Keda does not work properly when using gitSync #44798

Official Helm Chart version

1.15.0 (latest released)

Apache Airflow version

2.10.3

Kubernetes Version

1.31.2

Helm Chart configuration

I have the below section of workers form my values.yaml:

workers:
replicas: 1
keda:
enabled: true
minReplicaCount: 1 # each worker can has 16 celery concurencies
maxReplicaCount: 20
resources:
requests:
cpu: 100m
memory: 1750Mi

Docker Image customizations

No response

What happened

I try to use keda to autoscale my airflow workers which use CeleryKubernetesExecutor.

I followed instruction in https://airflow.apache.org/docs/helm-chart/stable/keda.html to install Keda and change my airflow values.yaml accordingly.

After applying the changes, I observed lots of warning from keda-operator with error message:
"error parsing postgreSQL metadata: error parsing postgresql metadata: no host given"

It seems to me that Keda ScaledObject doesnt work properly.

I checked that:

1. ScaledObject created on correct namespace, same as my airflow namespace
2. It has correct trigger type: postgresql (I use postgres for airflow metadata)
3. it has connectionFromEnv: AIRFLOW_CONN_AIRFLOW_DB

After further investigation, I found that ScaledObject scaleTargetRef has other property called "envSourceContainerName"
as explain in https://keda.sh/docs/2.16/reference/scaledobject-spec/#scaletargetref

The purpose of that property is to tell Keda name of container on which AIRFLOW_CONN_AIRFLOW_DB defined.

If I modify airflow-worker ScaledObject by adding envSourceContainerName: worker into scaleTargetRef, it start working properly.

When I check my airflow-worker StatefulSet, I can see that it has 3 containers: git-sync, worker-log-groomer, and worker.

I'm aware that on the chart template workers/worker-deployment.yaml, worker container is defined as 1st container, but for some reason when I apply the template, worker container is 3rd container in the StatefulSet. I tried deleting airflow-worker StatefulSet and do another helm install with same result.

In my opinion, we cant rely on the position of worker container within the StatefulSet nor Deployment, but we should specify worker container name in ScaledObject scaleTargetRef

What you think should happen instead

Keda autoscaller should work regardless of position of worker container in StatefulSet or Deployment.

How to reproduce

1. Deploy aiflow with git-sync enable
2. Deploy Keda into Kubernetes cluster
3. Configure worker to use keda
4. Observe that ScaledObj has no warning

Anything else

No response

Are you willing to submit PR?

• Yes I am willing to submit a PR!

Code of Conduct

• I agree to follow this project's Code of Conduct