The Dashboard
The Dashboard is the overview page of the Zebroo Sync app. It shows one card per pipeline, so you can see at a glance which pipelines are busy, which have failures waiting for attention, and which have not run at all.
Open it from the app menu: Zebroo Sync → Pipelines → Dashboard.
What a Card Shows
Each card carries the pipeline name, a row of counter tiles, the date of the last run, and a button to open that pipeline's instances.
The counters group the pipeline's instances by state:
| Tile | Instance state | Meaning |
|---|---|---|
| Done | success | Runs that completed without error. |
| Running | running | Runs currently being processed. |
| Pending | pending | Runs created but not yet picked up. |
| Failed | failed | Runs that aborted on an error. |
A pipeline that is paused carries a Paused badge next to its name.
Only Non-Zero Counters Are Shown
A tile is only drawn when its counter is greater than zero. A pipeline with nothing but successful runs shows a single Done tile rather than three empty ones, which makes the cards that do have failures or pending work stand out on a crowded dashboard.
The remaining tiles spread evenly across the width of the card, so a card with two counters shows two half-width tiles.
Hiding a counter never hides the pipeline. Every pipeline keeps its card regardless of its counters — including a pipeline whose counters are all zero, which shows one empty tile and the note No executions yet underneath.
The counters reflect the instances still present in the database, not everything the pipeline has ever run. zSYNC garbage-collects old instances according to each pipeline's Keep Instances For Days setting (see Runtime Configuration), so a long-lived pipeline will usually show far fewer runs than it has actually performed. Only success and failed instances are collected; running and pending are left alone.
Opening the Instances
The Instances button at the bottom right of each card opens the instance list filtered to that pipeline. From there you can inspect an individual run, step through it, and read the error of a failed batch — see Debugging a Pipeline.