with Atlassian’s shared-responsibility guidance. |
| Security work | Administrators must apply security updates and manage configuration, access, encryption, networking, backups, and audits. | Evaluate how Atlassian and product capabilities meet your requirements, and identify the work that remains with your organization. |
| Control and compliance | Self-management can support organization-specific control needs, but also places operational tasks on your team. | Assess your actual compliance and data-protection needs; Cloud is not automatically compliant for every organization. |
| Apps and integrations | Review the apps and integrations used in your current deployment. | Assess Marketplace app security, privacy, and suitability before migration; do not assume every app or integration has an equivalent. |
| Migration | The source environment must be assessed, prepared, tested, and cut over. | The destination must be validated against real data, workflows, users, and app requirements. |
The table describes operating responsibilities, not a measured security or cost ranking. Atlassian’s cited guidance does not establish that Cloud produces better security outcomes, lower maintenance costs, or a higher migration-success rate for every organization.
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Is Atlassian Cloud more secure than Data Center?
There is no support here for a blanket verdict that Cloud is more secure. The meaningful comparison is which team performs each security task, how that task is implemented, and whether the resulting controls meet your organization’s requirements.
What administrators must handle in Data Center
Atlassian’s security checklist assigns administrators work across the product and its operating environment. Depending on the deployment, that includes:
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- Managing user access and implementing identity protections such as MFA and SSO.
- Using encryption and securing operating systems and dependencies.
- Protecting the network, including measures such as private networking, a WAF, or a VPN.
- Maintaining regular backups and carrying out audits.
These controls require people, processes, and infrastructure. A team choosing Data Center should be confident it can own those ongoing responsibilities, not just install the software. In particular, a plan to patch the application is not a complete security plan if the underlying environment, identity controls, backups, and access practices are neglected.
What changes when evaluating Cloud
Atlassian’s Cloud data protection guidance recommends involving security, privacy, and legal teams; mapping requirements to the shared-responsibility model; and assessing Marketplace apps early. Treat these as assessment steps rather than proof that a specific Cloud configuration satisfies a regulation or internal policy.
For each requirement, record who is responsible, what product capability or organizational process addresses it, and what evidence your reviewers need. Where a requirement depends on an app, integration, or data-handling practice, assess that item specifically instead of assuming it inherits the same protections as the core Atlassian service.
Who is responsible for maintenance and recovery?
Data Center puts more of the day-to-day operational work on your administrators. Cloud changes that division of labor, but your team still needs to review its responsibilities, access model, apps, and recovery requirements rather than treating the move as “maintenance-free.”
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Data Center operational ownership
Before selecting or retaining Data Center, identify owners for updates, secure configuration, infrastructure, access, encryption, backups, and audits. Atlassian supplies secure releases and application-level fixes, but your administrators must apply and operate them. The responsibility for self-managed hardware infrastructure remains with the organization.
That model can be appropriate when your organization has a concrete need for self-management and the staff and processes to operate it. The tradeoff is not simply control versus convenience: control has to be exercised through reliable maintenance and security operations.
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For Cloud, map each policy, legal, and security requirement to the shared-responsibility model and the relevant product capabilities. Bring security, privacy, and legal stakeholders into the decision early, and include app review in the assessment rather than waiting until migration testing.
Do not infer from a change in infrastructure operator that your organization’s own access decisions, app choices, or compliance obligations have disappeared. The sources support a changed responsibility boundary, not a universal conclusion about what a particular customer must do or whether its controls are sufficient.
What happens to Atlassian Data Center after 2029?
Atlassian’s current Data Center End of Life page says impacted Jira, Jira Service Management, and Confluence Data Center subscriptions and associated Marketplace apps expire on March 28, 2029 at 23:59 PST and become read-only. Atlassian’s stated timeline is product-specific: Bitbucket and Bamboo Data Center are exceptions and are not ending in 2029.
| Date or period | Atlassian’s stated lifecycle detail |
|---|---|
| March 30, 2026 | Atlassian says support began winding down in phases. New customers could no longer purchase new Data Center subscriptions or new Data Center Marketplace apps after this date. |
| Through March 30, 2028 | Atlassian says existing customers can continue purchasing subscriptions, apps, and expansions through this date. |
| Through March 28, 2029 | Atlassian says technical support, critical-vulnerability security bug fixes, and connectors to Cloud continue through this date. |
| March 28, 2029 at 23:59 PST | Impacted subscriptions and associated apps expire and become read-only, according to Atlassian. |
| After 2029 | Atlassian says Bitbucket and Bamboo Data Center continue past 2029 under a hybrid license for continued Data Center use alongside Cloud. |
These dates and commitments are Atlassian’s published lifecycle information and can change; verify the live page when planning a purchase, renewal, or migration. Do not apply the Jira, Jira Service Management, and Confluence outcome to Bitbucket or Bamboo, or assume that every Data Center product has the same lifecycle.
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Should we migrate Jira or Confluence from Data Center to Cloud?
Consider migration if Cloud fits your security, compliance, app, data, and operating requirements—and, for impacted products, include Atlassian’s lifecycle timeline in your plan. Do not migrate solely on the assumption that every workflow or app will transfer unchanged. Atlassian recommends a phased approach: assess, plan, prepare, test, migrate, and complete post-migration work.
