Thought this looked familiar.
https://clearml.slack.com/archives/CTK20V944/p1635323823155700?thread_ts=1635323823.155700&cid=CTK20V944

It's a local deployment. I was only presented with username without a need to enter passwords. When I'm in, I don't see an option in my profile to set a password as well. Neither is there integration with ldap for example.

Thanks SuccessfulKoala55 , how might I do this clean up? Does this increase with more use of ClearML? And to add, we save all artifacts onto a remote S3 server.

Thanks. This appears to be solely for web UI and API, What if i want to orchestrate on K8S?

Hi i missed this. Is there a recording?

Hi, we are still not getting the model repo to work, mainly due to clearml.storage failing to save the models.
We tried a vanilla boto3 code and it works, but we can't figure out why we get connectionreseterror 104 when clearml does it.

How do we configure clearml in correspondence to following boto code?

S3= boto3.resource('s3', endpoint_url=' https://ecs.ai ', aws_access_key_id='mykey', aws_secret_access_key='mysevret', config=Config(signature_version='s3v4'), region_name='us-east-1', ve...

Try set docker_force_pull: true under agent section of your agent's clearml.conf.

Here's my two cents worth.
I thought its really nice to start off the topic highlighting 'pipelines', its unfortunately one of the most missed component when ppl start off with ML work. Your article mentioned about drfits and how MLOps process covered it. I thought there are 2 more components that was important and deserves some mention.Retraining pipelines. ML engineers tend not to give much thought to how they want to transit a training pipeline in development to a automated retraining pipe...

It didn't work as expected.
` task init
task report iter 10

task init
task report iter 10

The second task pushed the reporting iteration to 20 instead. `

ah ok, so if i see Jax's workspace on https://app.community.clear.ml/dashboard , then i'm on the right track? How regular does this reset then?

Nice, what are the names of the talks?

I see. Is there a more elaborate codeset that describes the above interactions?

Sorry i forgot to paste the logs.

Previously we had similar issues when we switched images used in agent. Might want to check on that.

I'm also beginning to think this is related to https://clearml.slack.com/archives/CTK20V944/p1620664770492400 . Previously when i set force_repo_requirements_txt=true and system_site_packages: true , it seems to work. upgrading to v1.02 seems to change things.

ok, i'll wait till i get my hands on vault then. thanks.

Yeah that'll cover the first two points, but I don't see how it'll end up as a dataset catalogue as advertised.

Ok thanks. that explains alot. We have been doing this wrongly the whole time, thinking that the clearml.conf on the client side would be acknowledged by the remote agent execution. In reality, only the API section is utilised.

Hi.

We tried as advised above and it still didn't work.
Host: http://ecs.ai:443
output_uri = S3://ecs.ai:443/bucketname

This time round the client gave this error.
Botocore.exceptions.connectiinclosederror: connection was closed before we received a valid response from endpoint URL: ' http://ecs.ai/bucketname/.clearml.test '.

It's quite apparent that whatever clearml passed to boto3 ends up as a http call instead of https, which is wrong.

Having same issues. Looks like Google DNS can't resolve the DNS at all.
` %nslookup app.clear.ml - 8.8.8.8
Server: 8.8.8.8
Address: 8.8.8.8#53

** server can't find app.clear.ml: SERVFAIL `

I've been reading the documentation for a while and I'm not getting the following very well.
Given an open source codes say, huggingface. I wanted to do some training and i wanted to track my experiments using ClearML. The obvious choice would be to use Explicit Reporting in ClearML. But the part on sending my training job. and let ClearML orchestrate is vague. Would appreciate if i can be guided to the right documentation on this.

Hi, for both of them,  args.lastiter  is the exact same value. But when plotted out, they are 2 actually iterations apart.

Hi. nice read. Your permalink is wrong though, here's the right one.
https://cpatrickalves.com/mlops-what-it-is-and-why-does-it-matter

Hi AgitatedDove14 , i dug a bitt deeper. I saw this in installed packages in the original completed task. When the task is cloned, this is copied over and thus the problem. Can i ask, how ClearML create the list of installed packages? Why is it that some of them (E.g. attr is being pulled from @ file:///tmp/build/80754af9/attrs_1604765588209/work)

` absl-py==0.11.0
alabaster==0.7.12
antlr4-python3-runtime==4.8
apex==0.1
appdirs==1.4.4
argon2-cffi==20.1.0
ascii-graph==1.5.1
async-gener...

I would say its intermittent.

Space is way above nominal. What created this folder that it's trying to process? What processing is this?
Processing /tmp/build/80754af9/attrs_1604765588209/workIs there any paths in the agent machine that i can clear out to remove any possible issues from previous versions?

AgitatedDove14 , would you elaborate on this resolution process?

I see i understand better now. Thanks.

ok thanks. this would mean that increasing the disk space for my ClearML is the only option as we are not at liberty to delete.

Does the glue write any error logs anywhere? I only see CLEARML_AGENT_UPDATE_VERSION =
and nothing else.