For example, it would useful to integrate https://github.com/whylabs/whylogs#features into ClearML as part of data and model monitoring. WhyLogs would have their own static page that would preferably be displayed as a new custom tab (besides logs, scalars and plots.).

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

Hi CostlyOstrich36 , What you described is task. I was referring to the pipeline controller.

Hi SuccessfulKoala55 , just wondering how i can follow up on this.

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

clearml=1.0.3
python=3.8.10
clearml-data upload --id 12314jhg42342j4j --storagehttp://ecs.ai is an on-prem DELL EMC ECS that serves as our S3 storage configured with s self signed cert.

Alright, fingers crossed.

Just to put a ping for those on this side of the timezone to look at. Thanks.

Hi. The upgrade seems to go well but i'm seeing one wierd output. When i ran a task and observe the software installed under the execution tab , i still see clearml=0.17 . Is this expected?

Yes I am.

I think a related question is, ClearML replies heavily on Triton (Good thing) but Triton only support a few frameworks out of the box. So this 'engine' need to make sure its can work with Triton and use all its wonderful features such as request batching, GPU reuse...etc.

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 `

Hi it is missing --docker on the agent. Thanks! Dynamic GPU option only available with Enterprise version right?

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.

I see, so its a path. Another question, as far as i can tell, clearml-data will download entire datasets before starting training. This isn't very ideal when we are dealing with billions of datasets (E.g. WE might want to download a subset at a time, send to GPU for training and then use the CPU to concurrently pull another subset.). Any comments on this?

ah thanks. Hopefully the old ones get flushed out by Google soon.

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

Thanks. We set this configuration and the client ran and submitted the job for remote execution (agent running k8s glue). However when the job runs, and tries to save into model repo, this error came up.
ClearML.storage - ERROR - Failed creating storage object S3://ecs.ai Reason; Missing key and secret for S3 storage access ( S3://ECS.ai ).

I remember being told that the ClearML.conf on the client will not be used in a remote execution like the above so I think this was the problem. I also...

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 CostlyOstrich36 , That's correct.

What type of pipeline steps are you running? From task, decorator or function?

We were trying with 'from task' at the moment. But the question apply to all methods.

If they're all running on the same container why not make them the same task and do things in parallel?

The tasks were created by different teams and their tasks content is rather independent and modular. Usage of them is usually optional. For example, task1 performs 'image whitening', task2 performs 'image resize'.

Hi SuccessfulKoala55 , just to add, my clearml.conf (client) and clearml.agent.conf (agent) can have differing values. I'm not sure which one takes precedence and if this could be the cause.

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?

Its. 0.17-63.
It doesn't appear in profile page.

AgitatedDove14 , would you elaborate on this resolution process?

I see i understand better now. Thanks.