tensorflow / tensorflow/tensorboard
tensorboard not working with S3
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Description
Environment information (required)
Mac 10.14.6
Tensorboard 2.0.0
botocore 1.19.1
boto3 1.16.0
tensorflow 2.0.0 mkl_py37hda344b4_0
tensorflow-base 2.0.0 mkl_py37h66b1bf0_0
tensorflow-estimator 2.0.0 pyh2649769_0
AWS credentials are available in the ~/.aws/credentails file in profile default
Issue description
AWS_LOG_LEVEL=1 AWS_DEFAULT_PROFILE=default S3_REGION=eu-west-1 tensorboard --logdir s3://gourav-bucket/gourav-data/tensorboard/
gives the following errors:
Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all
TensorBoard 2.0.0 at http://localhost:6006/ (Press CTRL+C to quit)
2020-10-24 23:13:51.056759: E tensorflow/core/platform/s3/aws_logging.cc:60] Curl returned error code 28
2020-10-24 23:13:51.056861: E tensorflow/core/platform/s3/aws_logging.cc:60] Http request to retrieve credentials failed
2020-10-24 23:13:51.056910: W tensorflow/core/platform/s3/aws_logging.cc:57] Request failed, now waiting 0 ms before attempting again.
2020-10-24 23:13:52.057796: E tensorflow/core/platform/s3/aws_logging.cc:60] Curl returned error code 28
2020-10-24 23:13:52.057882: E tensorflow/core/platform/s3/aws_logging.cc:60] Http request to retrieve credentials failed
2020-10-24 23:13:52.057923: W tensorflow/core/platform/s3/aws_logging.cc:57] Request failed, now waiting 2000 ms before attempting again.
2020-10-24 23:13:55.062484: E tensorflow/core/platform/s3/aws_logging.cc:60] Curl returned error code 28
2020-10-24 23:13:55.062540: E tensorflow/core/platform/s3/aws_logging.cc:60] Http request to retrieve credentials failed
2020-10-24 23:13:55.062570: W tensorflow/core/platform/s3/aws_logging.cc:57] Request failed, now waiting 4000 ms before attempting again.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the reported command with TensorBoard 2.0.0 and the listed AWS environment variables, then investigate the credential retrieval path indicated by the S3 error output. Done means TensorBoard can access the specified S3 log directory using the default profile without repeated credential-request failures.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws
- Domain
- cloud
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100