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Atlassian Data Center and Atlassian Cloud put different responsibilities on your organization. Data Center gives you control over hosting, networks, operating systems, upgrades, backups, and data location, but your administrators must operate and secure that stack. Cloud moves much of the infrastructure operation to Atlassian, while your team still has to evaluate identity, permissions, data protection, Marketplace apps, integrations, and regulatory requirements. For Jira Software, Jira Service Management, and Confluence, Atlassian currently says affected Data Center subscriptions and associated apps become read-only after March 28, 2029; Bitbucket and Bamboo are stated exceptions. The right decision therefore depends on control and compliance requirements, application fit, migration risk, and how much self-managed operations your team can sustain—not on a universal claim that one deployment is always safer.
What is the difference between Atlassian Data Center and Cloud?
Data Center is a self-managed deployment: your organization supplies and operates the infrastructure on which the Atlassian applications run. Cloud is a hosted service in which Atlassian operates the service infrastructure under a shared-responsibility model. The boundary changes who performs routine work, but it does not eliminate your security, governance, or application-management duties.
| Decision area | Data Center | Cloud |
|---|---|---|
| Infrastructure operation | Your team or an infrastructure provider runs the servers, operating systems, networks, storage, and supporting dependencies. | Atlassian operates the cloud service infrastructure; your team manages the tenant configuration and the controls assigned to customers. |
| Security updates | Atlassian supplies application releases and fixes, but administrators must test and apply them promptly and secure the surrounding stack. | Atlassian operates the service and delivers platform updates; you still manage identity, permissions, configuration, apps, integrations, and requirement mapping. |
| Data and hosting control | You choose the hosting environment and can place data and systems inside organization-specific network and operational boundaries. | You select from the controls and locations Atlassian offers and must verify that they satisfy your contractual, privacy, and regulatory requirements. |
| Backups and recovery | Your organization designs, runs, tests, and audits backup and recovery procedures. | Atlassian operates service-level resilience, while your team must understand the available recovery features and retain any customer-side exports or procedures required by policy. |
| Marketplace apps | Apps are installed and operated in your environment; compatibility, patching, and app data protection are your responsibilities. | Apps run under their vendors’ cloud models and permissions. You must assess security, privacy, data flows, and feature fit before migration. |
| Lifecycle horizon | For impacted Jira, Jira Service Management, and Confluence subscriptions, Atlassian states a March 28, 2029 expiration and read-only outcome. | Cloud is the destination Atlassian is directing customers toward for those products, subject to the service’s terms, capabilities, and your requirements. |
Atlassian’s Data Center security checklist and Cloud data-protection guidance describe the responsibilities behind this comparison.
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Neither option is automatically more secure for every organization. Cloud can reduce the amount of infrastructure your team must harden and maintain, while Data Center can provide control that is essential for particular network, residency, isolation, or customization requirements. Security depends on the controls in scope, how they are configured, and whether your organization can operate them consistently.
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What your team must secure in Data Center
Atlassian describes Data Center security as shared work between Atlassian and the customer. Atlassian supplies secure application releases and application-level fixes. Administrators must then implement and verify the controls around those releases, including:
- Applying security updates and supported versions promptly after testing.
- Hardening operating systems, databases, search services, containers, and other dependencies.
- Configuring product permissions, administrative access, audit settings, and authentication safely.
- Using protections such as private networking, firewalls, a web application firewall or VPN where appropriate, and network segmentation.
- Enforcing strong identity controls such as single sign-on and multifactor authentication through the organization’s identity provider.
- Protecting data in transit and at rest with suitable encryption and key-management procedures.
- Creating regular backups, storing them securely, testing restoration, and documenting recovery objectives.
- Monitoring the environment and conducting security reviews and audits.
Atlassian states explicitly, “Atlassian doesn’t take responsibility for self-managed hardware infrastructure.” That means a secure Atlassian application does not by itself make an unpatched host, exposed management interface, weak identity configuration, or untested backup system safe.
What changes in Cloud
Cloud transfers much of the physical and platform operation to Atlassian, but customer controls remain important. Atlassian recommends involving security, privacy, and legal stakeholders; mapping requirements to the shared-responsibility model; determining which requirements Atlassian or a product capability satisfies; and assessing Marketplace apps before migration. These are evaluation activities, not a blanket certification that Cloud meets every organization’s obligations.
