In brand new cluster using k3d locally, I first installed keda:
```bash
helm install keda \
    --namespace keda kedacore/keda \
    --version "v1.5.0"
```

Next, I installed airflow using this config:

```yaml
executor: CeleryExecutor
defaultAirflowTag: 2.0.0-python3.7
airflowVersion: 2.0.0
workers:
  keda:
    enabled: true 
  persistence:
    enabled: false
pgbouncer:
  enabled: true
```

I think this should create a scaled object `airflow-worker`.  

But it does not.

@turbaszek and @dimberman you may have insight ...

chart/tests/helm_template_generator.py
"""
    Helper to create a lookup dict from k8s_objects.
    The keys of the dict are the k8s object's kind and name
    """
    k8s_obj_by_key = {
        (k8s_object["kind"], k8s_object["metadata"]["name"]): k8s_object for k8s_object in k8s_objects
    }
    return k8s_obj_by_key
def render_k8s_object(obj, type_to_render):
    """
    Function that renders dictionaries into k8s objects. For helm chart testing only.
    """
    return api_client._ApiClient__deserialize_model(obj, type_to_render)