diff --git a/awx/main/scheduler/dag_workflow.py b/awx/main/scheduler/dag_workflow.py
index 3f7657f571..924e459929 100644
--- a/awx/main/scheduler/dag_workflow.py
+++ b/awx/main/scheduler/dag_workflow.py
@@ -50,6 +50,7 @@ class WorkflowDAG(SimpleDAG):
         return [n['node_object'] for n in nodes_found]
 
     def cancel_node_jobs(self):
+        cancel_finished = True
         for n in self.nodes:
             obj = n['node_object']
             job = obj.job
@@ -57,7 +58,9 @@ class WorkflowDAG(SimpleDAG):
             if not job:
                 continue
             elif job.can_cancel:
+                cancel_finished = False
                 job.cancel()
+        return cancel_finished
 
     def is_workflow_done(self):
         root_nodes = self.get_root_nodes()
diff --git a/awx/main/scheduler/task_manager.py b/awx/main/scheduler/task_manager.py
index 51c807047a..08cb6cd247 100644
--- a/awx/main/scheduler/task_manager.py
+++ b/awx/main/scheduler/task_manager.py
@@ -103,8 +103,15 @@ class TaskManager():
 
     def spawn_workflow_graph_jobs(self, workflow_jobs):
         for workflow_job in workflow_jobs:
+            if workflow_job.cancel_flag:
+                logger.debug('Not spawning jobs for %s because it is pending cancelation.', workflow_job.log_format)
+                continue
             dag = WorkflowDAG(workflow_job)
             spawn_nodes = dag.bfs_nodes_to_run()
+            if spawn_nodes:
+                logger.info('Spawning jobs for %s', workflow_job.log_format)
+            else:
+                logger.debug('No nodes to spawn for %s', workflow_job.log_format)
             for spawn_node in spawn_nodes:
                 if spawn_node.unified_job_template is None:
                     continue
@@ -112,6 +119,7 @@ class TaskManager():
                 job = spawn_node.unified_job_template.create_unified_job(**kv)
                 spawn_node.job = job
                 spawn_node.save()
+                logger.info('Spawned %s in %s for node %s', job.log_format, workflow_job.log_format, spawn_node.pk)
                 if job._resources_sufficient_for_launch():
                     can_start = job.signal_start()
                     if not can_start:
@@ -129,20 +137,23 @@ class TaskManager():
                 # TODO: should we emit a status on the socket here similar to tasks.py awx_periodic_scheduler() ?
                 #emit_websocket_notification('/socket.io/jobs', '', dict(id=))
 
-    # See comment in tasks.py::RunWorkflowJob::run()
     def process_finished_workflow_jobs(self, workflow_jobs):
         result = []
         for workflow_job in workflow_jobs:
             dag = WorkflowDAG(workflow_job)
             if workflow_job.cancel_flag:
-                workflow_job.status = 'canceled'
-                workflow_job.save()
-                dag.cancel_node_jobs()
-                connection.on_commit(lambda: workflow_job.websocket_emit_status(workflow_job.status))
+                logger.debug('Canceling spawned jobs of %s due to cancel flag.', workflow_job.log_format)
+                cancel_finished = dag.cancel_node_jobs()
+                if cancel_finished:
+                    logger.info('Marking %s as canceled, all spawned jobs have concluded.', workflow_job.log_format)
+                    workflow_job.status = 'canceled'
+                    workflow_job.save()
+                    connection.on_commit(lambda: workflow_job.websocket_emit_status(workflow_job.status))
             else:
                 is_done, has_failed = dag.is_workflow_done()
                 if not is_done:
                     continue
+                logger.info('Marking %s as %s.', workflow_job.log_format, 'failed' if has_failed else 'successful')
                 result.append(workflow_job.id)
                 workflow_job.status = 'failed' if has_failed else 'successful'
                 workflow_job.save()
@@ -499,6 +510,14 @@ class TaskManager():
             running_workflow_tasks = self.get_running_workflow_jobs()
             finished_wfjs = self.process_finished_workflow_jobs(running_workflow_tasks)
 
+            previously_running_workflow_tasks = running_workflow_tasks
+            running_workflow_tasks = []
+            for workflow_job in previously_running_workflow_tasks:
+                if workflow_job.status == 'running':
+                    running_workflow_tasks.append(workflow_job)
+                else:
+                    logger.debug('Removed %s from job spawning consideration.', workflow_job.log_format)
+
             self.spawn_workflow_graph_jobs(running_workflow_tasks)
 
             self.process_tasks(all_sorted_tasks)