Which fits a team that already runs self-managed GitLab for code and CI
If your engineers already host repositories, code review and pipelines in self-managed GitLab, the main question is whether issue tracking should sit next to that work or stay in Jira. GitLab fits best when planning is mostly engineering planning: issues that link directly to merge requests, branches and pipeline results, and boards that engineers already check during review. The Free tier covers issues, issue boards and merge requests, so a team that does not need epics can keep its data on its own servers without adding a per-user license. Jira fits better when work crosses many teams with different workflows, when the team depends on Jira-specific marketplace apps, or when existing reporting and dashboards built in Jira are used by managers and non-engineering stakeholders who will not move to a new tool.
The decision turns on three checks. First, confirm whether you need epics. The GitLab epics documentation says epics are available in Premium and Ultimate, including self-managed installations, and that nested child epics are Ultimate only, so the cost of the planning layer depends on which tier you need. Second, test the Jira importer against a real sample. GitLab's importer brings over titles, descriptions and labels, maps Jira users to project members, and appends Jira fields with no GitLab equivalent to the description as plain text. It does not bring over assignees or comments, and GitLab's documentation points to an open epic on that gap. If your history depends on comments or ownership, plan to keep the Jira export as an archive or to rebuild that context by hand. Third, measure your process complexity. Teams with simple statuses and a single backlog usually map cleanly, while teams with multi-level approvals, custom field schemas or cross-project dependencies should map workflows on paper before committing.
Which option fits which team situation
This table matches common Jira situations to the option that fits better, with the reason tied to facts about GitLab, the Jira importer and the other platforms covered on this site. Read each row against your own team's workflow, and treat the dash cells as points to confirm with the vendor rather than as answers.
| Situation | Better fit | Reason |
|---|---|---|
| Issues tied closely to merge requests and pipelines | GitLab | Issues, merge requests and CI/CD sit in one self-managed instance, so planning and code review share one permission model and one place to look. |
| Portfolio planning across many teams | OpenProject or Plane | Epics exist in GitLab Premium and Ultimate, but nested child epics are Ultimate only, so check the depth you need before choosing GitLab for portfolio work. |
| Heavy dependence on Jira Marketplace apps | Neither, confirm first | Marketplace apps do not move with issues, and GitLab's importer does not carry over workflows or add-ons. List each app and confirm a replacement before you commit. |
| Air-gapped deployment | GitLab | GitLab documents offline, air-gapped installs, and its installation methods include the Linux package. Confirm the offline update path with your own network team. |
| Migrating full issue history including comments and assignees | Neither as a direct import | GitLab's importer skips assignees and comments, and OpenProject's Jira Migrator is beta and limited to Data Center. Plan an export and archive step for full history. |
| Small team wanting zero license cost on the code platform | GitLab Free | The Free tier is MIT-licensed for the code outside the ee/ directory, but epics require Premium or Ultimate. Confirm which features your team needs before relying on Free. |
| Teams that need both Jira-style agile boards and Gantt views | OpenProject | OpenProject covers Gantt planning and portfolio features in its Enterprise plans, which makes it a closer match for planning-heavy work than GitLab's issue boards. |
Where the data lives and who controls it
Jira Cloud is operated by Atlassian. Your organization controls projects, permissions and users inside the service, but the infrastructure, patching and availability of the platform sit with the vendor. Data residency and processing locations are contractual and product-specific, so the reader should not assume them from the product name alone.
- Operator control: Atlassian runs the hosting, upgrades and backups of the service, and your team administers the tenant.
- Backup scope: Atlassian's backup for cloud covers work items, board and sprint data, comments, users and project configuration, but not automation rules, third-party apps or Assets, so those need separate handling.
- Exit path: Moving data out depends on export options and on what the export format preserves.
- Identity: Sign-in and provisioning follow the tenant's configured identity provider and Atlassian's admin controls.
- Compliance evidence: Evidence comes from the vendor's assurance documents and your own configuration reviews.
Confirm with Atlassian which data residency and processing locations apply to your contract, and which compliance reports are available to your auditors.
Self-managed GitLab runs in infrastructure you choose: your data center, a cloud account you control or an air-gapped network. The database, repositories, attachments and backups stay with your team, and your team decides the upgrade calendar. GitLab supports installation through the Linux package, the Helm chart, the GitLab Operator, Docker or from source.
