Project Management migration
Field-level mapping, validation, and rollback between Taiga and Jira. We move data and schema; workflows are rebuilt natively in Jira.
Taiga
Source
Jira
Destination
Compatibility
8 of 10
objects map 1:1 between Taiga and Jira.
Complexity
BStandard
Timeline
2-3 weeks
Overview
Taiga and Jira share a similar Scrum and Kanban vocabulary, but their underlying data models differ enough to require careful mapping. Taiga uses a flat hierarchy with User Stories, Tasks, and standalone Issues under a Project; Jira nests Stories under Epics, splits Tasks into Subtasks or linked Issues, and organizes work into Sprints within a Project. No native Taiga-to-Jira import path exists — Taiga exports project-level JSON that Jira's CSV and JSON importers do not accept, and the official Atlassian documentation lists only Trello, Asana, GitHub, and CSV as valid Jira import sources. We work around this by parsing Taiga's export format directly, building a field-level transformer that maps status, priority, severity, points, and custom attributes into Jira's issue schema, then loading through Jira's REST API or bulk import endpoint. We handle Taiga's hard 30-record page limit on the extraction side by looping until the API returns an empty page. Automations, custom workflows, and Taiga notifications do not migrate as code; we deliver a written inventory of every rule requiring 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 Taiga 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.
Taiga
Project
Jira
Project
1:1Taiga Projects map directly to Jira Projects. We preserve the project name, description, and member list. Each Taiga project requires a Jira project key (e.g., PROJ) that we define during scoping; the key becomes the prefix for all Jira issue IDs migrated from that project. Taiga project settings including wiki, module configuration (Kanban vs Scrum), and custom attributes export with the project and require field-level mapping decisions before Jira import.
Taiga
Milestone / Sprint
Jira
Sprint
1:1Taiga Milestones map to Jira Sprints. We preserve the sprint name, start date, end date, and sprint order within the project. Closed Sprints migrate with their Completed status intact. Open Sprints that have not yet closed are created as future sprints in Jira with the original start/end dates. If a Taiga project uses multiple active sprints simultaneously (Kanban with swimlanes treated as sprint-equivalents), we map these to Jira sprints within a shared board.
Taiga
Epic
Jira
Epic
1:1Taiga Epics map to Jira Epics (available in Jira Software from the free plan onward). Epic status, color tag, and description preserve. In Taiga, Epics are top-level backlog items that group User Stories; in Jira, Epics function identically with an Epic Link custom field on Stories. We set the Epic Name field on Jira Epic issues and map the Epic Link field on child Stories during migration. Where a Taiga Epic has no child Stories, we create a standalone Jira Epic and flag it for review.
Taiga
User Story
Jira
Story
1:1Taiga User Stories map to Jira Story issues. The story subject becomes the Jira Summary (required). Story description, status, points (story points to a numeric custom field), assignee, milestone reference, tags, and custom attributes migrate. Taiga's us epic link field maps to Jira's Epic Link field. We resolve the target Epic ID during migration so the Epic Link is populated at import time rather than requiring post-migration manual linking.
Taiga
Task
Jira
Subtask or Story
1:manyTaiga Tasks nested under a User Story map to Jira Subtasks. Subtasks inherit the parent Story's project, Epic Link (if set), and sprint assignment. Taiga Tasks that are not children of a User Story (top-level tasks) map to Jira Story issues — we treat them as Stories in Jira because Jira does not have standalone top-level Tasks without a parent. During scoping, the customer chooses whether all Tasks become Subtasks or whether free-standing Tasks become Stories.
Taiga
Issue
Jira
Bug, Task, or Story
lossyTaiga Issues are standalone work items outside the sprint backlog, with type, severity, priority, and status. We map Taiga issue type to Jira Issue Type (Bug, Task, Story) based on the customer's naming convention. Taiga severity and priority map to Jira Priority (Highest, High, Medium, Low) and to a custom Jira severity field if the customer's workflow requires both. Closed issues from Taiga migrate with their final status and resolution preserved in Jira's Resolution field.
Taiga
Custom Attributes
Jira
Custom Fields
1:1Taiga allows custom attributes on User Stories, Tasks, and Issues per project. We extract the attribute definition (name, type, and options) and create matching Jira custom fields before migration. Text attributes map to Jira Text Field (single line), long text to Text Area (multi-line), number to Number field, date to Date field, and dropdown or multi-select options to Jira Select (single) or Multi-select fields. Enum values are preserved as picklist options in Jira.
Taiga
Wiki Pages
Jira
Confluence Pages or Jira Description
1:1Taiga project wikis contain Markdown-formatted pages organized in a tree. We export the page tree and convert Markdown to Confluence Storage Format (XHTML) if the customer has Confluence. If Confluence is not in scope, page content migrates as Jira issue description with Markdown preserved. Links between wiki pages require manual re-linking post-migration because Taiga's internal wiki links do not have Jira equivalents. The page tree structure is documented as a navigation map for the admin to reproduce.
