green open events-log-d1bd92a3b039400cbafc60a7a5b1e52b Yh4BPGmgRZKU7STdCghmtw 1 0 96 0 175.1kb 175.1kb 175.1kb
And are you still getting exactly this error?
<500/100: events.add_batch/v1.0 (General data error: err=1 document(s) failed to index., extra_info=[events-log-d1bd92a3b039400cbafc60a7a5b1e52b][0] primary shard is not active Timeout: [1m], request: [BulkShardRequest [[events-log-d1bd92a3b039400cbafc60a7a5b1e52b][0]] containing [index {[events-log-d1bd92a3b039400cbafc60a7a5b1e52b][f3abecd0f46f4bd289e0ac39662fd850], source[{"timestamp":1747654820464,"type":"log","task":"fd3d00d99d88427bbc576cba53db062d","level":"info","worker":"b1193fbdd662","msg":"Starting the training.\nClearML Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoring","model_event":false,"@timestamp":"2025-05-19T11:40:21.919Z","metric":"","variant":""}]}] and a refresh])>
it's
ClearML Monitor: Could not detect iteration reporting, falling back to iterations as seconds-from-start
fzd6tw0x46-algo-1-lswt4 | 2025-05-20 10:02:08,177 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683ccb670>, 'Connection to "" timed out. (connect timeout=300.0)')': /
fzd6tw0x46-algo-1-lswt4 | 2025-05-20 10:02:08,178 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683cc9810>, 'Connection to "" timed out. (connect timeout=300.0)')': /
fzd6tw0x46-algo-1-lswt4 | 2025-05-20 10:02:08,178 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urlli
so, the same ClearML monitor error, but another issue now.
btw, the task logs the configuration, artifacts, etc.
I get this error at the end.
This seems something different not connected to ES. Where do you get these logs?
ClearML Task: created new task id=f08b012bce42420dba7cd166668f5e4b
2025-05-20 09:54:59,251 - clearml.Task - INFO - No repository found, storing script code instead
ClearML results page: /projects/184c6e8651d94b9088ae60ae3a9c8ace/experiments/f08b012bce42420dba7cd166668f5e4b/output/log
2025-05-20 12:55:02
ClearML Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoring
Starting the training.
....
ClearML Monitor: Could not detect iteration reporting, falling back to iterations as seconds-from-start
2025-05-20 13:02:08
2025-05-20 10:02:08,177 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683ccb670>, 'Connection to ec2-13-217-109-164.compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:02:08,178 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683cc9810>, 'Connection to ec2-13-217-109-164.compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:02:08,178 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683ccb6a0>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 13:04:25
2025-05-20 10:04:25,347 - urllib3.connectionpool - WARNING - Retrying (Retry(total=1, connect=1, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683c32bf0>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:04:25,348 - urllib3.connectionpool - WARNING - Retrying (Retry(total=1, connect=1, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683c32c20>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:04:25,348 - urllib3.connectionpool - WARNING - Retrying (Retry(total=1, connect=1, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683c33040>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 13:06:48
2025-05-20 10:06:48,615 - urllib3.connectionpool - WARNING - Retrying (Retry(total=0, connect=0, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683c32da0>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:06:48,616 - urllib3.connectionpool - WARNING - Retrying (Retry(total=0, connect=0, read=5, redirect=5, status=None)) after connection broken by 'ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x76f683c33f40>, 'Connection to .compute-1.amazonaws.com timed out. (connect timeout=300.0)')': /
2025-05-20 10:06:48,616 - urllib3.connectionpool - WARNING - Retrying (Retry(total=0, connect=0, read=5, redirect=5, status=None)) after
I assume that ec2-13-217-109-164.compute-1.amazonaws.com is the ec2 instance where the API is running?
Are you using the files server or S3 for storage? Can you verify on the storage itself that the artifacts are actually uploaded and are downloadable?
I tested that theory before; I commented out these two lines
output_model = OutputModel(task=task, name="trained_model")
output_model.update_weights(register_uri=s3_model_uri)
The issue, however, persisted.
I'm begining to think that there is something besides ClearML. I'll execute the training script on remote (SageMaker), instead of SageMaker local mode.
@<1722061389024989184:profile|ResponsiveKoala38> @<1523701070390366208:profile|CostlyOstrich36>
it's ClearML, I commented out clearml lines, and it ran successfully!
Also, (without CLearML) the model artifacts are uploaded/downloadable.
So you watered it down to these lines?
output_model = OutputModel(task=task, name="trained_model")
output_model.update_weights(register_uri=s3_model_uri)
This is what causes the timeout errors? Did you define
no, it's something else.
I commented out the above two line and I was still facing the issue.
Can you provide a standalone code snippet that reproduces this behaviour?
That's a big context!
In general, I'm using standard functions; the script is running in SageMaker pipeline.
The model, however, is a composite, and consists of multiple primitive ones.
task = Task.init(
project_name="icp",
task_name=f"model_training_{client_name}",
task_type=Task.TaskTypes.training,
auto_connect_frameworks={'matplotlib': True, 'tensorflow': False,
'tensorboard': False,
'pytorch': False, 'xgboost': False, 'scikit': False, 'fastai': False,
'lightgbm': False, 'hydra': True, 'detect_repository': True, 'tfdefines': False,
'joblib': False, 'megengine': False, 'catboost': False, 'gradio': False
},
output_uri=False
)
task.set_script(repository=repo_url, branch=branch_name, working_dir="./", commit=commit_id)
task.set_parameter("commit_id", commit_id)
task.connect_configuration()
output_model = OutputModel(task=task, name="trained_model")
output_model.update_weights(register_uri=s3_model_uri)
....
task = Task.current_task()
if task is None:
print("Warning: No ClearML task found. Metrics will not be logged to ClearML.")
logger = None
else:
logger = task.get_logger()
logger.report_matplotlib_figure()
logger.report_scalar()
to close this thread, file server port wasn't configured
I added
- IpProtocol: tcp
FromPort: 8081
ToPort: 8081
CidrIp: 0.0.0.0/0
to cloudformation template, and it was resolved.
Thanks a bunch, guys
@<1722061389024989184:profile|ResponsiveKoala38> @<1523701070390366208:profile|CostlyOstrich36>
Also, it would be great if you could add a recommendation for EBS size in this guide ( None ),
The Elastic Search issue happened with 8 GB, and was resolved with 15 GB.