This tutorial focuses on boto's interface to AWS SimpleWorkflow service.
A workflow is a sequence of multiple activities aimed at accomplishing a well-defined objective. For instance, booking an airline ticket as a workflow may encompass multiple activities, such as selection of itinerary, submission of personal details, payment validation and booking confirmation.
- Except for the start and completion of a workflow, each step has a well-defined predecessor and successor. With that
- on successful completion of an activity the workflow can progress with its execution,
- when one of workflow's activities fails it can be retried,
- and when it keeps failing repeatedly the workflow may regress to the previous step to gather alternative inputs or it may simply fail at that stage.
Modelling an application on a workflow provides a useful abstraction layer for writing highly-reliable programs for distributed systems, as individual responsibilities can be delegated to a set of redundant, independent and non-critical processing units.
Amazon SimpleWorkflow service defines an interface for workflow orchestration and provides state persistence for workflow executions.
- Amazon SWF applications involve communication between the following entities:
- The Amazon Simple Workflow Service - providing centralized orchestration and workflow state persistence,
- Workflow Executors - some entity starting workflow executions, typically through an action taken by a user or from a cronjob.
- Deciders - a program codifying the business logic, i.e. a set of instructions and decisions. Deciders take decisions based on initial set of conditions and outcomes from activities.
- Activity Workers - their objective is very straightforward: to take inputs, execute the tasks and return a result to the Service.
The Workflow Executor contacts SWF Service and requests instantiation of a workflow. A new workflow is created and its state is stored in the service. The next time a decider contacts SWF service to ask for a decision task, it will be informed about a new workflow execution is taking place and it will be asked to advise SWF service on what the next steps should be. The decider then instructs the service to dispatch specific tasks to activity workers. At the next activity worker poll, the task is dispatched, then executed and the results reported back to the SWF, which then passes them onto the deciders. This exchange keeps happening repeatedly until the decider is satisfied and instructs the service to complete the execution.
You need a valid access and secret key. The examples below assume that you have exported them to your environment, as follows:
bash$ export AWS_ACCESS_KEY_ID=<your access key>
bash$ export AWS_SECRET_ACCESS_KEY=<your secret key>Before workflows and activities can be used, they have to be registered with SWF service:
# register.py
import boto.swf.layer2 as swf
from boto.swf.exceptions import SWFTypeAlreadyExistsError, SWFDomainAlreadyExistsError
DOMAIN = 'boto_tutorial'
VERSION = '1.0'
registerables = []
registerables.append(swf.Domain(name=DOMAIN))
registerables.append(swf.WorkflowType(domain=DOMAIN, name='HelloWorkflow', version=VERSION, task_list='default'))
registerables.append(swf.WorkflowType(domain=DOMAIN, name='SerialWorkflow', version=VERSION, task_list='default'))
for activity_type in ('HelloWorld', 'ActivityA', 'ActivityB', 'ActivityC'):
registerables.append(swf.ActivityType(domain=DOMAIN, name=activity_type, version=VERSION, task_list='default'))
for swf_entity in registerables:
try:
swf_entity.register()
print swf_entity.name, 'registered successfully'
except (SWFDomainAlreadyExistsError, SWFTypeAlreadyExistsError):
print swf_entity.__class__.__name__, swf_entity.name, 'already exists'Execution of the above should produce no errors.
bash$ python -i register.py
Domain boto_tutorial already exists
WorkflowType HelloWorkflow already exists
SerialWorkflow registered successfully
ActivityType HelloWorld already exists
ActivityA registered successfully
ActivityB registered successfully
ActivityC registered successfully
>>> This example is an implementation of a minimal Hello World workflow. Its execution should unfold as follows:
- A workflow execution is started.
- The SWF service schedules the initial decision task.
- A decider polls for decision tasks and receives one.
- The decider requests scheduling of an activity task.
- The SWF service schedules the greeting activity task.
- An activity worker polls for activity task and receives one.
- The worker completes the greeting activity.
- The SWF service schedules a decision task to inform about work outcome.
- The decider polls and receives a new decision task.
- The decider schedules workflow completion.
- The workflow execution finishes.