Taiga
Tags / Labels
Jira
Labels
1:1Taiga's free-form tags on User Stories, Tasks, and Issues extract as label strings and apply as Jira Labels. Taiga supports multiple tags per artifact; Jira Labels is a multi-value text field that accepts the equivalent. Where Taiga uses structured tags as a pseudo-category system (e.g., frontend, backend, ux), we recommend the customer review the label vocabulary post-migration to consolidate duplicates and enforce a controlled vocabulary in Jira.
Taiga
Attachments
Jira
Attachments
1:1Taiga stores attachments as file reference URLs pointing to the Taiga media storage. We retrieve attachments from Taiga's media URL if the instance is cloud-hosted and accessible, then upload them to Jira via the Jira REST API attachment endpoint (10MB per-file limit on Jira Cloud). Taiga's attachment metadata (filename, uploader, upload date, comment) becomes the Jira attachment comment. Self-hosted Taiga instances with local file storage require the customer to provide media file access during migration.
| Taiga | Jira | Compatibility | |
|---|---|---|---|
| Project | Project1:1 | Fully supported | |
| Milestone / Sprint | Sprint1:1 | Fully supported | |
| Epic | Epic1:1 | Fully supported | |
| User Story | Story1:1 | Fully supported | |
| Task | Subtask or Story1:many | Fully supported | |
| Issue | Bug, Task, or Storylossy | Fully supported | |
| Custom Attributes | Custom Fields1:1 | Mapping required | |
| Wiki Pages | Confluence Pages or Jira Description1:1 | Mapping required | |
| Tags / Labels | Labels1:1 | Mapping required | |
| Attachments | Attachments1:1 | Mapping required |
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.
Taiga gotchas
REST API hard-codes 30 records per page
Import only accepts Trello, Jira, Asana, and GitHub
Docker self-hosted v5 to v6 migration can lose data silently
Taiga export is instance-specific JSON, not portable CSV
Custom CSS / taiga-ui v3 to v4 style overrides break after migration
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 data audit
We audit every Taiga project in scope: record counts per object type (Epics, User Stories, Tasks, Issues, Milestones), custom attribute definitions, attachment volume and total storage size, wiki page count, and project settings (Scrum vs Kanban per module). We identify the target Jira Cloud or Data Center instance and verify project key availability. We document the full Taiga role-permission matrix for mapping to Jira groups and project roles. The discovery output is a written migration scope with record counts, a Jira schema design, and a mapping table for every custom field.
Extraction with pagination loop
We extract from Taiga via paginated REST API calls, looping through 30-record pages for each object type until the API returns an empty page. We accumulate results in a staging store and validate total record counts against the Taiga JSON export if available. For self-hosted Taiga Docker instances, we require a JSON export as a fallback backup in case the API extraction encounters authentication or network issues. We extract wiki pages and attachment URLs in parallel with artifact extraction.
Schema creation in Jira
We create the destination Jira project(s), define project keys, and provision custom fields to match Taiga's custom attribute schema. We configure the Jira workflow, status values, and issue type scheme to approximate Taiga's workflow before any data loads. If the customer uses multiple Taiga projects, we create one Jira project per Taiga project or consolidate per the scoping decision. The Jira schema is deployed to a staging or sandbox environment first for validation before production load.
Data transformation and sandbox import
We transform Taiga's JSON export into Jira-compatible CSV (for bulk import) or JSON (for REST API load) format. This includes mapping Taiga status to Jira status, Taiga severity to Jira Priority or a custom field, Taiga story points to a Jira numeric custom field, and Taiga tags to Jira Labels. Custom attributes transform according to the type mapping defined during schema creation. We run a sandbox import into the customer's Jira staging environment, reconcile record counts, spot-check 25-50 records per object type against the Taiga source, and document any mapping corrections before production.
Attachment migration
We download files from Taiga's media storage URL for each attachment, verify the file is accessible, and upload to Jira via the Jira REST API attachment endpoint. Files over 10MB on Jira Cloud are flagged for the customer to decide whether to split or exclude. Attachment comments (uploader, timestamp, description) are preserved as Jira attachment comments. Self-hosted Taiga instances with local storage require the customer to provide direct file system access or a media URL endpoint.
Production migration and cutover
We freeze write access to the source Taiga project(s) during the production cutover window. We run a delta extraction for any records modified during testing, apply the final transformation, and load into the production Jira instance. We validate record counts per object type post-load against the extraction counts. We deliver the automation and workflow inventory document to the customer's admin team. We support a 72-hour hypercare window for reconciliation issues. Wiki page link updates in Confluence (if applicable) require a separate pass after Confluence is provisioned.
Platform deep dives
Taiga
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 Taiga 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
Taiga: Not publicly documented in official docs.
Data volume sensitivity
Taiga 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
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