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- Project permissions, data-sharing settings, external collaboration, API tokens, and service accounts can still create exposure.
- Marketplace apps and integrations may process or copy information outside Atlassian’s service boundary, so their vendors’ security and privacy terms matter.
- Retention, legal hold, export, incident-response, and audit requirements must be matched to the Cloud products and plans you will use.
A useful comparison is therefore “which team can operate the required controls reliably?” Data Center may be appropriate when your organization has mature infrastructure and security operations and needs direct control. Cloud may be preferable when reducing platform operations lowers risk, provided the available controls and data-processing terms satisfy your requirements.
Who is responsible for maintenance and security fixes?
Data Center leaves more maintenance in your operating model; Cloud removes much of the platform work but not the need for administration and assurance. The following division helps identify the staffing and process impact.
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| Workload | Data Center responsibility | Cloud responsibility |
|---|---|---|
| Application upgrades | Plan maintenance windows, test releases, upgrade nodes and connected services, and resolve version or plugin issues. | Atlassian operates the service updates; administrators still review release impact, change configuration safely, and test critical workflows and apps. |
| Operating systems and hardware | Your team owns capacity, host patching, storage, virtualization or containers, hardware failures, and network availability. | Atlassian operates the underlying platform; your team manages client-side integrations and access paths. |
| Identity and access | Configure and maintain the identity provider, SSO, MFA, directory synchronization, privileged access, and product permissions. | The same governance is required, using the Cloud identity and administration features available to your organization. |
| Backup and disaster recovery | Design schedules, retention, off-site storage, recovery procedures, and restoration tests. | Understand Atlassian’s service resilience and available export or recovery functions, then document any additional customer-side controls your policy requires. |
| Vulnerability response | Track Atlassian advisories and vulnerabilities in the whole stack, prioritize patches, and verify remediation. | Track Atlassian and app advisories, review customer-configured exposure, and address identity, integration, and app issues. |
| Performance and capacity | Size and tune the cluster, database, search tier, storage, network, and monitoring. | Manage configuration, usage patterns, integrations, and limits exposed by the service; platform capacity is operated by Atlassian. |
Cloud is not “maintenance-free.” It changes maintenance from patching servers and coordinating cluster upgrades to governing identities, settings, data flows, vendors, and change testing. A team that lacks either set of skills should account for that gap before selecting a deployment model.
When does Data Center control and compliance justify the extra work?
Data Center is most defensible when a documented requirement cannot be met by the Cloud controls, locations, integrations, or operating model available to you. The decision should begin with specific requirements rather than a preference for “on-premises” or “cloud.”
Control and hosting questions to answer
- Must the application and its database remain inside a particular facility, network zone, or jurisdiction?
- Do regulators or contracts require a control over infrastructure access that the Cloud service cannot provide?
- Do you need direct control of encryption keys, operating-system settings, network routes, or inspection devices?
- Does an internal system require a network connection or protocol that cannot be exposed safely to Cloud?
- Can your organization fund 24/7 monitoring, patching, backup testing, capacity planning, and incident response for the full stack?
A “yes” to a control question does not automatically make Data Center compliant: your implementation still has to be configured, evidenced, and audited. A “no” does not automatically make Cloud compliant: verify the product’s controls, contractual terms, data locations, and app behavior with your legal and security teams.
What Cloud assessment should include
Atlassian’s Cloud data-protection guidance recommends bringing security, privacy, and legal stakeholders into the assessment. Map each requirement to one of three outcomes: an Atlassian control, a customer configuration or process, or a gap that needs mitigation or rules out the move. Record evidence and ownership rather than treating a marketing security statement as a completed assessment.
What happens to Atlassian Data Center after 2029?
Atlassian’s current Data Center End of Life page says affected Jira Software, 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. The timetable is product-specific and time-sensitive, so confirm the live page and your contract before committing to a plan.
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| Date or period | Atlassian-stated change | Planning implication |
|---|---|---|
| March 30, 2026 | Support wind-down begins. New customers can no longer purchase new Data Center subscriptions or new Data Center Marketplace apps. | New deployments should not assume the same purchasing or support horizon as an existing installation. |
| Through March 30, 2028 | Existing customers can continue purchasing subscriptions, apps, and expansions, according to the stated lifecycle information. | Expansion may be possible during this period, but it does not remove the 2029 end date for impacted products. |
| Through March 28, 2029 | Atlassian states that technical support, critical-vulnerability security bug fixes, and connectors to Cloud continue. | Use the remaining support period to assess, remediate, test, and execute a controlled transition. |
| March 28, 2029 at 23:59 PST | Impacted subscriptions and associated apps expire and become read-only. | Users should not plan on normal production changes after this point; complete migration or another approved architecture beforehand. |
Are Bitbucket and Bamboo included?