1. Assess the current environment
Inventory the products, data, users, apps, integrations, and customizations that matter to the people who rely on the deployment. Identify which items are essential, which need redesign or replacement, and which require further validation in Cloud. The assessment should include business owners as well as technical administrators: they can help identify workflows or data that a technical inventory alone may not make obvious.
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Start the security and privacy review at this point. Map organizational requirements to the Cloud shared-responsibility model, involve legal stakeholders, and assess Marketplace apps for security and privacy. A migration tool or successful data transfer does not, by itself, establish that an app is suitable or that a compliance requirement is met.
2. Plan the target and cutover
Define the desired Cloud environment, migration scope, test criteria, user communications, and cutover approach before moving production data. Decide how you will verify the data and workflows users need, and assign people to investigate failures or mismatches. The relevant proof is whether your actual use cases work in the destination, not just whether a migration process completes.
Atlassian’s Cloud Transformation Guide distinguishes classic migration from incremental migration. In a classic migration, the Data Center and Cloud environments are not linked; work performed in Data Center after migration begins does not appear in Cloud. Plan a cutover window and prevent production use of the source from creating changes that the destination will miss.
3. Prepare and test before production
Prepare the source and destination according to the migration plan, then test the process and validate the results before the production cutover. Test the apps and integrations that are essential to the work, along with representative data and workflows. The available guidance calls for app assessment and testing but does not establish parity for any particular customer’s apps, configurations, or data.
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Atlassian recommends Cloud Migration Assistants for production migration. Use testing to identify issues that would otherwise surface during the production move, and revise the plan where the destination does not meet a real requirement.
4. Choose the cutover approach deliberately
For a classic migration, Atlassian’s production cutover guidance calls for putting the source instance in read-only mode before migration. Since the environments are not linked, users’ subsequent source-side work will not be reflected in Cloud. The project therefore needs a clearly communicated window in which production changes stop and the migration team can complete the move and validation.
Incremental migration can reduce the length of the final read-only period by syncing Data Center changes to a Cloud staging environment while teams prepare. A short read-only window is still needed to capture final changes before Cloud becomes production. After cutover, the environments are no longer connected, so do not treat them as continuously synchronized systems.
5. Validate after migration
After the move, check the data, workflows, apps, integrations, and user access that were defined as important during planning. Give users a clear way to report problems and route those reports to owners who can distinguish migration issues from expected differences in the target. The post-migration phase matters because successful transfer is not the same as proving that the destination is ready for normal work.
When is staying on Data Center the better fit?
Data Center may be the better fit when self-management is a genuine requirement and your organization can operate the security and maintenance work it entails. For Jira, Jira Service Management, and Confluence, however, a decision to stay must also account for Atlassian’s published end-of-life timeline.
- Control: Your organization has a specific need to manage its own environment and is prepared to carry the associated operational responsibilities.
- Security operations: You have owners and processes for prompt updates, secure configuration, identity and access controls, encryption, network protection, backups, and audits.
- Requirements fit: Your security, privacy, legal, and compliance teams have assessed the selected deployment model against actual requirements rather than relying on a general label such as “secure.”
- Apps and integrations: The tools your users depend on have been assessed for the target environment, including suitability and data-handling concerns.
- Lifecycle: You have verified the lifecycle that applies to each product and have a practical plan for the relevant dates.
These checks are decision criteria, not a claim that one model will meet every organization’s requirements. If any critical requirement remains unclear, resolve it before committing to a migration or continuing a deployment whose lifecycle is changing.
How should we make the decision?
Compare the options requirement by requirement, then separate facts that apply across the organization from questions that depend on a particular product, app, or workflow. A concise decision record can prevent teams from mistaking a general preference for evidence that the chosen environment will work.
- List non-negotiable requirements. Ask security, privacy, legal, IT, and product owners to identify the controls, operating needs, and workflows that must be met.
- Assign an owner to each control. For Data Center, make explicit who handles infrastructure and each operational security task. For Cloud, map responsibilities to Atlassian, product capabilities, or your own organization using the shared-responsibility model.
- Review apps and integrations individually. Record which are essential and assess their security, privacy, and suitability for the intended environment.
- Test the destination against real work. Choose representative data and workflows, then define what counts as a successful result before testing.
- Plan the lifecycle and cutover together. Account for the applicable product dates, the migration approach, the read-only window, and communications to affected users.
- Record unresolved risks. Document what has not yet been validated, who will resolve it, and what decision depends on that answer.
Atlassian recommends considering a Cloud Migration Specialized Solution Partner when migration is complex. That is an option for additional migration assistance, not evidence that any particular partner is available or suitable; evaluate any prospective provider independently.
Frequently Asked Questions
Does a successful migration mean our Cloud setup is compliant?
No. A completed transfer demonstrates neither regulatory compliance nor that every organizational control is satisfied. Compliance reviewers must assess the actual Cloud configuration, apps, data practices, and applicable requirements.
Can we keep Data Center and Cloud running during migration?
Atlassian describes incremental migration as syncing Data Center changes to a Cloud staging environment during preparation. That does not mean the two environments remain connected after production cutover.
Will our users need training after a Cloud migration?
User readiness is part of migration planning, but the amount of training depends on what changes in your environment and how your teams work. Identify affected groups and explain the cutover and any validated workflow differences before launch.
Does Atlassian recommend help from a migration partner?
Atlassian’s lifecycle FAQ recommends considering a Cloud Migration Specialized Solution Partner when a migration is complex. That recommendation does not establish the availability, terms, or suitability of any specific provider.
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