When you create a new support request, we need to be able to reproduce your issue on our infrastructure. To aid our efforts, we ask that you provide us with a minimal reproducible pipeline that will allow us to identify a solution to your issue in a reduced timeframe. The more information you provide upfront, the less additional information we will need to request from you to start our debugging process. Once your issue has been reproduced on our infrastructure, we can advise on the expected behavior and the steps you need to take for the solution.
A minimal reproducible pipeline may consist of one or more of the following components:
For Nextflow pipelines, include:
As few processes as possible
Ideally, provide us with the process information that you are experiencing issues with, rather than your entire production pipeline
Any required Nextflow configuration
Include all the configuration variables that are relevant to the problematic processes in your nextflow.config
Access to the containers used by the pipeline, if they aren’t already public
To rule out any issues with your containers, we need to run the pipeline using the same containers used in your environment
A minimal test dataset that can be used as input to the pipeline
With some exceptions, we generally do not need your entire production dataset to be able to reproduce your pipeline issue
The exact command and parameters used to run the pipeline
To rule out the run parameters as the cause of your issue
Specific details about the compute environment and infrastructure (if applicable)
Any relevant information about your environment will allow us to replicate your pipeline in the same setting that produced your issue
Any other relevant information
Cloud provider constraints, software dependencies, etc.
Other useful information:
Nextflow version
Tower version
Tower CLI version and exact command (if applicable)
Java version
You can either attach the files listed above to your initial email, the issue (if already created) in our support portal, or (ideally) via a Git repo that contains the code. This will make it easier for us to clone and run the pipeline.
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