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Support multi-platform storages for Tensorboard #337

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IronPan opened this issue Nov 20, 2018 · 1 comment

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@IronPan
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commented Nov 20, 2018

Currently tensorboard pod mounts the GCP service accounts and can access to GCS.

const pod = {
kind: 'Pod',
metadata: {
generateName: 'tensorboard-',
},
spec: {
containers: [{
args: [
'tensorboard',
'--logdir',
logdir,
],
image: 'tensorflow/tensorflow',
name: 'tensorflow',
ports: [{
containerPort: 6006,
}],
env: [{
name: 'GOOGLE_APPLICATION_CREDENTIALS',
value: '/secret/gcp-credentials/user-gcp-sa.json'
}],
volumeMounts: [{
mountPath: '/secret/gcp-credentials',
name: 'gcp-credentials',
}],
}],
volumes:[{
name: 'gcp-credentials',
secret:{
secretName: 'user-gcp-sa',
},
}],
},
};

The credential should be a configurable parameter that user specifies, to read data from various storage, S3, PV, etc.

@Jeffwan

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commented May 7, 2019

@IronPan

Any idea how could we improve this manifest? The most straightforward way is check logdir protocol?

  1. for gcs, s3 and minio, pod can mount cloud provider specific environment and secrets
  2. for local disk, we need pvc name and mountPath?
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