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Commit a57b52c1 by Calen Pennington
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Combine local_task_timing.py into task_timing.py

parent 1cc0fc7f
Showing with 85 additions and 137 deletions
playbooks/callback_plugins/local_task_timing.py deleted 100644 → 0
import json
import os
from os.path import exists, dirname, splitext, basename
from datetime import datetime
"""
Originally written by 'Jharrod LaFon'
#https://github.com/jlafon/ansible-profile/blob/master/callback_plugins/profile_tasks.py
"""
ANSIBLE_TIMER_LOG = os.environ.get('ANSIBLE_TIMER_LOG')
class Timestamp(object):
def __init__(self):
self.start = datetime.utcnow()
self.end = None
def stop(self):
self.end = datetime.utcnow()
@property
def duration(self):
return self.end - self.start
class CallbackModule(object):
"""
Ansible plugin get the time of each task and total time
to run the complete playbook
"""
def __init__(self):
self.stats = {}
self.current_task = None
self.playbook_name = None
self.playbook_start = None
self.playbook_end = None
def playbook_on_play_start(self, pattern):
self.playbook_name, _ = splitext(
basename(self.play.playbook.filename)
)
self.playbook_start = datetime.utcnow()
def playbook_on_task_start(self, name, is_conditional):
"""
Logs the start of each task
"""
if self.current_task is not None:
# Record the running time of the last executed task
self.stats[self.current_task].stop()
# Record the start time of the current task
self.current_task = name
self.stats[self.current_task] = Timestamp()
def playbook_on_stats(self, stats):
"""
Prints the timing of each task and total time to
run the complete playbook
"""
# Record the timing of the very last task, we use it here, because we
# don't have stop task function by default
if self.current_task is not None:
self.stats[self.current_task].stop()
self.playbook_end = datetime.utcnow()
# Sort the tasks by their running time
results = sorted(
self.stats.items(),
key=lambda (task, timestamp): timestamp.duration,
reverse=True
)
# log the stats
# N.B. This is intended to provide a consistent interface and message format
# across all of Open edX tooling, so it deliberately eschews standard
# python logging infrastructure.
if ANSIBLE_TIMER_LOG is not None:
log_path = self.playbook_start.strftime(ANSIBLE_TIMER_LOG)
if not exists(dirname(log_path)):
os.makedirs(dirname(log_path))
with open(log_path, 'a') as outfile:
for name, timestamp in results:
log_message = {
'task': name,
'playbook': self.playbook_name,
'started_at': timestamp.start.isoformat(),
'ended_at': timestamp.end.isoformat(),
'duration': timestamp.duration.total_seconds(),
}
json.dump(
log_message,
outfile,
separators=(',', ':'),
sort_keys=True,
)
outfile.write('\n')
log_message = {
'playbook': self.playbook_name,
'started_at': self.playbook_start.isoformat(),
'ended_at': self.playbook_end.isoformat(),
'duration': (self.playbook_end - self.playbook_start).total_seconds(),
}
json.dump(
log_message,
outfile,
separators=(',', ':'),
sort_keys=True,
)
outfile.write('\n')
playbooks/callback_plugins/task_timing.py
import os
import datetime
from os.path import splitext, basename, exists, dirname
from datetime import datetime, timedelta
import json
import time
import logging
import datadog
......@@ -16,6 +18,22 @@ Originally written by 'Jharrod LaFon'
"""
ANSIBLE_TIMER_LOG = os.environ.get('ANSIBLE_TIMER_LOG')
class Timestamp(object):
def __init__(self):
self.start = datetime.utcnow()
self.end = None
def stop(self):
self.end = datetime.utcnow()
@property
def duration(self):
return self.end - self.start
class CallbackModule(object):
......@@ -27,6 +45,8 @@ class CallbackModule(object):
self.stats = {}
self.current_task = None
self.playbook_name = None
self.playbook_start = None
self.playbook_end = None
self.datadog_api_key = os.getenv('DATADOG_API_KEY')
