We're not using a load balancer at the moment.

The easiest way is to add ELB and have amazon add the httpS on top (basically a few clicks on their console)

🤞

@<1687643893996195840:profile|RoundCat60> can you access the web UI over https ?

Yes the clearml-server AMI - we want to be able to back it up and encrypt it on our account

I think the easiest and safest way for you is to actually have full control over the AMI, and recreate once from scratch.
Basically any ubuntu/centos + docker and docker-compose should do the trick, wdyt ?

SmallAnt76
see https://clear.ml/pricing/ , under "What plan should I choose?"
what you are looking for is the first column "open-source". make sense ?

So assuming they are all on the same LB IP: You should do:
LB 8080 (https) -> instance 8080
LB 8008 (https) -> instance 8008
LB 8081 (https) -> instance 8081

It might also work with:
LB 443 (https) -> instance 8080

HI @<1687643893996195840:profile|RoundCat60>
Are you running on AWS ?

Hi @<1687643893996195840:profile|RoundCat60>
You mean the clearml-server AMI ?
I also wonder is there any specific reason to store previous versions ?

I'm suggesting to make it public.

Actually I'm thinking of enabling users to register Drivers in runtime, expanding the capability to support any type of URL link, meaning you can register "azure://" with AzureDriver, and the StorageHelper will automatically use the driver you provide.
This will make sure Any part of the system will be able to transparently use any custom driver.
wdyt?

Hi @<1730396272990359552:profile|CluelessMouse37>

However, the caching doesn't seem to be working correctly. Despite not changing the configuration, the first step runs every time.

How are you creating the cached component?
is this a standalone script or a git repo link?

These parameters are dictionaries of specific configurations (dict of dict) that are the same but might not be taken into account properly by the caching mechanism.

hmm for the component to be cached (or reuse...

And how did you connect your example,yaml?

Yes, because when a container is executed, the agent creates a new venv and inherits from the system wide installed packages, but it cannot inherit or "understand" there is an existing venv, and where it is.

but it still not is able to run any task after I abort and rerun another task

When you "run" a task you are pushing it to a queue, so how come a queue is empty? what happens after you push your newly cloned task to the queue ?

CleanWhale17 per your request :)

An automated ML Pipeline 👍 Automated Data Source Integration 👍 Data Pooling and Web Interface for Manual Annotation of Images(Seg. / Classif) [Allegro Enterprise] or users integrate with open-source Storage of Annotation output files(versioned JSON) 👍 Online-Training  Support(for Dataset Shifts) [Not Sure what you mean] Data Pre-processessing (filter/augment) [Allegro Enterprise] or users integrate with open-source Data-set visualization(stats...

Hi @<1687653458951278592:profile|StrangeStork48>

• Agreed,
• Notice this user/pass is only used for the initial authentication, after that all authentication is done via a signed JWT tokenHow about a GitHub issue with the feature request, if there is enough interest (or someone jumps in offering implementation) we can push it forward. What do you think?

Hi @<1687643893996195840:profile|RoundCat60>

anyone with access to the server

Is that a thing? If you have access to the server Not sure how "protected" you are even if using a key ring...
(unfortunately I do not think we support anything else, but what did you have in mind?

We’d be using https in production

Nice 🙂
@<1687653458951278592:profile|StrangeStork48> , I was reading this thread trying to understand what exactly is the security concern/fear here, and I'm not sure I fully understand. Any chance you can elaborate ?

Assuming it was hashed, the seed would be stored on the same server, so knowing both would allow me the same access, no?

• Set hashed passwords with  pass_hashed: true
• Generate passwords using  python3 -c 'import bcrypt,base64; print(base64.b64encode(bcrypt.hashpw("password".encode(), bcrypt.gensalt())))'  (obviously, replace "password" with the actual password). The resulting b64 string should be placed in the password field for each user.
  For example, assuming your password is "123456":
• bash:

> python3 -c 'import bcrypt,base64; print(base64.b64encode(bcrypt.hashpw("123456".encode(), bcrypt.gensal...

@<1687643893996195840:profile|RoundCat60> I'm assuming we are still talking about the S3 credentials, sadly no 😞
Are you familiar with boto and IAM roles ?

Let me check

Hi @<1687653458951278592:profile|StrangeStork48>

secrets manager per se,

Quick question, are you running the trains-server over http or https ?

None

As we can’t create keys in our AWS due to infosec requirements

Hmmm

I suggest a bump in the GitHub issue

Still not supported 😞

Hi FierceFly22

Hi, does anyone know where trains stores tensorboard data

Tesnorboard data is stored wherever you point your file-writer to 🙂
What trains is doing is while tensorboard writes it's own data to disk, it takes the data (in-flight) and sends it to the trains-server. The trains-server puts everything in the DB, so later everything is viewable & searchable.
Basically you don't need to store your TB files after your experiment is done, you have all the data in the trains-s...

Just curious, if

is a value I can set, where is it used?

It is used when Creating a dataset from inside the cluster (i.e. when launching using the clearml k8s glue),
it will have No effect on what users have on their local machines
i.e. they can always point to a diff server.

That said, when users create their initial clearml.conf and copy paste the info from the web UI, this value (or it might be another one, I'll double check later) will set the initial configuration the c...

Yes exactly !

Welp, it's been a day with the new settings, and stats went up 140K for API calls

... going to check again tomorrow to see if any of that was spill over from yesterday

140K calls a day, how often are you sending scalars ? how long is it running? how many experiments are running ?