# Pipe Runs

You can view the runs of a Pipe by going to the [Pipes tab in Pipekit](https://pipekit.io/pipes) and clicking on the Pipe you wish to view the runs of.

From here you can see all past runs of the Pipe. The view allows you to understand what [Run Conditions](/pipekit/pipes/managing-pipes/run-sync-conditions.md) triggered the run, the cluster the run ran on, the status of the run, the current progress of the run (if still running), any output message from Argo Workflows, the time the run started, and the duration of the run.

## Cron Pipes

You can also see past [Cron Workflow](/pipekit/pipes/cron-workflows.md) runs in the same way. Just click the Pipe you are interested in. If the underlying workflow was a Cron Workflow, you can see information about the cron schedule, as well as the standard Pipe run information.

## Stopping a running Run

If a run is still running, you can stop it by clicking the checkbox to the left of the run, and then clicking the `Stop` button at the top of the page. This will gracefully stop the run, and the run will be marked as `Stopped` in the list of runs.

{% hint style="info" %}
A `Stop` command is an asynchronous command. It may take a few moments for the run to stop, especially if your workflow has an exit handler that needs to complete before the run can be gracefully stopped.
{% endhint %}

## Resubmitting a Run

You can resubmit a run by clicking the checkbox to the left of the run, and then clicking the `Resubmit` button at the top of the page. This will create a new run of the workflow, with the same parameters as the original run.

{% hint style="info" %}
You can only resubmit a run if it is no longer running.
{% endhint %}

## More information about a Run

You can view more information about a given run by clicking on the run. This will take you to the run graph for the run. From here you can see the [run graph](/pipekit/pipes/pipe-runs/run-graph.md) for the run, the [pod logs](/pipekit/pipes/pipe-runs/pod-logs.md) for the run, and the [workflow logs](/pipekit/pipes/pipe-runs/workflow-logs.md) for the run.

## Data Retention

Pipekit will retain all runs for a Pipe. There is no limit to the number of runs that will be retained or the time period that they will be retained for.


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