- Offline operation: GitLab documents running self-managed instances in offline, air-gapped environments, with separate guidance for its security scanners and GitLab Duo Self-Hosted.
- Scale range: GitLab's reference architectures range from 1,000 users at 20 API requests per second to 50,000 users at 1,000 API requests per second.
- High availability: For 3,000 or more users, the docs generally recommend a high availability strategy using Gitaly Cluster with Praefect, PostgreSQL with Patroni, Redis Sentinel and Consul.
- Kubernetes limit: Running stateful components such as PostgreSQL and Redis inside Kubernetes is not supported; the Cloud Native Hybrid architecture keeps them on VMs or managed services.
- Disaster recovery: GitLab documents Geo and backup and restore procedures that your team must test.
Confirm the reference architecture and installation method that match your user count, and whether your air-gapped update process can meet GitLab's release and upgrade-stop schedule.
Identity decides who can sign in, who is provisioned and who is removed when they leave. Both products can sit behind your identity provider, but the features that enable this differ by tier and by deployment, so the reader should check them against the exact plan and version in scope.
- Authentication options: GitLab documents its authentication and authorization methods for self-managed instances, which should be mapped to your identity provider.
- Provisioning: Confirm whether user provisioning and deprovisioning are available on the tier you plan to buy, and whether they run automatically.
- Admin separation: Keep the instance administrators separate from the people who manage the project data.
- Jira side: Atlassian's tenant identity settings govern Jira Cloud users, and they must be reviewed separately when people move.
- Mapping users: The GitLab Jira importer maps Jira users to project members, so identity records must be reconciled before import.
Confirm with GitLab which authentication and provisioning features your tier includes, and document who holds administrator rights on each side.
Hosting choice changes who produces compliance evidence. With Jira Cloud, much of the infrastructure evidence comes from the vendor. With self-managed GitLab, your team produces the configuration, patching, backup and access evidence that auditors will request, and DeployOpen prepares systems, controls and evidence for assessments without issuing audit reports.
- Shared responsibility: Write down which controls the vendor covers and which your team owns for each hosting model.
- Hardening baseline: GitLab publishes hardening recommendations that can serve as a configuration reference for your own standard.
- Backup evidence: Document backup frequency, restore tests and retention, and test restores from the GitLab backup and restore documentation.
- Patch evidence: Record the release you run against the maintenance policy and the upgrade stops that apply.
- Auditor role: Independent auditors and certification bodies decide whether controls meet the framework you are assessed against.
Confirm with your auditor which evidence they expect for each hosting model before you choose one.
What the MIT Free tier and paid epics actually cost you
The first thing to settle is which parts of GitLab you are actually licensing. GitLab's source repository is open core: code outside the ee/ directory is available under the MIT Expat license, while code under ee/ falls under the GitLab Enterprise Edition license. That split matters for a team that wants to inspect, fork or self-host the Free tier, because the MIT-licensed portion is what a Free installation runs on. Paid features are gated by subscription, not by a separate codebase you can avoid, so the licensing question and the pricing question are related but not identical. Ask your legal team to read the LICENSE file in the gitlab-org/gitlab repository directly, since the license file is the authoritative source for how the split applies to your use.
Pricing for self-managed installations has three tiers. GitLab Free costs 0 US dollars, Premium costs 29 US dollars per user per month billed annually, and Ultimate is custom priced. All three are available for self-managed instances. For planning-related work, the decision point is epics: they are available in Premium and Ultimate, but nested child epics are Ultimate only. If your Jira hierarchy depends on multi-level epics, a Premium subscription will not reproduce it. Premium also adds advanced CI/CD and priority support, while Ultimate adds application security testing, software supply chain security, vulnerability management and compliance features. Each tier is a recurring per-user or negotiated cost, so the seat count of people who only need issues and boards is a direct lever on the bill.
Before you rely on a tier for a requirement, confirm the specifics with GitLab in writing. Check the current GitLab pricing page against your planned feature list, ask whether the features you need for audit evidence or security scanning are in Premium or only in Ultimate, and request a quote that names the tier, seat count and billing term. Also confirm how Jira-imported epics and issues will sit under your chosen tier, since the importer does not bring assignees or comments across. Your budget should cover the subscription, the staff who run the instance, and the upgrade cadence described in GitLab's maintenance policy, which ships a major release yearly and requires upgrade stops along the way.
