diff --git a/trains/automation/controller.py b/trains/automation/controller.py
index 12a350c4..40048f94 100644
--- a/trains/automation/controller.py
+++ b/trains/automation/controller.py
@@ -9,7 +9,7 @@ from plotly import graph_objects as go
 from plotly.subplots import make_subplots
 
 from attr import attrib, attrs
-from typing import Sequence, Optional, Mapping, Callable, Any
+from typing import Sequence, Optional, Mapping, Callable, Any, Union
 
 from trains import Task
 from trains.automation import TrainsJob
@@ -159,13 +159,14 @@ class PipelineController(object):
         return True
 
     def start(self, run_remotely=False, step_task_created_callback=None):
-        # type: (bool, Optional[Callable[[PipelineController.Node, dict], None]]) -> bool
+        # type: (Union[bool, str], Optional[Callable[[PipelineController.Node, dict], None]]) -> bool
         """
         Start the pipeline controller.
         If the calling process is stopped, then the controller stops as well.
 
         :param bool run_remotely: (default False), If True stop the current process and continue execution
-            on a remote machine. This is done by calling the Task.execute_remotely with the queue name 'services'
+            on a remote machine. This is done by calling the Task.execute_remotely with the queue name 'services'.
+            If `run_remotely` is a string, it will specify the execution queue for the pipeline remote execution.
         :param Callable step_task_created_callback: Callback function, called when a step (Task) is created
             and before it is sent for execution.
 
@@ -195,10 +196,17 @@ class PipelineController(object):
         if not params['continue_pipeline']:
             for k in pipeline_dag:
                 pipeline_dag[k]['executed'] = None
+
         self._default_execution_queue = params['default_queue']
         self._add_pipeline_tags = params['add_pipeline_tags']
         self._deserialize(pipeline_dag)
 
+        # if we continue the pipeline, make sure that we re-execute failed tasks
+        if params['continue_pipeline']:
+            for node in self._nodes.values():
+                if node.executed is False:
+                    node.executed = None
+
         if not self._verify():
             raise ValueError("Failed verifying pipeline execution graph, "
                              "it has either inaccessible nodes, or contains cycles")
@@ -206,7 +214,7 @@ class PipelineController(object):
         self._update_execution_plot()
 
         if run_remotely:
-            self._task.execute_remotely(queue_name='services')
+            self._task.execute_remotely(queue_name='services' if not isinstance(run_remotely, str) else run_remotely)
             # we will not get here if we are not running remotely
 
         self._start_time = time()
@@ -461,7 +469,7 @@ class PipelineController(object):
                     '<br />'.join('{}: {}'.format(k, v) for k, v in (node.parameters or {}).items()))
                 sankey_node['color'].append(
                     ("blue" if not node.job or not node.job.is_failed() else "red")
-                    if node.executed else ("green" if node.job else "lightsteelblue"))
+                    if node.executed is not None else ("green" if node.job else "lightsteelblue"))
 
                 for p in parents:
                     sankey_link['source'].append(p)
@@ -592,10 +600,16 @@ class PipelineController(object):
                 break
 
         # stop all currently running jobs:
+        failing_pipeline = False
         for node in self._nodes.values():
-            if node.job and not node.executed:
+            if node.executed is False:
+                failing_pipeline = True
+            if node.job and node.executed and not node.job.is_stopped():
                 node.job.abort()
 
+        if failing_pipeline and self._task:
+            self._task.mark_failed(status_reason='Pipeline step failed')
+
         if self._stop_event:
             # noinspection PyBroadException
             try: