Project Management migration
Field-level mapping, validation, and rollback between Cerebro and Jira. We move data and schema; workflows are rebuilt natively in Jira.
Cerebro
Source
Jira
Destination
Compatibility
7 of 11
objects map 1:1 between Cerebro and Jira.
Complexity
BStandard
Timeline
3-5 weeks
Overview
Moving from Cerebro to Jira is a structural migration that collapses unlimited task nesting depth into Jira's three-level hierarchy (Epic, Story/Task, Subtask) and trades Cerebro's opaque no-API export model for Jira's mature REST API. The highest-risk part of this migration is source data access: Cerebro publishes no public REST or GraphQL endpoint, and all export work must proceed through its built-in file export and screen-based extraction. We sequence the migration by extracting Cerebro Projects first, resolving the nesting depth into parent-child Jira issue relationships, then re-uploading media assets that Cerebro stored on its own distributed servers. Permission groups require explicit mapping to Jira's role-based model, and any Cerebro Gantt dependencies are reconstructed using Jira's native issue linking. Workflows, automations, and team calendars do not migrate as code; we deliver written inventories for the customer's admin to rebuild in Jira.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a Cerebro object lands in Jira, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Cerebro
Project
Jira
Jira Project
1:1Cerebro Projects map directly to Jira Projects. Project name, description, status, start and end dates, and tags migrate as-is. Each Cerebro Project becomes a Jira Project with a corresponding project key (e.g., ANIM, VFX) that prefixes all issues migrated from that project. Jira project creation requires the customer to pre-configure project templates (Scrum or Kanban) in the destination before migration begins.
Cerebro
Task (top-level)
Jira
Epic or Story
1:1Cerebro top-level tasks map to Jira Epic issues. The Epic's summary, description, assignee, and due date transfer directly. If the customer prefers a flat Story-based model, top-level Cerebro tasks can map to Stories at the customer's direction during scoping. Epic-Story linking is preserved by mapping the Cerebro task's immediate children as Stories under the Epic.
Cerebro
Task (nested)
Jira
Story or Task
lossyCerebro tasks nested at any depth map to Jira Stories or Tasks with parent links reconstructed. Because Jira enforces a maximum of two levels below Epic (Epic > Story > Subtask), Cerebro's unlimited nesting depth requires flattening. We preserve the full Cerebro hierarchy path in the Jira issue description as a breadcrumb trail (e.g., 'Cerebro path: Project / Act 1 / Scene 2 / Shot 10') and link parent-child relationships using Jira issue links or the parent field on Subtask.
Cerebro
Subtask
Jira
Subtask
1:1Cerebro Subtask records map to Jira Subtask issues linked to their parent Story or Task. Assignee, status, due date, and description transfer directly. Subtasks retain the parent breadcrumb path from the Cerebro hierarchy.
Cerebro
Tag
Jira
Label
1:1Cerebro tags migrate to Jira Labels. Tag naming conventions vary by team; we extract all unique tag values across all Cerebro objects, normalize them (lowercase, remove spaces, strip special characters per Jira label format), and apply them to the corresponding Jira issues. Labels that exceed Jira's character limit or conflict with existing Jira label names are flagged for manual review.
Cerebro
Task Dependency
Jira
Issue Link
lossyCerebro Gantt chart dependencies (Finish-to-Start, Start-to-Start, Finish-to-Finish, Start-to-Finish) are exported as explicit dependency edges. We map them to Jira Issue Links using the 'blocks' and 'is blocked by' link types. Jira does not natively support Finish-to-Start vs Start-to-Start semantic differences, so all dependencies are set as 'blocks' with the original dependency type noted in the link comment for the customer's admin to configure Jira Automation rules post-migration if granular dependency semantics are required.
Cerebro
Attachment
Jira
Attachment
lossyCerebro stores media files on its own distributed servers. We extract all attachment URLs from the Cerebro export, download each file individually, and re-upload to Jira as Attachments on the corresponding issue. Re-upload failures (due to file size limits, unsupported file types, or network errors) are logged in a per-file reconciliation report. Audiovisual commentaries are treated as linked media assets with a URL reference retained in the Jira issue description.
Cerebro
Comment
Jira
Comment
1:1Cerebro Comments migrate to Jira Comments on the corresponding issue. Author attribution is preserved by resolving the comment author's Cerebro user ID to a Jira user account by email match. Comment body migrates as plain text; any Cerebro built-in translator UI artifacts are stripped during comment normalization. Inline media references in comments are converted to download links pointing to the re-uploaded attachment in Jira.
Cerebro
Team Calendar
Jira
Issue Schedule (Dates)
1:1Cerebro team and individual calendars aggregate task assignments and deadlines. We extract the scheduled dates from Cerebro calendar entries and apply them to Jira issues as Start Date and Due Date. All-day vs partial-day semantics differ between platforms; Cerebro all-day entries map to Jira issues with no Start Date and only a Due Date set.
