Controlled execution for supported Jira operations.
JiraFlow turns repeatable Jira administration and file-driven work into controlled workflows that run inside the customer environment, with structured inputs, supported Jira operations and retained run evidence.
It is designed for defined Jira workflows where teams need more control than manual administration, one-off scripts or repetitive spreadsheet-driven changes.
Structured input in. Supported Jira operation out.
JiraFlow focuses on controlled, repeatable execution against Jira within the documented supported scope. It does not try to replace Jira’s own native automation for event-driven rules.
- ✓ JQL search and supported issue reads
- ✓ Issue create, bulk create and supported updates
- ✓ Workflow transitions and worklog creation
- ✓ Archive and unarchive patterns where available in the target Jira deployment and agreed workflow scope
- ✓ Local execution with retained logs, outputs and failures
Jira administration becomes risky when repeatable work stays manual.
Many Jira teams eventually face recurring work that sits awkwardly between native automation and manual administration: bulk issue creation, repeated update runs, transitions, worklogs and structured file-driven operations.
Manual issue creation
Teams repeatedly create Jira issues from spreadsheets, forms or operational extracts.
Bulk updates
Large issue sets need consistent changes without relying on repetitive UI actions or fragile scripts.
Workflow transitions
Selected issues may need to move through agreed transitions in a controlled, repeatable way.
Configuration complexity
Custom fields and customer-specific Jira configuration make generic scripts harder to maintain safely.
Prepare, validate, execute and evidence
JiraFlow follows the same controlled execution pattern used across DDF: define the input and operation, validate the workflow, execute locally and retain evidence of what happened.
1. Prepare
Define the agreed source data, selection criteria and Jira operation using structured configuration.
2. Validate
Use supported previews and preflight checks where the workflow supports them before live execution.
3. Execute
JiraFlow performs the supported Jira operation from within the customer environment.
4. Evidence
Retain inputs, outputs and failures for review, with reconciliation where the workflow requires it.
Supported Jira operations
JiraFlow is intended for defined Jira workflows within the documented supported scope. The exact field and operation set should be agreed against the customer’s Jira configuration.
Search and read
Use JQL search and supported single or bulk issue reads to retrieve selected Jira data.
Create and bulk create
Create Jira issues from agreed structured input using supported standard and configured fields.
Update issues
Apply supported changes to selected Jira issues within the defined workflow scope.
Workflow transitions
Apply agreed Jira transitions to selected issues where the target workflow and permissions support them.
Worklogs
Create worklogs from structured input where the customer workflow requires repeatable operational time entry.
Archive lifecycle operations
Support agreed archive, export and unarchive patterns where available in the target Jira deployment and within the documented JiraFlow scope.
Built for configured Jira estates
Enterprise Jira environments rarely look identical. JiraFlow uses its GetCreateIssueTypes and GetCreateIssueTypeMetadata services to retrieve available Jira create metadata for the selected project and issue type, then applies supported field handling through structured configuration rather than embedding customer-specific logic in one-off scripts.
Metadata-driven field discovery
JiraFlow uses its GetCreateIssueTypes and GetCreateIssueTypeMetadata services to retrieve the Jira create metadata available for the selected project and issue type, subject to the target Jira deployment, API access and permissions.
Implemented field patterns
JiraFlow includes implemented handling for a defined set of standard and custom Jira field schemas, including select, user, date, datetime, number and text patterns. Applicable field types are confirmed against the agreed workflow and customer configuration.
Unsupported schemas are explicit
Specialist, app-provided, read-only or unvalidated schemas are assessed separately and remain outside the supported scope until their payload behaviour has been implemented and validated for an agreed workflow.
Customer Jira configuration still matters
Permissions, issue type metadata, field schemes, transitions and target configuration remain part of the deployment assessment.
JiraFlow includes standard-field support and implemented handling for selected custom-field patterns. The current field catalogue records implemented, read-only and not-yet-implemented schemas so support can be confirmed against the actual Jira configuration rather than assumed universally.
JiraFlow complements native Jira automation
Jira’s native automation is well suited to event-driven rules inside Jira. JiraFlow is aimed at a different class of problem: structured external inputs, repeatable bulk operations and controlled execution where files, query results or wider operational processes drive the work.
Recurring bulk issue creation, controlled update runs, workflow transitions, worklog operations, archive lifecycle work and other structured Jira processes that need a repeatable execution pattern.
Add DDF Plus when the workflow needs more local data intelligence
JiraFlow Core provides controlled execution for supported Jira operations. DDF Plus is the customer-wide capability layer for workflows that also need local preparation, calculation, comparison, delta detection or enhanced reconciliation.
QueryLocal
Prepare, filter and join local workflow data before Jira execution.
CalcLocal
Apply configured calculations where Jira workflow values need to be derived locally.
SmartSync
Identify new, changed, missing or unchanged records where comparison rules are configured for the workflow.
Reconciliation
Add defined comparison and readback controls where the workflow requires verification.
Local execution and customer-controlled authentication
JiraFlow runs inside the customer environment. Where SentinelFlow is used, approved authentication material can be retrieved at runtime from a supported customer-managed credential source, and JiraFlow authenticates directly with the approved Jira endpoint.
Customer environment
JiraFlow execution runs locally rather than through a DDF-hosted execution service.
SentinelFlow
Supports agreed runtime credential-retrieval patterns for customer-managed stores such as CyberArk, 1Password and Windows Credential Manager.
Run evidence
Inputs, outputs and failures can be retained for review. Credential values are not intended to form part of workflow configuration or run outputs.
Extend JiraFlow into a controlled multi-system workflow
Multiple DDF connectors can run independently. Add FlowBridge only when one approved workflow needs to coordinate supported work across Jira and one or more other licensed systems.
A single controlled FlowBridge input could contain supported Jira work alongside supported Planview or ServiceNow work, while JiraFlow remains responsible for the Jira-specific operations.
Start with one repeatable Jira workflow
JiraFlow is best introduced around a defined operational problem rather than as a promise to automate an entire Jira estate.
Bulk creation
Turn structured source data into repeatable Jira issue creation.
Recurring update runs
Apply agreed field updates consistently across selected issue sets.
Transitions and worklogs
Automate supported workflow transitions or worklog creation from agreed inputs.
Archive lifecycle work
Apply supported archive, export or unarchive patterns where available in the target Jira deployment and agreed workflow scope.
Which Jira workflow would you most like to stop doing manually?
Show us the current input, Jira operation and expected outcome. We can assess whether it fits the documented JiraFlow scope and whether Core, Plus or FlowBridge is appropriate.