No. Atlassian states that Bitbucket Data Center and Bamboo Data Center will not end of life in 2029 and describes a hybrid license for continued Data Center use alongside Cloud. Do not apply the Jira, Jira Service Management, and Confluence dates to those products without checking their specific terms.
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The lifecycle commitments can change, and the dates above are Atlassian’s published position rather than an independent guarantee. Treat the lifecycle page as a date-sensitive source during budgeting, procurement, and executive approval.
How do Marketplace apps and integrations affect the choice?
Apps are often the largest source of migration uncertainty. A workflow that works in Data Center may depend on an app’s server-side code, database access, scheduled jobs, custom fields, or network path that has no direct Cloud equivalent.
Build an app and integration inventory
- Export a complete list of installed apps, versions, administrators, license owners, and business owners.
- For each app, record the projects, spaces, issues, fields, workflows, automation rules, reports, and data it creates or modifies.
- Map outbound and inbound integrations, webhooks, service accounts, API tokens, IP allowlists, certificates, and scheduled jobs.
- Identify regulated, confidential, or personal data handled by each app and where that data is stored or transmitted.
- Ask whether a Cloud edition exists, whether its features and data model differ, and how the vendor handles migration or export.
- Test the replacement in a representative Cloud environment instead of assuming that a similar name means feature parity.
Atlassian’s Cloud guidance specifically calls for Marketplace app security and privacy assessment early in the process. The available guidance does not establish that every app, customization, integration, data type, or workflow will migrate unchanged; only a workload-specific test can establish that.
Typical app decisions
- Retain: a supported Cloud edition meets functional, security, and data-processing requirements.
- Replace: a native Cloud feature or another approved app covers the use case with acceptable change effort.
- Redesign: the process must be rebuilt because Cloud APIs, permissions, automation, or data models differ.
- Retire: the app is unused, duplicates native functionality, or no longer has an acceptable support or privacy position.
Should you migrate Jira or Confluence from Data Center to Cloud?
Migration is usually the prudent path for impacted products when the Cloud assessment closes your security, compliance, app, and integration requirements. It is not prudent to migrate merely because a deadline exists if a critical control or workload has not been proven in testing; instead, escalate the gap and create a dated remediation or exception decision.
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Signals that support a Cloud move
- Your organization wants to reduce responsibility for hardware, operating systems, cluster capacity, and platform patching.
- The identity, residency, retention, audit, and integration controls you require are available and accepted by security and legal reviewers.
- Critical Marketplace apps have supported Cloud editions or approved replacements.
- Data volume, customizations, and user populations fit the migration tools and a feasible cutover window.
- Business owners can test workflows and accept any redesigned processes before production cutover.
Signals to pause or retain Data Center temporarily
- A required integration depends on private network access or server-side behavior that has no tested Cloud design.
- A regulated workload cannot yet satisfy data-location, processing, retention, or evidence requirements in Cloud.
- Critical apps lack a supported Cloud path and no replacement has passed functional and security testing.
- You cannot staff the discovery, remediation, user readiness, and validation work before the lifecycle date.
- Your organization has not defined how read-only operation, archives, exports, and legal holds would work if migration slips.
For a complex program, Atlassian’s lifecycle FAQ recommends considering an Atlassian Cloud Migration Specialized Solution Partner. Evaluate any provider through your normal procurement, security, and conflict-of-interest processes; the cited guidance does not establish a particular provider’s availability, price, or suitability.
What are the phases of an Atlassian migration?
Atlassian’s Cloud Transformation Guide organizes migration into assess, plan, prepare, test, migrate, and post-migration phases. Treat the phases as gates: do not schedule production cutover while a prior phase still contains an unresolved blocker.
1. Assess
- Identify every Jira, Jira Service Management, and Confluence instance, project, space, directory, app, integration, and data owner.
- Measure data volume, attachment volume, custom fields, workflows, automation, permissions, inactive accounts, and archived material.