What runs up the cost on each side
Jira and GitLab costs break into different components. GitLab's license cost is per user and tier, while the larger items are one-time migration work and recurring staff time for upgrades, backups and hosting. Read each card against your own user count, hosting plan and Jira contract dates.
Per-user licensing on GitLab
GitLab Free costs 0 US dollars. Epics need Premium, which the GitLab pricing page lists at 29 US dollars per user per month billed annually, and all three tiers are available for self-managed installations. Nested child epics need the top tier, which is custom priced, so request that quote only if your planning requires nested epics. License cost recurs every billing period, so count every person who will file, plan or update work items, not only developers.
Jira's current licensing timeline
Atlassian ends new Data Center subscriptions for new customers on March 30, 2026. Existing customers can add licenses and expansions until March 30, 2028, and Data Center licenses become read-only on March 28, 2029. Any Jira spend you carry during a move is recurring until your contract ends, so a parallel-running period belongs in the comparison. Confirm your contract dates and renewal terms directly with Atlassian.
Server and storage hosting
GitLab's Linux package bundles PostgreSQL, Redis and Sidekiq, and the reference architectures range from 1,000 users to 50,000 users. The docs generally recommend a high availability strategy for 3,000 or more users, using Gitaly Cluster with Praefect, Patroni, Redis Sentinel and Consul. The reference architectures do not support running PostgreSQL or Redis inside Kubernetes, so budget VMs or managed services for those components. Hosting recurs and scales with user count and availability targets.
Upgrade and backup staffing
GitLab ships a minor release on the third Thursday of each month and patch releases twice a month. Upgrades must pass through required upgrade stops, which since GitLab 17.5 fall at x.2, x.5, x.8 and x.11. Security fixes are backported to the previous two monthly releases, while bug fixes go only to the current stable release, so the team must keep up with the release calendar. Someone must own upgrades, backups and restore tests every month, and that staff time recurs for the life of the installation.
One-time migration and rebuild
The Jira issue importer brings titles, descriptions and labels, lets you map Jira users to project members, and adds Jira fields with no GitLab equivalent to the description as plain text. It does not bring assignees or comments, and Jira text is not converted to GitLab Flavored Markdown. Budget one-time effort for a test import, rebuilding boards and epics, and preserving any comment history you need through a separate archive. Ask the implementer exactly which fields they will verify after import.
Training and vendor support
Jira administrators know workflows, schemes and boards, while GitLab administrators also run pipelines, runners and merge requests on the same instance. Training is a one-time cost per role, but it grows when several teams move at once. Premium includes priority support, which is a recurring line you can compare with other support contracts. Ask for training plans and support terms in writing before you commit to a migration date.
How a move from Jira into GitLab proceeds
The sequence moves engineering issues out of Jira into self-managed GitLab next to the code, and lists what must be rebuilt by hand so the team knows what it has lost before cutover. Each step ends with a check that the work is complete.
Inventory Jira projects and workflows
Engineering leads and a Jira administrator list every Jira project that holds engineering work, with its issue types, statuses, workflows, labels, custom fields, boards and sprints. Record which projects are active, which are archived, and which issues have open links to other projects or to code. This inventory decides what is migrated, what is archived and what is rebuilt. The step is done when each project has a named owner and a yes or no decision on migration, and the list is agreed by the team that will work in GitLab.
Map issue types and labels to GitLab
Before any import, the team decides how Jira issue types and labels become GitLab labels, and which Jira fields have no GitLab equivalent. The importer carries over titles, descriptions and labels, and it appends fields without a GitLab counterpart to the description as plain text. Jira text is not converted to GitLab Flavored Markdown, so the team should decide whether formatting loss is acceptable for long descriptions. The step is done when a written mapping table exists and has been reviewed against a sample project.
Run the Jira issue importer on a test project
A project administrator runs GitLab's built-in Jira issue importer against a copy or sample of the Jira project, not the live one. Check that titles, descriptions and labels arrive as expected, that the appended Jira fields read clearly, and that issue counts match the source. Keep the import log and the list of any issues that failed. The step is done when a test import has been reviewed line by line for one representative project and the team agrees the output is usable.
Map Jira users to GitLab project members
The importer lets you map Jira users to members of the GitLab project, so the migration team should add the engineers to the project first and confirm each mapping before the real run. Unmapped users will leave history without a clear owner. Because assignees are not brought over, this mapping matters mainly for the people who will rebuild assignments by hand. The step is done when every active Jira user who needs access has a GitLab account, a project role and a confirmed mapping.
Rebuild assignees, comments and attachments
The importer does not bring over assignees or comments today, and the GitLab Jira import documentation points to an open epic proposing both. Teams that need that history should export comments and attachments from Jira, store them in a read-only archive they control, and link to the archive from the matching GitLab issues. Assignees are reset by hand or by a scripted step for open work only. Confirm current importer behavior in the GitLab documentation before the real run, since the open epic may change. The step is done when the agreed history is archived, linked, and open issues have assignees.
Rebuild boards, epics and iterations
Boards, epics and sprint-style planning do not move as Jira structures, so the team recreates them in GitLab. Epics are available in GitLab Premium and Ultimate, including self-managed, and nested child epics require Ultimate, so confirm the tier before planning the hierarchy. Build the board columns from the agreed status mapping and recreate epics for active initiatives only. The step is done when each active Jira board has a GitLab equivalent that a product owner has reviewed and the epic structure matches the agreed plan.
Keep the GitLab instance on supported versions
Because the team will depend on this instance for code, CI and planning, the GitLab version must stay on a supported path. GitLab requires upgrades to pass through required upgrade stops, which since GitLab 17.5 fall at versions x.2, x.5, x.8 and x.11, for example 18.2, 18.5, 18.8, 18.11 and 19.2, 19.5, 19.8 and 19.11. Plan each upgrade hop against the upgrade paths documentation and take a backup before each step. The step is done when the target version is recorded, every required stop is on the upgrade calendar, and a restore has been tested from the latest backup.
Cut over and retire Jira write access
Set a cutover date, run the final import for the projects in scope, complete the rebuilt assignments and board setup, then announce that new work goes into GitLab only. Make the Jira projects read-only for the migrated teams and keep an archived export for the period your records policy requires. Confirm the cutover with a short checklist: issue counts reconciled, users able to sign in, boards and epics visible, and pipelines linked to the migrated issues. The step is done when the engineering lead signs off that Jira is read-only for migrated work and the archive location is documented.
Questions buyers ask before choosing GitLab over Jira
Does GitLab Free cover issue tracking for our software team?
Yes for basic issue tracking, but not for every planning feature. GitLab Free costs 0 dollars and is available for self-managed installations, and it includes issues and boards alongside merge requests and pipelines. Epics, which group related issues into larger planning items, are available in Premium and Ultimate, including on self-managed instances. Nested child epics are limited to Ultimate. Before you decide, list the planning structures your teams use in Jira today, then check each one against the current GitLab pricing page and the epics documentation so you know which tier you need.
What does the GitLab Jira importer leave behind?
The importer brings over each issue's title, description and labels, and it lets you map Jira users to project members. It does not bring over assignees or comments. Jira fields with no GitLab equivalent are appended to the description as plain text, and Jira markup is not converted to GitLab Flavored Markdown, so formatting may need cleanup. To close the gap, export comments and assignee history from Jira before the import and store them as attachments or in a linked archive, or ask a GitLab-experienced engineer to script a supplement through the API. GitLab's documentation points to an open epic that proposes adding assignees and comments, so confirm its status before you plan around it.
How much effort does running self-managed GitLab take?
Effort depends mainly on instance size, availability requirements and how you install it. GitLab documents several installation methods, and the Linux package is described as the most mature, bundling PostgreSQL, Redis and Sidekiq. GitLab's reference architectures range from 1,000 users to 50,000 users, and the documentation generally recommends a high availability strategy at 3,000 or more users, which adds Gitaly Cluster, Patroni, Redis Sentinel and Consul. Running stateful components such as PostgreSQL and Redis inside Kubernetes is not supported, so plan for VMs or managed services for those parts. Recurring work includes monthly minor releases, twice-monthly patch releases, and required upgrade stops at versions such as 18.2, 18.5 and 18.8. Ask your team to map these to on-call duties before committing.
How long does a migration from Jira to GitLab take?
No fixed duration applies, because the timeline depends on what you move and how clean the source data is. The main drivers are the number of projects and issues, how much history and comment content must be preserved, how many custom fields and workflows must be rebuilt as labels or epics, and how many users need mapping. Teams with a small backlog and few custom fields move faster than teams that need years of comments and assignee records. Start with a pilot project to measure the real volume, then agree the cutover date with the teams that still use Jira. Confirm the expected duration in writing with whichever party does the work.