Workflow logic is encoded in the decider:
# hello_decider.py
import boto.swf.layer2 as swf
DOMAIN = 'boto_tutorial'
ACTIVITY = 'HelloWorld'
VERSION = '1.0'
TASKLIST = 'default'
class HelloDecider(swf.Decider):
domain = DOMAIN
task_list = TASKLIST
version = VERSION
def run(self):
history = self.poll()
if 'events' in history:
# Find workflow events not related to decision scheduling.
workflow_events = [e for e in history['events']
if not e['eventType'].startswith('Decision')]
last_event = workflow_events[-1]
decisions = swf.Layer1Decisions()
if last_event['eventType'] == 'WorkflowExecutionStarted':
decisions.schedule_activity_task('saying_hi', ACTIVITY, VERSION, task_list=TASKLIST)
elif last_event['eventType'] == 'ActivityTaskCompleted':
decisions.complete_workflow_execution()
self.complete(decisions=decisions)
return True The activity worker is responsible for printing the greeting message when the activity task is dispatched to it by the service:
import boto.swf.layer2 as swf
DOMAIN = 'boto_tutorial'
VERSION = '1.0'
TASKLIST = 'default'
class HelloWorker(swf.ActivityWorker):
domain = DOMAIN
version = VERSION
task_list = TASKLIST
def run(self):
activity_task = self.poll()
if 'activityId' in activity_task:
print 'Hello, World!'
self.complete()
return TrueWith actors implemented we can spin up a workflow execution:
$ python
>>> import boto.swf.layer2 as swf
>>> execution = swf.WorkflowType(name='HelloWorkflow', domain='boto_tutorial', version='1.0', task_list='default').start()
>>> From separate terminals run an instance of a worker and a decider to carry out a workflow execution (the worker and decider may run from two independent machines).
$ python -i hello_decider.py
>>> while HelloDecider().run(): pass
... $ python -i hello_worker.py
>>> while HelloWorker().run(): pass
...
Hello, World!Great. Now, to see what just happened, go back to the original terminal from which the execution was started, and read its history.
>>> execution.history()
[{'eventId': 1,
'eventTimestamp': 1381095173.2539999,
'eventType': 'WorkflowExecutionStarted',
'workflowExecutionStartedEventAttributes': {'childPolicy': 'TERMINATE',
'executionStartToCloseTimeout': '3600',
'parentInitiatedEventId': 0,
'taskList': {'name': 'default'},
'taskStartToCloseTimeout': '300',
'workflowType': {'name': 'HelloWorkflow',
'version': '1.0'}}},
{'decisionTaskScheduledEventAttributes': {'startToCloseTimeout': '300',
'taskList': {'name': 'default'}},
'eventId': 2,
'eventTimestamp': 1381095173.2539999,
'eventType': 'DecisionTaskScheduled'},
{'decisionTaskStartedEventAttributes': {'scheduledEventId': 2},
'eventId': 3,
'eventTimestamp': 1381095177.5439999,
'eventType': 'DecisionTaskStarted'},
{'decisionTaskCompletedEventAttributes': {'scheduledEventId': 2,
'startedEventId': 3},
'eventId': 4,
'eventTimestamp': 1381095177.855,
'eventType': 'DecisionTaskCompleted'},
{'activityTaskScheduledEventAttributes': {'activityId': 'saying_hi',
'activityType': {'name': 'HelloWorld',
'version': '1.0'},
'decisionTaskCompletedEventId': 4,
'heartbeatTimeout': '600',
'scheduleToCloseTimeout': '3900',
'scheduleToStartTimeout': '300',
'startToCloseTimeout': '3600',
'taskList': {'name': 'default'}},
'eventId': 5,
'eventTimestamp': 1381095177.855,
'eventType': 'ActivityTaskScheduled'},
{'activityTaskStartedEventAttributes': {'scheduledEventId': 5},
'eventId': 6,
'eventTimestamp': 1381095179.427,
'eventType': 'ActivityTaskStarted'},
{'activityTaskCompletedEventAttributes': {'scheduledEventId': 5,
'startedEventId': 6},
'eventId': 7,
'eventTimestamp': 1381095179.6989999,
'eventType': 'ActivityTaskCompleted'},
{'decisionTaskScheduledEventAttributes': {'startToCloseTimeout': '300',
'taskList': {'name': 'default'}},
'eventId': 8,
'eventTimestamp': 1381095179.6989999,
'eventType': 'DecisionTaskScheduled'},
{'decisionTaskStartedEventAttributes': {'scheduledEventId': 8},
'eventId': 9,
'eventTimestamp': 1381095179.7420001,
'eventType': 'DecisionTaskStarted'},
{'decisionTaskCompletedEventAttributes': {'scheduledEventId': 8,
'startedEventId': 9},
'eventId': 10,
'eventTimestamp': 1381095180.026,
'eventType': 'DecisionTaskCompleted'},
{'eventId': 11,
'eventTimestamp': 1381095180.026,
'eventType': 'WorkflowExecutionCompleted',
'workflowExecutionCompletedEventAttributes': {'decisionTaskCompletedEventId': 10}}]The following example implements a basic workflow with activities executed one after another.