- Classify information by sensitivity, retention, residency, and legal-hold requirements.
- Document the current recovery objectives, audit evidence, and operational dependencies.
2. Plan
- Define the target Cloud organization, sites, products, identity architecture, domains, groups, administrators, and environment separation.
- Set scope: what moves, what is transformed, what is archived, and what is retired.
- Choose a migration sequence and success criteria for data, permissions, workflows, integrations, performance, and user acceptance.
- Reserve a cutover window, communications plan, support staffing, rollback or contingency approach, and decision owners.
3. Prepare
- Clean obsolete users, groups, projects, spaces, attachments, and app data where policy permits.
- Verify domains and identity synchronization, configure security baselines, and establish administrative roles.
- Install and configure the Cloud Migration Assistants recommended for production migration and resolve their reported issues.
- Prepare app replacements, integration credentials, network changes, DNS or links, training, and support documentation.
4. Test
- Run a representative migration or test dataset that includes the largest and most complex projects or spaces.
- Validate issue and page content, attachments, history, links, permissions, groups, workflows, automation, reports, and app behavior.
- Have business owners execute real scenarios, including search, notifications, approvals, service queues, exports, and audit tasks.
- Measure duration and identify anything that requires transformation, manual remediation, or a revised cutover window.
5. Migrate
For the production cutover, Atlassian’s guidance says to put the source instance into read-only mode before migration. In the classic approach, Data Center and Cloud are not linked; work completed in Data Center after migration begins does not appear in Cloud. Freeze changes, communicate the window, run the migration, validate the results, and release Cloud only after the agreed checks pass.
6. Post-migration
- Reconcile users, permissions, project or space counts, attachments, links, app records, and integration events.
- Monitor authentication, automation, notifications, queues, reports, API clients, and performance during the first production period.
- Keep the source environment protected and available according to your retention and rollback policy until the business signs off.
- Update runbooks, diagrams, asset inventories, incident procedures, access reviews, and compliance evidence.
What is the difference between classic and incremental migration?
Classic migration uses a defined cutover: the source becomes read-only, data is migrated, and users switch to Cloud. Incremental migration continuously synchronizes changes from Data Center to a Cloud staging environment while teams prepare, then uses a short final read-only period to capture the last changes before Cloud becomes production.
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| Characteristic | Classic migration | Incremental migration |
|---|---|---|
| Source and target relationship | Data Center and Cloud are not linked after migration starts; post-start source work does not flow to Cloud. | Changes are synchronized to a Cloud staging environment during preparation, then the connection ends after cutover. |
| Read-only period | The source is placed in read-only mode for the migration window. | A shorter final read-only period captures the last changes before Cloud is promoted. |
| Best fit | Smaller or simpler environments that can accept a single planned outage and freeze. | Large or complex environments that need extended preparation with less final downtime, provided synchronization and validation are feasible. |
| Main risk | Users may create untracked changes if communications or the freeze are not enforced. | Synchronization, staging configuration, and reconciliation are more complex; a staged copy is not automatically production-ready. |
Choose based on measured data shape, app behavior, user availability, and the downtime your business can tolerate. Neither approach removes the need for testing, a final validation, or a contingency plan.
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How should you control downtime, data integrity, and user readiness?
Migration duration is driven by data volume, attachments, app processing, network conditions, validation effort, and the number of workflows that must be tested. Do not promise a cutover duration until a representative test has measured it.
Before the window
- Publish the exact start and end times, affected products, user actions, support channels, and expected behavior.
- Freeze nonessential configuration changes and record the final source version, app versions, user counts, and data counts.
- Confirm backups or exports, restoration procedures, administrative access, credentials, certificates, and monitoring.
- Obtain business-owner sign-off on test results and a written go/no-go checklist.
During the window
- Place the source in the required read-only state and verify that users cannot continue editing.
- Run the migration with an operator log and capture warnings, retries, skipped objects, and app-specific actions.
- Keep stakeholders informed when checkpoints pass or a decision threshold is reached.
- Do not allow ad hoc edits in either environment that are outside the migration plan.
After the switch
- Validate counts and samples at the object level, not just whether the migration tool reports completion.
- Test authentication, permissions, search, links, attachments, notifications, automation, integrations, and critical business workflows.
- Ask representative users to complete acceptance scenarios before ending heightened support.
- Record defects, owners, deadlines, and the conditions under which the source can be retired.
