Cause when i check it references to 3y ago and i am following this: None

As far as i can test, the server is going ok, i had some isses with resources not loading but solved those. The bigger issue for now is agent and prob could propagate to the serving. Later on i plan on adding also gpu resouces to both so im not entirely sure on that part

clearml-apiserver-866ccf75f7-zr5wx 1/1 Running 0 37m
clearml-apiserver-asyncdelete-8dfb574b8-8gbcv 1/1 Running 0 37m
clearml-elastic-master-0 ...

Hey! @<1729671499981262848:profile|CooperativeKitten94> Is there any tips you can give me on this?

It seems like the most recent version supported for kubernetes is clearml-agent==1.9.2?

thanks again!

Sorry we had a short delay on the deployment but

with these values:

clearml:
  agentk8sglueKey: "8888TMDLWYY7ZQJJ0I7R2X2RSP8XFT"
  agentk8sglueSecret: "oNODbBkDGhcDscTENQyr-GM0cE8IO7xmpaPdqyfsfaWearo1S8EQ8eBOxu-opW8dVUU"
  clearmlConfig: |-
    api {
        web_server: 

        api_server: 

        files_server: 

        credentials {
            "access_key" = "8888TMDLWYY7ZQJJ0I7R2X2RSP8XFT"
            "secret_key" = "oNODbBkDGhcDscTENQyr-...

I will try :
1- update the agent with these values
2- run argo with those changes

Yeah i know.. thats what i did for the github implementation, but for this i need them to be generated on the fly or via CLI that i can use argo to create if thats possible

I had those setted on the config file, but i can provide you what i am using for server and agent config if it helps. I got lost on the configs so i tried everything 🤣

I will get back at you in 15mn if thats ok

parameters:
      - name: namespace
        value: clearml-prod
      - name: node-ip
        value: "192.168.70.211"
      - name: force-cleanup
        value: "false"
      - name: install-server
        value: "true"
      - name: install-agent
        value: "true"
      - name: install-serving
        value: "true"
      - name: diagnose-only
        value: "false"
      - name: storage-class
        value: openebs-hostpath
      - name: helm-timeout
        value: 900s
      - nam...

and for dev im not providing

with the values on helm

 helm get values clearml-agent -n clearml-prod
USER-SUPPLIED VALUES:
agentk8sglue:
  apiServerUrlReference: 

  clearmlcheckCertificate: false
  createQueueIfNotExists: true
  fileServerUrlReference: 

  image:
    pullPolicy: Always
    repository: allegroai/clearml-agent-k8s-base
    tag: latest
  queue: default
  resources:
    limits:
      cpu: 500m
      memory: 1Gi
    requests:
      cpu: 100m
      memory: 256Mi
  webServerUrlRefe...

The value field is a default argo falls back into if i dont provide any

Python regex error in k8s glue agent :

sre_constants.error: bad inline flags: cannot turn on global flag at position 92

• Issue is in clearml-agent k8s glue codebase (Python 3.6 compatibility)
• Not configuration-related - persists across different HOCON formats
• Affects image tags: 1.24-21 , 1.24-23 , latest

Hi! Im using just a plain Kubernetes cluster (kubeadm) running on Proxmox VM, and im using Argo to deploy the helm, in order to standarize it Let me know if you need any more details!

I also see these logs:
bash

/root/entrypoint.sh: line 28: /root/clearml.conf: Read-only file system

This indicates that the container's filesystem is mounted as read-only , preventing the agent from writing its configuration file.

From

podSecurityContext:
  readOnlyRootFilesystem: true  # This causes the issue

PodSecurityPolicies
Security Context Constraints (OpenShift)
Admission controllers enforcing read-only filesystems

I have separed the most crutial part. Its a container that runs the standard helm commands

example:
....
cat > /tmp/server-values.yaml <<EOF
global:
defaultStorageClass: $STORAGE_CLASS

        apiserver:

...
helm install clearml clearml/clearml
--namespace "$NS"
--values /tmp/server-values.yaml
--wait
--timeout "$TMO"

...

helm install clearml-agent clearml/clearml-agent
-...

for now:

• name: clearml-access-key
  value: CLEARML8AGENT9KEY1234567890ABCD
  - name: clearml-secret-key
  value: CLEARML-AGENT-SECRET-1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ123456
  - name: admin-password
  value: clearml123!

kubectl describe pod -n clearml-prod -l app.kubernetes.io/name=clearml-agent
kubectl logs -n clearml-prod -l app.kubernetes.io/name=clearml-agent --previous 2>/dev/null || true
Name:             clearml-agent-848875fbdc-x8x6s
Namespace:        clearml-prod
Priority:         0
Service Account:  clearml-agent-sa
Node:             kharrinhao/192.168.70.211
Start Time:       Mon, 21 Jul 2025 15:23:02 +0000
Labels:           app.kubernetes.io/instance=clearml-agent
                  app.kube...

Yes i am using those, they are hardcoded ones cause i will on a later stage generate them via a secure method

I had no issues deploying via the Github but helm is quite more confusing

Ok will try it

I will try to create them on the UI and only run the Agent task on argo or so to see if it helps

then share what i found

cat values-prod.yaml
agent:
  api:
    web_server: "

"
    api_server: "

"
    files_server: "

"
    credentials:
      access_key: "8888TMDLWYY7ZQJJ0I7R2X2RSP8XFT"
      secret_key: "oNODbBkDGhcDscTENQyr-GM0cE8IO7xmpaPdqyfsfaWearo1S8EQ8eBOxu-opW8dVUU"