The business logic, i.e. the serial execution of activities, is encoded in the decider:
# serial_decider.py
import time
import boto.swf.layer2 as swf
class SerialDecider(swf.Decider):
domain = 'boto_tutorial'
task_list = 'default_tasks'
version = '1.0'
def run(self):
history = self.poll()
if 'events' in history:
# Get a list of non-decision events to see what event came in last.
workflow_events = [e for e in history['events']
if not e['eventType'].startswith('Decision')]
decisions = swf.Layer1Decisions()
# Record latest non-decision event.
last_event = workflow_events[-1]
last_event_type = last_event['eventType']
if last_event_type == 'WorkflowExecutionStarted':
# Schedule the first activity.
decisions.schedule_activity_task('%s-%i' % ('ActivityA', time.time()),
'ActivityA', self.version, task_list='a_tasks')
elif last_event_type == 'ActivityTaskCompleted':
# Take decision based on the name of activity that has just completed.
# 1) Get activity's event id.
last_event_attrs = last_event['activityTaskCompletedEventAttributes']
completed_activity_id = last_event_attrs['scheduledEventId'] - 1
# 2) Extract its name.
activity_data = history['events'][completed_activity_id]
activity_attrs = activity_data['activityTaskScheduledEventAttributes']
activity_name = activity_attrs['activityType']['name']
# 3) Optionally, get the result from the activity.
result = last_event['activityTaskCompletedEventAttributes'].get('result')
# Take the decision.
if activity_name == 'ActivityA':
decisions.schedule_activity_task('%s-%i' % ('ActivityB', time.time()),
'ActivityB', self.version, task_list='b_tasks', input=result)
if activity_name == 'ActivityB':
decisions.schedule_activity_task('%s-%i' % ('ActivityC', time.time()),
'ActivityC', self.version, task_list='c_tasks', input=result)
elif activity_name == 'ActivityC':
# Final activity completed. We're done.
decisions.complete_workflow_execution()
self.complete(decisions=decisions)
return TrueThe workers only need to know which task lists to poll.
# serial_worker.py
import time
import boto.swf.layer2 as swf
class MyBaseWorker(swf.ActivityWorker):
domain = 'boto_tutorial'
version = '1.0'
task_list = None
def run(self):
activity_task = self.poll()
if 'activityId' in activity_task:
# Get input.
# Get the method for the requested activity.
try:
print 'working on activity from tasklist %s at %i' % (self.task_list, time.time())
self.activity(activity_task.get('input'))
except Exception, error:
self.fail(reason=str(error))
raise error
return True
def activity(self, activity_input):
raise NotImplementedError
class WorkerA(MyBaseWorker):
task_list = 'a_tasks'
def activity(self, activity_input):
self.complete(result="Now don't be givin him sambuca!")
class WorkerB(MyBaseWorker):
task_list = 'b_tasks'
def activity(self, activity_input):
self.complete()
class WorkerC(MyBaseWorker):
task_list = 'c_tasks'
def activity(self, activity_input):
self.complete()Spin up a workflow execution and run the decider:
$ python
>>> import boto.swf.layer2 as swf
>>> execution = swf.WorkflowType(name='SerialWorkflow', domain='boto_tutorial', version='1.0', task_list='default_tasks').start()
>>> $ python -i serial_decider.py
>>> while SerialDecider().run(): pass
... Run the workers. The activities will be executed in order:
$ python -i serial_worker.py
>>> while WorkerA().run(): pass
...
working on activity from tasklist a_tasks at 1382046291$ python -i serial_worker.py
>>> while WorkerB().run(): pass
...
working on activity from tasklist b_tasks at 1382046541$ python -i serial_worker.py
>>> while WorkerC().run(): pass
...
working on activity from tasklist c_tasks at 1382046560Looks good. Now, do the following to inspect the state and history of the execution:
>>> execution.describe()
{'executionConfiguration': {'childPolicy': 'TERMINATE',
'executionStartToCloseTimeout': '3600',
'taskList': {'name': 'default_tasks'},
'taskStartToCloseTimeout': '300'},
'executionInfo': {'cancelRequested': False,
'closeStatus': 'COMPLETED',
'closeTimestamp': 1382046560.901,
'execution': {'runId': '12fQ1zSaLmI5+lLXB8ux+8U+hLOnnXNZCY9Zy+ZvXgzhE=',
'workflowId': 'SerialWorkflow-1.0-1382046514'},
'executionStatus': 'CLOSED',
'startTimestamp': 1382046514.994,
'workflowType': {'name': 'SerialWorkflow', 'version': '1.0'}},
'latestActivityTaskTimestamp': 1382046560.632,
'openCounts': {'openActivityTasks': 0,
'openChildWorkflowExecutions': 0,
'openDecisionTasks': 0,
'openTimers': 0}}
>>> execution.history()
...