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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 2 years ago
Votes Newest

Answers 5


Hi 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 2 years ago

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 2 years ago

Thanks CostlyOstrich36 .
What are considered as experiment objects?

  
  
Posted 2 years 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 2 years ago

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 2 years ago
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5 Answers
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