self.datadog_api_initialized = False
......@@ -41,9 +61,10 @@ class CallbackModule(object):
return value.replace(" | ", ".").replace(" ", "-").lower()
def playbook_on_play_start(self, pattern):
self.playbook_name, _ = os.path.splitext(
os.path.basename(self.play.playbook.filename)
self.playbook_name, _ = splitext(
basename(self.play.playbook.filename)
)
self.playbook_start = datetime.utcnow()
def playbook_on_task_start(self, name, is_conditional):
"""
......@@ -52,20 +73,20 @@ class CallbackModule(object):
if self.current_task is not None:
# Record the running time of the last executed task
self.stats[self.current_task] = (time.time(), time.time() - self.stats[self.current_task])
self.stats[self.current_task].stop()
# Record the start time of the current task
self.current_task = name
self.stats[self.current_task] = time.time()
self.stats[self.current_task] = Timestamp()
def _datadog_log_tasks(self, playbook_name, results):
if self.datadog_api_initialized:
datadog_tasks_metrics = []
for name, points in results:
for name, timestamp in results:
datadog_tasks_metrics.append({
'metric': 'edx.ansible.task_duration',
'date_happened': points[0],
'points': points[1],
'date_happened': timestamp.start,
'points': timestamp.duration.total_seconds(),
'tags': [
'task:{0}'.format(self.clean_tag_value(name)),
'playbook:{0}'.format(self.clean_tag_value(playbook_name))
......@@ -89,11 +110,11 @@ class CallbackModule(object):
logger.error(ex.message)
def _logger_log_tasks(self, playbook_name, results):
for name, elapsed in results[:10]:
for name, timestamp in results[:10]:
logger.info(
"{0:-<80}{1:->8}".format(
'{0} '.format(name),
' {0:.02f}s'.format(elapsed[1]),
' {0:.02f}s'.format(timestamp.duration.total_seconds()),
)
)
......@@ -102,7 +123,7 @@ class CallbackModule(object):
playbook_name,
time.asctime(),
task_count,
datetime.timedelta(seconds=(int(duration)))
timedelta(seconds=(int(duration)))
))
def playbook_on_stats(self, stats):
......@@ -113,14 +134,62 @@ class CallbackModule(object):
# Record the timing of the very last task, we use it here, because we
# don't have stop task function by default
if self.current_task is not None:
self.stats[self.current_task] = (time.time(), time.time() - self.stats[self.current_task])
self.stats[self.current_task].stop()
self.playbook_end = datetime.utcnow()
# Sort the tasks by their running time
results = sorted(self.stats.items(),
key=lambda value: value[1][1], reverse=True)
results = sorted(
self.stats.items(),
key=lambda (task, timestamp): timestamp.duration,
reverse=True
)
# log the stats
# N.B. This is intended to provide a consistent interface and message format
# across all of Open edX tooling, so it deliberately eschews standard
# python logging infrastructure.
if ANSIBLE_TIMER_LOG is not None:
log_path = self.playbook_start.strftime(ANSIBLE_TIMER_LOG)
if not exists(dirname(log_path)):
os.makedirs(dirname(log_path))
with open(log_path, 'a') as outfile:
for name, timestamp in results:
log_message = {
'task': name,
'playbook': self.playbook_name,
'started_at': timestamp.start.isoformat(),
'ended_at': timestamp.end.isoformat(),
'duration': timestamp.duration.total_seconds(),
}
json.dump(
log_message,
outfile,
separators=(',', ':'),
sort_keys=True,
)
outfile.write('\n')
log_message = {
'playbook': self.playbook_name,
'started_at': self.playbook_start.isoformat(),
'ended_at': self.playbook_end.isoformat(),
'duration': (self.playbook_end - self.playbook_start).total_seconds(),
}
json.dump(
log_message,
outfile,
separators=(',', ':'),
sort_keys=True,
)
outfile.write('\n')
# Total time to run the complete playbook
total_seconds = sum([x[1][1] for x in self.stats.items()])
total_seconds = (self.playbook_end - self.playbook_start).total_seconds()
# send the metric to datadog
self._datadog_log_tasks(self.playbook_name, results)
......
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