I have a python program launching a batch job. The job outputs a json file, I'd like to know what is the easiest way to get this result back to the python program that launched it.
So far I thought of these solutions:
Upload the json file to S3 (pretty heavy)
Display it in the pod logs then read the logs from the python program (pretty hacky/dirty)
Mount a PVC, launch a second pod with the same PVC, and create a shared disk between this pod and the job (pretty overkill)
The json file is pretty lightweight. Isn't there a solution to do something like adding some metadata to the pod when the job completes? The python program can then just poll those metadata.
CodePudding user response：
An easy way not involving any other databases/pods is to run the first pod as an init container, mount a volume that is shared in both containers and use the JSON file in the next python program. (Also, this approach does not need a persistent volume, just a shared one), see this example:
Also, depending on the complexity of these jobs, would recommend taking a look at Argo workflows or any dag-related job schedulers.