Inconsistent pod name with parallelization enabled

[agarwalankitnyu]

Pre-requisites

• I have double-checked my configuration
• I can confirm the issues exists when I tested with :latest
• I'd like to contribute the fix myself (see contributing guide)

What happened/what you expected to happen?

I am noticing some inconsistent behavior for the pod names calculation when using parallelization with v1 POD_NAME spec. I have parallelization enabled to run 5 max workflows at the same time. I submit 20 workflows at the same time, the first 5 calculate pod names for all tasks without the template name(according to v1 spec), after that every workflow that was stuck in the Pending state appends template name to the pod name as well(v2 spec). Argo UI doesn't show this, but when you monitor the pods using kubectl, you can see the name of the pods being created after the initial 5 workflows will have template names appended to it(v2 spec)

Version

3.4.0

Paste a small workflow that reproduces the issue. We must be able to run the workflow; don't enter a workflows that uses private images.

apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: steps-
spec:
  entrypoint: hello-hello-hello

  # This spec contains two templates: hello-hello-hello and whalesay
  templates:
  - name: hello-hello-hello
    # Instead of just running a container
    # This template has a sequence of steps
    steps:
    - - name: hello1            # hello1 is run before the following steps
        template: whalesay
        arguments:
          parameters:
          - name: message
            value: "hello1"
    - - name: hello2a           # double dash => run after previous step
        template: whalesay
        arguments:
          parameters:
          - name: message
            value: "hello2a"
      - name: hello2b           # single dash => run in parallel with previous step
        template: whalesay
        arguments:
          parameters:
          - name: message
            value: "hello2b"

  # This is the same template as from the previous example
  - name: whalesay
    inputs:
      parameters:
      - name: message
    container:
      image: docker/whalesay
      command: [cowsay]
      args: ["{{inputs.parameters.message}}"]

Logs from the workflow controller

kubectl logs -n argo deploy/workflow-controller | grep ${workflow}

Logs from in your workflow's wait container

kubectl logs -n argo -c wait -l workflows.argoproj.io/workflow=${workflow},workflow.argoproj.io/phase!=Succeeded

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. If this is a mentoring request, please provide an update here. Thank you for your contributions.

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. If this is a mentoring request, please provide an update here. Thank you for your contributions.

[rohankmr414]

bump