jobs_running not accurate for control nodes

We can either NOT use "idle instances" for control nodes, or we need
to update the jobs_running property on the Instance model to count
jobs where the node is the controller_node.

I didn't do that because it may be an expensive query, and it would be
hard to make it match with jobs_running on the InstanceGroup which
filters on tasks assigned to the instance group.

This change chooses to stop considering "idle" control nodes an option,
since we can't acurrately identify them.

The way things are without any change, is we are continuing to over consume capacity on control nodes
because this method sees all control nodes as "idle" at the beginning
of the task manager run, and then only counts jobs started in that run
in the in-memory tracking. So jobs which last over a number of task
manager runs build up consuming capacity, which is accurately reported
via Instance.consumed_capacity

awx/main/scheduler/task_manager.py

@@ -502,7 +502,7 @@ def process_pending_tasks(self, pending_tasks):
                 control_impact = settings.AWX_CONTROL_NODE_TASK_IMPACT
             control_instance = InstanceGroup.fit_task_to_most_remaining_capacity_instance(
                 task, self.graph[settings.DEFAULT_CONTROL_PLANE_QUEUE_NAME]['instances'], impact=control_impact, capacity_type='control'
-            ) or InstanceGroup.find_largest_idle_instance(self.graph[settings.DEFAULT_CONTROL_PLANE_QUEUE_NAME]['instances'], capacity_type='control')
+            )
             if not control_instance:
                 self.task_needs_capacity(task, tasks_to_update_job_explanation)
                 logger.debug(f"Skipping task {task.log_format} in pending, not enough capacity left on controlplane to control new tasks")