Pipelines
Run history and triggers of the Train, Register, Deploy and CT pipelines, and run detail (task DAG, logs)
Required permission: View
This screen shows the history of runs that tie training → registration → deployment, and retraining when drift is detected (CT, Continuous Training), together as pipelines. Pipelines run as Kubernetes Jobs in the tenant namespace. Every member can view; triggering, rerunning and stopping need operate (OPERATOR, ADMIN).
| # | Area | Description |
|---|---|---|
| ① | Pipeline tabs | Train (Train) · Register (Register) · Deploy (Deploy) · CT (M3+) (CT (M3+)). Each tab shows the run history of that kind. |
| ② | New trigger (새 트리거) | Runs the current tab's pipeline once (operate). |
| ③ | Run history | Run, status, type, start, end. Click a row to open the run detail. |
Run detail
The run detail has the progress ("3/5 tasks completed (3/5 태스크 완료)"), a Tasks (DAG) (태스크 (DAG)) diagram (showing the order in which tasks run), and the log of a task when you click it. Rerun (재실행) · Stop (중단) at the top need the operate permission.
Main tasks
- Choose the tab of the pipeline to run.
- Press New trigger (새 트리거). A "Pipeline triggered (파이프라인 트리거됨)" notice appears and a new row is added to the history.
- Click the new row to see task progress and logs.
Statuses and badges
The status shows the Kubernetes Job status as is (in English).
| Value | Color | Meaning |
|---|---|---|
| Pending | Yellow | Waiting for the pod to start |
| Running | Blue | Running |
| Succeeded | Green | Ended normally |
| Failed | Red | Failed — see the task log for the cause |
| unknown | Grey | Status cannot be determined |