you need to investigate why it’s still in Pending state

try this into the pod

usually you can see if you are getting timeouts or wrong http code

later in the day I will push also a new clearml chart that will not contain anymore k8s glue since it’s now in clearml-agent chart, this is why I was suggesting to use that chart :)

these are steps for major upgrade to latest chart version

then you should go in UI creating a new pair of access/secretkey and use them as parameters for agent so it can connect to clearml and authenticate

an implementation of this kind is interesting for you or do you suggest to fork? I mean, I don't want to impact your time reviewing

I suggest to try exec into agent pod and try to do some kubectl command like a simple kubectl get pod

yes

if you have problems with other images I suggest to run docker in emulation mode so you can run amd64 images

so do you want to mount files into agent pod?

moreover url exposed by nginx should be under https

exactly

In this case I apologize for confusion. If you are going for AWS autoscaler it's better to follow official way to go, the solution I proposed is for an onpremise cluster containing every componenet without autoscaler. sorry for

and are you sure you mongodb respawned on same node?

SuccessfulKoala55 yes, no autoscaler on that chart. Maybe I'm missing the point but the request was for an "on-premise" setup so I guessed no aws. If I missed the point everything I posted is not useful 😄

ty

Hi Tom; lets’ try to debug. Did you install all the charts in same namespace? Did you generate a key/secret pair from UI and the use them just in agent and serving chart?

yep but this is not how it should work with inpod

but TaskTypes is under Task

you will probably need a metrics-server on your k8s

and then use them in agents if they are external

about minor releases they are not breaking so it should be linear

AgitatedDove14 trainsConfig is totally optional and you can put the config file itself in it.. e.g.:
` trainsConfig: |-
sdk {
aws {
s3 {
key: ""
secret: ""
region: ""
credentials: [
{
host: "minio.minio:9000"
key: "DEMOaccessKey"
secret: "DEMOsecretKey"
...

you can create a specific config like one in https://clear.ml/docs/latest/docs/integrations/storage/

I don’t think it’s possible to setup queues in advance with any ClearML chart env var but I’m not 100% sure. SuccessfulKoala55 can you pls clarify this?

I absolutely need to improve the persistence part of this chart 😄

Hi, in k8s autoscaling must be managed by cloud pro user autoscaler. When the clearml-agent bound to related queue will spawn a new task pod with configured resources, k8s will adapt. On AWS you can start here https://docs.aws.amazon.com/eks/latest/userguide/autoscaling.html

oh yass

` ❯ clearml-task --version
ClearML launch - launch any codebase on remote machine running clearml-agent
usage: clearml-task [-h] [--version] [--project PROJECT] --name NAME [--repo REPO] [--branch BRANCH]
[--commit COMMIT] [--folder FOLDER] [--script SCRIPT] [--cwd CWD] [--args [ARGS [ARGS ...]]]
[--queue QUEUE] [--requirements REQUIREMENTS] [--packages [PACKAGES [PACKAGES ...]]]
[--docker DOCKER] [--docker_args DOCKER_ARGS]
...