Plex and Jira integration

What moves between them

Quality issues and production orders flow from Plex into Jira as new issues or updates to existing ones on a polling schedule aligned with shop floor pace, typically every 5 to 15 minutes. Work center codes, part numbers, and due dates from Plex are mapped to Jira custom fields and project structure. Issue status changes in Jira are read back into Plex work order status if configured for closed-loop feedback, so production planning reflects team acknowledgment and progress.

How ml-connector handles it

ml-connector stores both Plex OAuth2 credentials and Jira authentication details encrypted, and polls the Plex REST API at a cadence you set, filtering quality issues and production orders by modified_date or created_date. For each new Plex record, ml-connector checks Jira for an existing issue matching the external reference (Plex issue ID or order number) to avoid duplicates, then creates a new Jira issue or updates an existing one with the latest part number, work center, due date, and status. It manages Jira webhook expiry by calling the refresh endpoint before the 30-day window closes. Plex role-based permissions are enforced per API call, so the integration user must have the correct Plex role assigned. All records carry a full audit trail and can be replayed if a downstream Jira call fails.

A real-world example

A mid-sized discrete manufacturer runs Plex for production, quality, and procurement across two plants and uses Jira for team task tracking and issue resolution. Before the integration, quality issues logged in Plex remained siloed in the ERP and never reached the wider team, so engineers and planners worked from separate systems. Support tickets in Jira were created by hand based on emails about production problems, leading to duplicate effort and missed context. With Plex and Jira connected, every quality hold or production issue automatically becomes a Jira ticket assigned to the right team with full part number and due-date context, and status updates in Jira flow back to Plex work-order tracking so the shop floor knows the team is engaged.

What you can do

• •Sync Plex quality issues and production orders into Jira as new issues with part numbers, work centers, and due dates mapped to custom fields.
• •Poll Plex REST API on a schedule you control, filtering by creation or modification date to track only recent changes.
• •Detect and prevent duplicate Jira issues by matching Plex external reference IDs.
• •Manage Jira webhook registration and automatic refresh before the 30-day expiry window closes.
• •Authenticate Plex with OAuth2 and Jira with either OAuth2 or Basic auth, with encrypted credential storage and a full audit trail on every record.

Questions

Which direction does data move between Plex and Jira?

The primary flow is from Plex into Jira. Quality issues and production orders from Plex are polled and synchronized into Jira as new issues or updates. Status changes in Jira can optionally be read back into Plex work-order status for closed-loop visibility so production planning reflects team progress.

Does the integration handle Plex's lack of native webhooks?

Yes. ml-connector polls Plex REST API on a configurable interval (5 to 15 minutes recommended) filtering by modified_date or created_date, so new and updated records are retrieved without relying on push notifications. This keeps Jira in sync with Plex shop-floor activity on a schedule aligned with production pace.

How are Plex work centers and part numbers mapped to Jira?

ml-connector maps Plex work center codes and part numbers to Jira custom fields as you configure them, so each Jira issue carries the manufacturing context (which plant, which part, which work station) needed for the team to act. The mapping is per-customer and stored encrypted with the rest of the integration configuration.