This is totally what I was looking for! Yeah, by "good story for offline batch" I meant, "good feature support for ..."

I bookmarked this comment. I think I'll be doing a POC trying to show this functionality within the next month.

OOooh, excellent. So the file server isn't necessary at all if you're using some other object storage? That's slick!

Is there a way I could move the JWT authentication (not authorization) logic into an API Gateway or Load Balancer? For example, if ClearML is following OAuth 2.0, then the load balancer or API Gateway could reach out to it's "issuer URL" (probably available on the EC2 instance where ClearML is running) like this example here.
![image](https://clearml-web-assets.s3.amazonaws.c...

For now, I've written a headless selenium script to generate credentials for the fresh ClearML instance in CI.

I use the Dark Reader chrome extension 😆

If the load balancer it Gateway can do the computation and leverage caching, we’re much safer against DDOS attacks. In general, I’d prefer not to have our EC2 instance directly exposed to the public Internet.

Oh I wasn’t aware of that. I don’t think it’d work for this use case though. We’re trying to test the behavior you can see here in this extension https://share.descript.com/view/g0SLQTN6kAk so basically the examples I said in that earlier message

This is a low-key open-source project if anyone wanted to contribute. Since the project is early, there are lots of high-impact things, e.g. UI polish, that would be relatively low effort 😄

Does this mean that none of the credientials in this file can be used with the clearml SDK when the docker-compose.yaml starts up with a fresh state?

Is there anyway to achieve such a behavior? Or are manual steps simply required to get a working set of keys. I'm trying to prepare a docker-compose file that I can use for automated tests of our VS Code extension.

Is there a way we can protect a ClearML deployment with a load balancer or API Gateway that is exposed to the whole world, but is protected by authentication so that only authorized clients can get in?

I see. Is it possible for two agents to be utilizing the same GPU? (like if the machine has a terrific GPU, but only one of them?)

Hi friends, I'm just seeing these new messages. I read these links and I agree with @<1557175205510516736:profile|ShallowSwan53> . It's nice that the webapp has these pages, but what is the workflow to actually use this registry?

Also, @<1557175205510516736:profile|ShallowSwan53> , do you have a specific workflow in mind that you're hoping to get from ClearML?

At BEN, we're experimenting with

• BentoML for model serving. It's a Python REST framework a lot like FastAPI, but with some nice...

Hi! Yes, it just logs the .py file.

How it works / what we finished:

• We used the SaaS ClearML, started an EC2 instance, and manually installed and ran the clearml-agent daemon on it
• We ran clearml-init on our laptops to generate the clearml.conf file.
• The extension is in TypeScript, so...
• We started trying to write code with the Python SDK to list sessions, but realized calling that from the extension would be hard, so we opted to have the TypeScript code make calls to the ClearML API server directly, e.g. ...

Hi. Yes that totally makes sense. It’s just that we don’t want the logic that does the Jenkins trigger to be in a ClearML handler or task, but rather as a handler that acts as a subscriber in a pub-sub system.

This is because we have a pub-sub architecture that we already use, it can handle retries, etc. also we will likely want multiple systems to react to notifications in the pub sub system. We already have a lot of setup for this.

I guess the conclusion is: I realize it’s possible...

Ah, but it's probably worth noting that the docker-compose.yml does register the EC2 isntance that the server is running on as an agent listening on the services queue, so ongoing tasks in that queue that happen to be placed on the server would get terminated when docker-compose down is run.

Yeah. I'd need to clone this and run it locally to start to understand how it all works. Would be a cool exercise. They advertise that it's really easy to author VS Code extensions. I've seen pretty junior folks do it which makes me think it can't be too bad 😆

In a future iteration, it'd be cool if you could configure presets. Like maybe you have an on-startup.sh script you really like using to set up your instance, and VS Code extensions you want to pass to the --install-extensions ... flag

Thanks for the response @<1523701205467926528:profile|AgitatedDove14> !

What would you consider an event?

I was thinking of the TriggerScheduler 's definition of an event. Pretty much, any thing the TriggerSchedule allows you to react to, it'd be great to be able to publish those events to a queue external to ClearML, e.g. a tag added to a model (or removed), a state in a task changing, etc. We'd want as much metadata about that event as possible. So if the event is due to a task...

@<1557175205510516736:profile|ShallowSwan53> at this point, I think this question deserves it's own thread. I'm curious about it too!

Oh duh, thanks. What about non standard entrypoints (as opposed to arguments) like accelerate launch train.py ?

Hey, thanks for responding!

Does there happen to be ClearML auto-logging... for MLFlow? That would make it super easy for us to migrate our existing training/batch inference jobs to ClearML 😄

I literally just ran into this minutes ago and was about to file a bug report. A colleague ran into the same problem. It looks like urllib3 upgraded to v2 last week.

This thread should be immortalized. Super stoked to try this out!

The dark theme you have

It's this chrome extension ! I forget it's even on sometimes. It gives you a keyboard shortcut to toggle dark mode on any website. I love it.

Success! Wow, so this means I can use ClearML training/inference pipelines as part of AWS StepFunctions!

My plan is to have a AWS Step Functions state machine (DAG) that treats running a ClearML job as one step (task) in t...

That could work! Is that an option? Something that lets me spin up the ClearML and get a services worker to connect to it without manual steps.

I'll try to describe the scenario I was thinking would cause ClearML to break down:

Assume:

• We've got a queue called streaming
• We've got an S3 bucket with images landing inside
• When the images land, they go into a queue
• When there are 100 images in the queue, we trigger a ClearML pipeline to ingest, transform, run inference on the batch, and then write the results somewhere
• Let's say we get 1,000,000 images in the Bucket per hour. That might be 1,000,000 / 100 = 10,000 batches. ...

I took a look

• I think the Outerbounds extension (the one in my screenshot) is currently closed source. That makes sense to me. A bit sad because it is highly similar.
• Another example could be the AWS ToolKit extension. But sadly, it's hardly a "minimal example". I was thinking it's relevant because it uses your local ~/.aws/ folder, which is similar to what we'd want to do.

I think it will work. There's a lot of really useful code in the black extension. I'm recruiting people now to join in on Friday. I'm actually very confident about it after messing around.

possibly cheaper on the cloud (Lambda vs EC2 instance)

Whoa, are you saying there's an autoscaler that doesn't use EC2 instances? I may be misunderstanding, but that would be very cool.

Maybe I should have said: my plan is to use AWS StepFunctions where a single task in the DAG is an entire ClearML pipeline . The non-ClearML steps would orchestrate putting messages into a queue, doing retry logic, and triggering said pipeline.

I think at some point, there has to be some amount of...

Oh my word, is this it? None

Can you set these to any strings and have them function as API keys?