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Deployment of image processing, ideally somewhere maintained by others! #47
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https://github.com/NERC-CEH/plankton_ml/blob/main/PIPELINES.md - this has the walkthrough of setting up the Luigi-based workflow (from NAS to object store). |
https://luigi.readthedocs.io/en/stable/central_scheduler.html - docs for the central scheduler. it's more of a task manager and UI, reminds me of Celery Flower, the expectation with Luigi is you use While testing this my connection to the VM died, |
I set up a (should be?) a small change and I might try to contribute it right now, but worried for our Luigi usage that it's been a known issue for over a year and version pinning to pre-2.0 is still the suggestion edit ... now at Luigi's equivalent of this issue with edit ... seeing there's already an unmerged PR with the same set of changes I was considering, i'll try to leave a helpful comment there and then just pin sqlalchemy spotify/luigi#3267 |
Range of options on this
[ ] luigid running on a development VM in the on-prem cloud with direct read access to NAS
[ ] chromadb also running locally on the same machine
[ ] Object store API in Posit or Datalabs (how do apps then authenticate?)
[ ] luigid in a container on e.g. kubernetes in the on-prem cloud, but with a means of mounting data from the NAS
[ ] Data from the NAS going unprocessed to an object store, and the pipelines reading from there, obviating the need to connect applications to local storage
[ ] tasks running in e.g. Airflow rather than within Luigi
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