Can our own engineers run the migration without outside help?
Often yes, if one or two engineers already administer GitLab and have a clear list of what to move. The importer is built into GitLab, the source data is available through Jira's export, and the steps are documented. The harder work is usually the decisions: which Jira fields become labels, which workflows become board columns, how users map to members, and what gets archived rather than imported. Those decisions need input from product owners and compliance staff, not only from administrators. Teams that lack someone with GitLab operations experience should budget time for training before the migration starts.
When is an implementation partner worth engaging for GitLab?
A partner is worth considering when the migration or the self-managed platform carries risk that your team cannot absorb alone. Typical triggers include regulated data that must stay in your own infrastructure, air-gapped or offline networks, multi-thousand user scale that needs a high availability design, or a compliance review that requires documented controls. DeployOpen plans, implements, integrates, hardens, backs up and documents self-hosted platforms inside your own cloud accounts, data centers or air-gapped networks, and most engagements are fixed-scope with deliverables agreed in writing before work starts. DeployOpen does not issue audit reports or certifications. Ask for a written scope that names the import gaps, backup approach and upgrade plan before you sign.
Where DeployOpen fits when GitLab replaces Jira
DeployOpen can plan, install, harden, back up and document a self-managed GitLab instance inside your own cloud account, data center or air-gapped network, and it scopes the Jira import and rebuild work in writing before any work starts. The first decision is the installation method. GitLab documents the Linux package, the Helm chart, the GitLab Operator, Docker and source installs, and the reference architecture you choose depends on user count and whether stateful services such as PostgreSQL and Redis will run inside Kubernetes, which the reference architecture documentation does not support. Confirm the user count, the expected API load and the high availability target with your platform team before anyone picks a method, because those choices drive the server layout and the recurring operations work.
The import scope is where most of the cost sits. The GitLab Jira issue importer carries over titles, descriptions and labels, maps Jira users to project members, and appends Jira fields without a GitLab equivalent as plain text. It does not carry comments or assignees today, so a written scope should state how those are handled, whether through an export archive, a read-only Jira instance kept for reference, or a documented manual step. Ask for a list of the Jira projects, custom fields, workflows and epics that will map to GitLab epics, and confirm which of those epics need nested child epics, a capability that GitLab documents as Ultimate only. The result should be a written decision on each mapping, not a surprise on cutover day.
Hardening and recovery are the parts that keep a self-managed forge trustworthy after handover. DeployOpen can set up access controls, backup and restore procedures, upgrade planning against GitLab's required upgrade stops, and runbooks that your operators can follow without us. Before signing off, check that backups cover the repositories, the database and the object storage your teams rely on, and that a restore has been rehearsed. DeployOpen prepares controls and evidence for compliance assessments but does not issue audit reports or certifications, so any independent assessment remains with your auditor.
How DeployOpen helps evaluate, implement and migrate
DeployOpen plans, implements and supports self-hosted open-source platforms inside your own infrastructure, including GitLab next to your existing code and CI. For Jira vs GitLab, we start by testing which Jira issue types, boards and epics your teams actually depend on before deciding what moves.
How we scope
- We inventory which Jira projects, boards and epics need to move, and which can stay in Jira or be closed.
- We check which GitLab tier covers your epic needs, since epics need Premium or Ultimate on Self-Managed.
- Engagements are fixed-scope, so deliverables, timelines and the importer gaps we will document are agreed in writing first.
How we build
- We install GitLab in your environment using the method your operations team already supports, such as the Linux package or Helm chart.
- We run a test import of a representative Jira project and record what arrives: titles, descriptions and labels.
- We rebuild assignee and comment history, labels and board views by hand or with scripts where the importer does not carry them.
How we hand over
- You receive documentation of the import mapping, the fields lost in transit and the manual steps performed.
- We document backup and restore procedures for GitLab so the planning data is covered by the same routine as the code.
- We walk your team through issue workflows, epic structure and merge request links so developers can work from day one.
How we support
- Ongoing support, upgrades and continuous testing are available as a retainer, including planning for GitLab's required upgrade stops.
- We help you track GitLab's monthly and patch release cadence against your change windows and test environment.
- Where you need offline operation, we document the air-gapped install and update path with your security team.
