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Hello Everybody, I'M Seeking For A Clarification On The 'Metrics' Quote For The Saas Platform. My Workspace Only Uses Self S3 Storage As The File Server To Store Artifacts, Datasets And Models. For Some Reason, My 'Metrics' Quota Is Blown Up By > 30Gb Of

Hello everybody,
I'm seeking for a clarification on the 'Metrics' quote for the SAAS platform.
My workspace only uses self S3 storage as the File Server to store artifacts, datasets and models.
For some reason, my 'Metrics' quota is blown up by > 30GB of data.
What kind of data is considered a Metric? I guess scalars reporting, and maybe console logs? How come It became so big?
image

  
  
Posted one year ago
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Answers 5


I did found this:

from clearml.backend_api.session.client import APIClient
client = APIClient()
client.events.get_task_metrics(tasks=['some_task_id'], event_type='log')

but it returns an empty 'metrics' object

  
  
Posted one year ago

@<1523701070390366208:profile|CostlyOstrich36>
Well, I doubt that it is the case in my situation.
Is there any API where I can get read the metrics per experiment?

  
  
Posted one year ago

the experiments themselves 🙂

Imagine if you have very large diffs or very large (several mb) configuration files logged into the system - this is sitting somewhere in the backend on a database

  
  
Posted one year ago

Thanks @<1523701070390366208:profile|CostlyOstrich36> .
What are considered as experiment objects?

  
  
Posted one year ago

Hi @<1523703961872240640:profile|CrookedWalrus33> , metrics are considered as scalers, logs, plots, and the experiment objects themselves that are saved in the backend databases.

You must be reporting some very metric heavy experiments 🙂

  
  
Posted one year ago
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