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GH action to generate report #199

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GH action to generate report #199

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asmacdo
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@asmacdo asmacdo commented Sep 25, 2024

Fixes #177

Step 1: Create Skeleton

  • Authenticate with AWS
  • Connect to K8s cluster
  • deploys our job-runner pod onto a Karpenter NodeClaim
  • Creates a SPOT node as needed
  • Run dummy job
  • Delete Pod
  • Scale Down

I've verified that when a user-node is available (created by running a tiny jupyterhub), the job pod schedules on that node. I then shut down my jupyterhub and all user-nodes scaled down. I reran this job, and Karpenter successfully scaled up a new spot node, the pod was scheduled on it, ran successfully, was deleted, and the node cleaned up. Step 1 complete!

Step 2 Generate Report

  • Connect Pod to EFS
  • List users
  • du each user
  • du shared
  • collate data into report
  • Double Check that nodes come up and down successfully
  • Run job several times in 1 day, check next day for EFS usage spike (IIUC we should be fine because EFS is Bursting mode)

Step 3 Push Report

  • Create private GitHub repository to store reports
  • Configure bot permission to push to repo
  • push report to repo on complete

Questions to answer:

  • If a SPOT node is preempted, can we redeploy again later?

Comment on lines 4 to 6
pull_request:
branches:
- main
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Should we also run this on a weekly basis?

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It's on PR push just so I can test easily, but yes, 1/week sounds good to me. @kabilar Do you have a preference for what day/time?

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@kabilar kabilar Sep 26, 2024

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Great, thank you. How about Mondays at 6am EST? We can then review the report on Monday mornings.

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kabilar commented Nov 7, 2024

Hi @asmacdo, just checking in to see how this report generation is going? Thanks.

@asmacdo asmacdo force-pushed the cron-data-usage-report branch from f53e820 to ff52971 Compare November 8, 2024 18:41
Using ubuntu for more modern python (3.12 vs 3.7 with previous or 3.9 with another amazon linux)
Python 3.9 is new enough. Ubuntu was not ideal because the EFS mounting
require amazonl-efs-utils which is available via package manage for amazon linux,
but requires building from source on Ubuntu.
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asmacdo commented Dec 12, 2024

see if more recent AMI with newer than 3.7 python available (e.g. 3.10 to be future proof somewhat)

Amazon Linux 2023 comes with 3.9, which is sufficient. I briefly tried ubuntu 22.04, (with 3.12) but that would add complexity, requiring amazon-efs-utils to be installed from source.

gzip will only be needed if we want to upload to s3
=== Do not change lines below ===
{
 "chain": [],
 "cmd": "black .github/scripts/calculate-directory-stats.py",
 "exit": 0,
 "extra_inputs": [],
 "inputs": [],
 "outputs": [
  ".github/scripts/calculate-directory-stats.py"
 ],
 "pwd": "."
}
^^^ Do not change lines above ^^^
Holding the entire file index in memory would be risky, especially with
zarr files
Whether there is an error or not, write all fields for each file.
This allows us to read the tsv file and unpack the same number of values
for each line.
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asmacdo commented Dec 16, 2024

Update:

  • The automation is incomplete
    • the launch script sets up an ec2 instance with the scripts
    • scripts must be executed by hand
    • produced data must be retrieved by hand
  • Running in parallel (8 simultaneous) the file indexing takes about 16 minutes
  • The file indexes are 499MB
Heres an example of the json output produced by the report generator:
{
  "total_size": 238294213,
  "file_count": 3639,
  "caches": {
    "pycache": {
      "total_size": 22782820,
      "file_count": 1431,
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        "asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/pygments/formatters/__pycache__",
        "asmacdo/venvs/myenv/lib/python3.11/site-packages/con_duct/__pycache__",
        "asmacdo/dandi-notebooks/000971/lernerlab/seiler_2024/__pycache__"
      ]
    },
    "user_cache": {
      "total_size": 10852503,
      "file_count": 81,
      "directories": [
        "asmacdo/.cache"
      ]
    },
    "yarn_cache": {
      "total_size": 0,
      "file_count": 0,
      "directories": []
    },
    "pip_cache": {
      "total_size": 10852503,
      "file_count": 80,
      "directories": [
        "asmacdo/.cache/pip"
      ]
    },
    "nwb_cache": {
      "total_size": 0,
      "file_count": 0,
      "directories": []
    }
  }
}

Notably, the total size 238294213 is less than reported by du.
du --apparent: 247232941
du: 252841984

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User data quota cron job
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