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 would try it again.

@<1722061389024989184:profile|ResponsiveKoala38> @<1523701070390366208:profile|CostlyOstrich36>
it's ClearML, I commented out clearml lines, and it ran successfully!

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.

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

no, it's something else.

I commented out the above two line and I was still facing the issue.

Yes

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.

Alright, it's running...

Probably the 9200 port is not mapped from the ES container in the docker compose
The easiest would be to perform "sudo docker exec -it clearml-elastic /bin/bash" and then run the curl command from inside the ES docker

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

console (client).

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 

Also, (without CLearML) the model artifacts are uploaded/downloadable.

Hi @<1835488771542355968:profile|PerplexedShells66> , please inspect your Elasticsearch logs. Any errors or warnings there?

I do not see any issues in the log. Do you still get errors in the task due to the failure in events.add_batch?

One of the most likely reasons for this issue would be insufficient free disk space for Elasticsearch. This may happen if less than 10% of free space is left on ES storage location. But there may be also other reasons

It depends on your usage. ES has some default watermarks that are activated when the amount of used space is above 85% and 90% (can be overwritten) of the storage. At some point it may transfer the index to a "readonly" state.

@<1722061389024989184:profile|ResponsiveKoala38> It's not resolved.

ok, I'm recreating the ec2 isntance to generate ssh key pair, then I'll check the elasticsearch logs.

I don't store anything on clearml server; everything is being stored in S3 and referenced by ClearML.

{
  "error" : {
    "root_cause" : [
      {
        "type" : "illegal_argument_exception",
        "reason" : "No shard was specified in the request which means the response should explain a randomly-chosen unassigned shard, but there are no unassigned shards in this cluster. To explain the allocation of an assigned shard you must specify the target shard in the request. See 

 for more information."
      }
    ],
    "type" : "illegal_argument_exception",
    "reason" : "No shard was specified in the request which means the response should explain a randomly-chosen unassigned shard, but there are no unassigned shards in this cluster. To explain the allocation of an assigned shard you must specify the target shard in the request. See 

 for more information."
  },
  "status" : 400
}

this means that elasticsearch server hasn't started, right?

it's behaving very strangely.

I'm trying to provision the instance, but something is off.
It's as if some functionalities are missing.

What is the status that you get for the "events-log-d1bd92a3b039400cbafc60a7a5b1e52b" index?

green open events-log-d1bd92a3b039400cbafc60a7a5b1e52b            Yh4BPGmgRZKU7STdCghmtw 1 0   96 0 175.1kb 175.1kb 175.1kb

Looks like elastic is failing to access a shard. Do you have visibility into machine utilization? How much RAM is elastic consuming?

Also, is this the entire error repeating or is there more context?

ok. Currently the ebs is 15 GB, is there a recommended size?

No, it says that it does not detect any problematic shards. Given that output and the absence of the errors in the logs I would expect that you will not get the error anymore

@<1523701070390366208:profile|CostlyOstrich36>
I've updated the instance type to t3a.large.
The issue persisted.