Cerebro
Permission Group
Jira
Project Role or Group
lossyCerebro uses a permission-group access model where users belong to named groups with specific access rights per project. Jira uses role-based access control with project roles (Administrators, Members, Viewers) and global permissions. We extract all Cerebro permission group memberships, map them to the closest matching Jira project role, and flag any Cerebro group with no direct Jira equivalent (e.g., a custom 'Reviewer' role with granular per-object rights) as requiring manual post-migration permission review.
Cerebro
User
Jira
User
1:1Cerebro user accounts are matched to Jira user accounts by email address. Any Cerebro user without a matching Jira account is held in a reconciliation queue for the customer's Jira admin to provision before record import begins. User display names, avatars, and contact information transfer where available.
| Cerebro | Jira | Compatibility | |
|---|---|---|---|
| Project | Jira Project1:1 | Fully supported | |
| Task (top-level) | Epic or Story1:1 | Fully supported | |
| Task (nested) | Story or Tasklossy | Fully supported | |
| Subtask | Subtask1:1 | Fully supported | |
| Tag | Label1:1 | Fully supported | |
| Task Dependency | Issue Linklossy | Fully supported | |
| Attachment | Attachmentlossy | Fully supported | |
| Comment | Comment1:1 | Fully supported | |
| Team Calendar | Issue Schedule (Dates)1:1 | Fully supported | |
| Permission Group | Project Role or Grouplossy | Fully supported | |
| User | User1:1 | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
Cerebro gotchas
No documented public API for automated export
Media attachments stored on Cerebro's servers require separate transfer
Permission groups do not map cleanly to role-based systems
Localization strings in exported comments may include UI artifacts
Jira gotchas
Unsupported workflow validators silently skipped during migration
Custom fields converted to flat text labels when migrating to non-Jira platforms
Historical status-change timestamps lost when exporting without a Marketplace plugin
Attachment import failures from oversized files and JQL reference corruption
Points-based API rate limits enforced on Jira Cloud apps from March 2026
Pair-specific challenges
Migration approach
Discovery and export scoping
We audit the Cerebro account to inventory all Projects, Tasks, Subtasks, Comments, Tags, Attachments, Permission Groups, and Users. Because Cerebro has no public API, we work from the customer's account export and screen-based extraction. We determine the maximum nesting depth per project, estimate the Jira issue expansion factor, catalog all attachment URLs for re-upload, and extract permission group membership lists. The discovery output is a written migration scope document with Jira project key assignments, nesting collapse strategy, and permission mapping plan.
Jira project and issue type configuration
Before any data moves, the customer configures Jira Projects with the appropriate issue type scheme that supports Epic > Story > Subtask hierarchies. We assist by documenting the required configuration: one Jira Project per Cerebro Project, with an Issue Type Screen Scheme that shows the Epic field on Stories, and a Subtask Issue Type screen that shows the Parent field. If the customer uses Jira Software Premium or Enterprise, we also configure the Automation for Jira rules needed to handle dependency reconstruction from the blocks-link inventory.
Sandbox migration and nesting collapse validation
We run a full migration into a Jira Sandbox (or a dedicated test project in production if no Sandbox is available) to validate the nesting collapse logic. We count Cerebro tasks in, Jira issues out, and verify the breadcrumb hierarchy comment on each issue. The customer spot-checks 25-50 random issues against the Cerebro source and validates that attachment re-uploads succeeded. Any mapping corrections (e.g., certain Cerebro task types should become Epics instead of Stories) happen at this stage before production migration begins.
User provisioning and permission mapping
We extract every distinct Cerebro user referenced across all objects and match by email against the Jira destination instance's user directory. Users without a matching Jira account are placed in a reconciliation queue for the customer's Jira admin to provision. Simultaneously, we apply the permission group mapping: each Cerebro permission group is mapped to a Jira project role, and group membership is assigned to the corresponding role. Groups with no Jira equivalent are flagged for manual post-migration review.
Production migration in dependency order
We run production migration in this order: Jira Projects (created in advance), Users (provisioned and validated), Cerebro Projects and Epics, Cerebro Tasks (top-level and nested, with parent-child links reconstructed), Cerebro Subtasks, Comments (with author attribution resolved), Tags (applied as Labels), Gantt dependencies (applied as blocks issue links with dependency type in comment), and Attachments (chunked download from Cerebro servers, upload to Jira with per-file error logging). Each phase emits a row-count reconciliation report before the next phase begins.
Cutover, validation, and inventory handoff
We freeze Cerebro writes during cutover, run a final delta migration of any records modified during the migration window, then enable Jira as the system of record. We deliver a written inventory of Cerebro Gantt dependencies (with original dependency type preserved) and Cerebro permission groups (with Jira role assignments and any unmapped groups flagged). We do not migrate Cerebro template workflows as Jira workflows; that rebuild work is documented separately for the customer's Jira admin. We support a one-week hypercare window for reconciliation issues.
Platform deep dives
Cerebro
Source
Strengths
Weaknesses
Jira
Destination
Strengths
Weaknesses
Complexity grading
Standard Project Management migration. 3 of 8 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Cerebro and Jira.
Object compatibility
3 of 8 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
Cerebro: Not publicly documented.
Data volume sensitivity
Cerebro doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
Pick a category, then your source and destination platforms.
Category
FAQ
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