You need to specify it. Or you could specify this in your config: https://github.com/allegroai/clearml/blob/54c601eea2f9981bb8e360a8203bc36696a55cfd/clearml/config/default/sdk.conf#L164

SmugDolphin23 Sorry to bother again, output_uri should be a URI to S3 endpoint or clear ml fileserver? If it's not provided artifacts are stored locally, right?

I think that will work, but I'm not sure actually. I know for sure that something like us-east-2 is supported

@<1523701087100473344:profile|SuccessfulKoala55> Fixed it by setting env var with path to certificates. I was sure that wouldn't help since I can curl and python get request to my endpoint from shell just fine. Now it says I am missing security headers, seems it's something on my side. Will try to fix this

@<1523701304709353472:profile|OddShrimp85> I fixed my SSL error by putting REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt in .bashrc file

Can you share a snippet?

How can you have a certificate error if you're using S3? I'm sure their certificate is OK...

SmugDolphin23 Thank you very much!
That's clearml.conf for ClearML end users right?

@<1523701435869433856:profile|SmugDolphin23> @<1523701087100473344:profile|SuccessfulKoala55>
2023-02-03 20:38:14,515 - clearml.metrics - WARNING - Failed uploading to <my-endpoint> (HTTPSConnectionPool(host=' e ndpoint', port=443): Max retries exceeded with url: / (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1131)'))))
2023-02-03 20:38:14,517 - clearml.metrics - ERROR - Not uploading 1/2 events because the data upload failed

@<1523701435869433856:profile|SmugDolphin23> Thanks a lot, that actually worked! It was very difficult to figure out you have to plug those exact values given you have https endpoint:

• Using s3 protocol instead of https together with bucket name in output URI
• Not providing a bucket name in credentials section where it is by default
• Providing default secure port for both host and output URI
• Disabling credentials chainI think a common use case for many people that they get S3 storage with integrated Amazon solution where they are provided with region and a bucket name. Together with access key it's sufficient to connect to their cloud. But a lot of people, especially in enterprise have a case like mine where they have https endpoint to their company hosted S3 solution so I think it would be great to reflect that case in documentation so other people would have easier time to configure https endpoints for clearml-agent. Another thing would be nice to have is to support endpoint parameter under S3 section of clearml.conf which if provided as is (with https and no port) is sufficient to connect to S3 bucket. That would require some coding and rewriting URL constructing methods and maybe boto3 calls (I peeked inside a code and would say some places regarding this issue were questionable e.g. init method in _Container class in helper.py). I would try to fix it myself and make a pull request if working schedule lets me but I can't make a promise on that.
  @<1523701070390366208:profile|CostlyOstrich36> @<1523701087100473344:profile|SuccessfulKoala55> H. Thank you too for helping! Would be great if you'd try to look at the issue I discussed in this message.
  Good luck, guys!

@<1526734383564722176:profile|BoredBat47> the bucket name in your case should just be somebucket (and should not start with s3:// )

The S3 endpoint

` from random import random
from clearml import Task, TaskTypes

args = {}
task: Task = Task.init(
project_name="My Proj",
task_name='Sample task',
task_type=TaskTypes.inference,
auto_connect_frameworks=False
)
task.connect(args)
task.execute_remotely(queue_name="default")
value = random()
task.get_logger().report_single_value(name="sample_value", value=value)
with open("some_artifact.txt", "w") as f:
f.write(f"Some random value: {value}\n")
task.upload_artifact(name="test_artifact", artifact_object="some_artifact.txt") `

@<1523701087100473344:profile|SuccessfulKoala55> Hey, Jake, getting back to you. I couldn't be able to resolve my issue. I can access my bucket by any means just fine, e.g. by S3 CLI client. All the tools I use require 4 params: AK, SK, endpoint, bucket. I wonder why ClearML doesn't have explicit endpoint parameter and you have to use output_uri for it and why is there a region when other tools don't require it.

The only expection is the models if I'm not mistaken, which are stored locally by default.

SmugDolphin23

@<1523701304709353472:profile|OddShrimp85> I haven't done it, for me it worked as-is

` s3 {
# S3 credentials, used for read/write access by various SDK elements

        # default, used for any bucket not specified below
        key: "mykey"
        secret: "mysecret"
        region: " ` ` "

        credentials: [

             {
                 bucket: "mybucket"
                 key: "mykey"
                 secret: "mysecret"
                 region: " ` ` "
              }, `

A bit overwhelmed by configuration, since it has an agent, a server and bunch of configuration files, easy to mess up

May I know where to set the cert to in env variable?

@<1523701087100473344:profile|SuccessfulKoala55> I figured where to find a region but we don't have an AWS dashboard. We have a custom S3 solution for our own enterprise servers like many companies do, data is not stored on amazon servers. That is why we have and endpoint which is an URL starting with http:// If I would connect to our bucket via boto3 I would pass endpoint to a client session with endpoint_url

Oh, it's configured o agent machine, got you

it's pretty much the same

@<1523701435869433856:profile|SmugDolphin23> Hello, again! I tried to fill the values by your example. Still no luck. I noticed console log on my task says that I have certificate error. I disabled it in api section in clearml.conf like this: verify_certificate = false and I still have SSL error. Any clues why would that be?

And I believe that by default we send artifacts to the clearml server if not specified

OK. Bt the way, you can find the region from the AWS dashabord

Yeah, that's always the case with complex systems 😕

check the output_uri parameter in Task.init

it's the same file you added your s3 creds to

Could you try adding region under credentials as well?