What migration failures are most common, and how do you prevent them?
| Failure mode | Why it happens | Preventive action |
|---|---|---|
| Users or groups lose access | Identity domains, email addresses, group mappings, or permission schemes differ between environments. | Reconcile identities before testing, configure the identity provider early, and test both ordinary and privileged accounts. |
| App functionality disappears | The Data Center app has no Cloud edition, uses a different data model, or requires a separate migration. | Inventory app dependencies, obtain vendor migration instructions, and test an approved replacement before the cutover decision. |
| Data is incomplete or transformed | Unsupported fields, attachments, history, custom objects, or encoding issues are discovered late. | Use representative test data, compare source and target counts, and define manual remediation for exceptions. |
| Integrations stop working | URLs, IP allowlists, tokens, certificates, webhooks, or API behavior change. | Map every integration, create new credentials safely, test both directions, and monitor events after launch. |
| Unplanned downtime expands | Migration and validation estimates were based on a small or clean sample. | Time a realistic rehearsal, include business acceptance in the window, and use incremental migration when its added complexity is justified. |
| Source and target diverge | Users continue editing Data Center after the migration starts or teams perform unscheduled changes. | Enforce read-only mode, communicate the freeze, restrict administrative changes, and log exceptions. |
| Compliance evidence is missing | Controls were discussed but not mapped to owners, settings, logs, or procedures. | Have security, privacy, and legal reviewers approve a control-to-evidence matrix before production. |
How do you make the final Data Center-versus-Cloud decision?
Use a written scorecard with weighted requirements rather than a generic “cloud versus on-premises” preference. A sample structure is below; set the weights with your security, infrastructure, product, legal, and business stakeholders.
| Criterion | Evidence to collect | Decision question |
|---|---|---|
| Security operations | Patch SLAs, staffing, monitoring, incident records, backup tests, and audit findings. | Can we operate the full Data Center stack to the required standard, or does Cloud reduce a material operational risk? |
| Compliance and data | Residency, retention, legal hold, encryption, access, processing, and contractual requirements. | Does the selected model provide acceptable controls and evidence for every workload? |
| Application fit | App inventory, vendor roadmaps, integration maps, test results, and redesign estimates. | Can critical workflows run with supported Cloud apps or an approved Data Center exception? |
| Migration risk | Data measurements, rehearsal duration, defect log, user acceptance, and cutover plan. | Can we complete and validate the move before the applicable lifecycle date without unacceptable disruption? |
| Lifecycle | Product-specific Atlassian dates, contract terms, support commitments, and procurement timing. | What is the cost and risk of staying, moving, archiving, or using a hybrid approach? |
For impacted Jira Software, Jira Service Management, and Confluence environments, include the March 28, 2029 read-only outcome in the decision’s timeline and risk register. For Bitbucket and Bamboo, perform a separate product-specific assessment because Atlassian states they are exceptions to that 2029 end-of-life event.
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The practical conclusion is conditional: choose Cloud when its controls and app ecosystem meet your requirements and reducing infrastructure responsibility improves your risk position; retain or extend Data Center only where documented control, compliance, or workload needs justify the operational burden and the remaining lifecycle supports that plan. In either case, assign owners, test the controls, and revisit the decision when Atlassian’s lifecycle terms or your requirements change.
Frequently Asked Questions
Can Atlassian Data Center and Cloud run at the same time?
They can coexist during a planned transition, but coexistence is not automatically a synchronized production architecture. Define which system is authoritative, how users and integrations are routed, how data is reconciled, and when the older environment will be retired; incremental migration uses a staging relationship only until cutover.
What does read-only Data Center operation mean for business teams?
Users can generally view existing information but should not rely on the instance for normal production edits, workflow transitions, or new service activity once the applicable subscription is read-only. Plan exports, archives, legal holds, and user communications before the lifecycle date instead of treating read-only access as a continuing operating license.
Do Jira, Jira Service Management, and Confluence have identical migration requirements?
No. They share the published Data Center lifecycle impact, but their data structures, apps, integrations, permissions, and business workflows differ. Assess and test each product and each connected service separately, even when they share an identity directory.
How far in advance should a large migration begin?
The sources do not prescribe a universal lead time. Start with inventory and a measured rehearsal, then work backward from the applicable lifecycle date while allowing time for app replacement, security review, user acceptance, remediation, and a contingency window.
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