def test_multiple_msg(self):
"""
Multiple messages are logged when there are multiple log effects
"""
eff = msg("yo", a="b").on(lambda _: msg("goo", d="c"))
self.assertIsNone(sync_perform(self.disp, eff))
self.log.msg.assert_has_calls([mock.call("yo", f1="v", a="b"), mock.call("goo", f1="v", d="c")])
def test_multiple_msg(self):
"""
Multiple messages are logged when there are multiple log effects
"""
eff = msg("yo", a='b').on(lambda _: msg("goo", d='c'))
self.assertIsNone(sync_perform(self.disp, eff))
self.log.msg.assert_has_calls(
[mock.call("yo", f1='v', a='b'),
mock.call("goo", f1='v', d='c')])
def trigger_convergence(tenant_id, group_id):
"""
Trigger convergence on a scaling group
"""
eff = mark_divergent(tenant_id, group_id)
return eff.on(success=lambda _: msg("mark-dirty-success"),
error=log_and_raise("mark-dirty-failure"))
def test_nested_msg(self):
"""
message is logged when nested inside other effects
"""
eff = Effect(Constant("foo")).on(lambda _: msg("yo", a="b")).on(lambda _: Effect(Constant("goo")))
self.assertEqual(sync_perform(self.disp, eff), "goo")
self.log.msg.assert_called_once_with("yo", f1="v", a="b")
def test_msg(self):
"""
message is logged with original field
"""
r = sync_perform(self.disp, msg("yo!"))
self.assertIsNone(r)
self.log.msg.assert_called_once_with("yo!", f1='v')
def _execute_steps(steps):
"""
Given a set of steps, executes them, logs the result, and returns the worst
priority with a list of reasons for that result.
:return: a tuple of (:class:`StepResult` constant,
list of :obj:`ErrorReason`)
"""
if len(steps) > 0:
results = yield steps_to_effect(steps)
severity = [StepResult.FAILURE, StepResult.RETRY,
StepResult.LIMITED_RETRY, StepResult.SUCCESS]
priority = sorted(results,
key=lambda (status, reasons): severity.index(status))
worst_status = priority[0][0]
results_to_log = [
{'step': step,
'result': result,
'reasons': map(structure_reason, reasons)}
for step, (result, reasons) in
zip(steps, results)
]
reasons = reduce(operator.add,
(x[1] for x in results if x[0] == worst_status))
else:
worst_status = StepResult.SUCCESS
results_to_log = reasons = []
yield msg('execute-convergence-results',
results=results_to_log,
worst_status=worst_status.name)
yield do_return((worst_status, reasons))
def test_msg_with_params(self):
"""
message is logged with its fields combined
"""
r = sync_perform(self.disp, msg("yo!", a='b'))
self.assertIsNone(r)
self.log.msg.assert_called_once_with("yo!", f1='v', a='b')
def test_msg(self):
"""
message is logged with original field
"""
r = sync_perform(self.disp, msg("yo!"))
self.assertIsNone(r)
self.log.msg.assert_called_once_with("yo!", f1='v')
def test_msg_with_params(self):
"""
message is logged with its fields combined
"""
r = sync_perform(self.disp, msg("yo!", a='b'))
self.assertIsNone(r)
self.log.msg.assert_called_once_with("yo!", f1='v', a='b')
def _execute_steps(steps):
"""
Given a set of steps, executes them, logs the result, and returns the worst
priority with a list of reasons for that result.
:return: a tuple of (:class:`StepResult` constant., list of reasons)
"""
if len(steps) > 0:
results = yield steps_to_effect(steps)
severity = [
StepResult.FAILURE, StepResult.RETRY, StepResult.LIMITED_RETRY,
StepResult.SUCCESS
]
priority = sorted(results,
key=lambda (status, reasons): severity.index(status))
worst_status = priority[0][0]
results_to_log = [{
'step': step,
'result': result,
'reasons': map(structure_reason, reasons)
} for step, (result, reasons) in zip(steps, results)]
reasons = reduce(operator.add,
(x[1] for x in results if x[0] == worst_status))
else:
worst_status = StepResult.SUCCESS
results_to_log = reasons = []
yield msg('execute-convergence-results',
results=results_to_log,
worst_status=worst_status.name)
yield do_return((worst_status, reasons))
def trigger_convergence(tenant_id, group_id):
"""
Trigger convergence on a scaling group
"""
eff = mark_divergent(tenant_id, group_id)
return eff.on(success=lambda _: msg("mark-dirty-success"),
error=log_and_raise("mark-dirty-failure"))
def test_nested_msg(self):
"""
message is logged when nested inside other effects
"""
eff = Effect(Constant("foo")).on(lambda _: msg("yo", a='b')).on(
lambda _: Effect(Constant("goo")))
self.assertEqual(sync_perform(self.disp, eff), "goo")
self.log.msg.assert_called_once_with("yo", f1='v', a='b')
def test_nested_boundfields(self):
"""
BoundFields effects can be nested and the log effects internally
will expand with all bound fields
"""
eff = Effect(Constant("foo")).on(lambda _: msg("foo", m="d")).on(lambda _: Effect(Constant("goo")))
e = Effect(Constant("abc")).on(lambda _: with_log(eff, i="a")).on(lambda _: Effect(Constant("def")))
self.assertEqual(sync_perform(self.disp, with_log(e, o="f")), "def")
self.log.msg.assert_called_once_with("foo", i="a", f1="v", m="d", o="f")
def conv_resume_group_eff(trans_id, group):
"""
Resume scaling group of convergence enabled tenant
"""
eff = parallel([
Effect(ModifyGroupStatePaused(group, False)),
mark_divergent(group.tenant_id, group.uuid).on(
lambda _: msg("mark-dirty-success"))])
return with_log(eff, transaction_id=trans_id, tenant_id=group.tenant_id,
scaling_group_id=group.uuid).on(lambda _: None)
def test_boundfields(self):
"""
When an effect is wrapped `BoundFields` then any logging effect
inside is performed with fields setup in `BoundFields`
"""
f = object()
eff = Effect(Constant("foo")).on(lambda _: err(f, "yo", a='b')).on(
lambda _: msg("foo", m='d')).on(lambda _: Effect(Constant("goo")))
eff = with_log(eff, bf='new')
self.assertEqual(sync_perform(self.disp, eff), "goo")
self.log.msg.assert_called_once_with("foo", f1='v', bf='new', m='d')
self.log.err.assert_called_once_with(f, "yo", f1='v', bf='new', a='b')
def conv_resume_group_eff(trans_id, group):
"""
Resume scaling group of convergence enabled tenant
"""
eff = parallel([
Effect(ModifyGroupStatePaused(group, False)),
mark_divergent(group.tenant_id,
group.uuid).on(lambda _: msg("mark-dirty-success"))
])
return with_log(eff,
transaction_id=trans_id,
tenant_id=group.tenant_id,
scaling_group_id=group.uuid).on(lambda _: None)
def delete_divergent_flag(tenant_id, group_id, version):
"""
Delete the dirty flag, if its version hasn't changed. See note [Divergent
flags] for more info.
:return: Effect of None.
"""
flag = format_dirty_flag(tenant_id, group_id)
path = CONVERGENCE_DIRTY_DIR + '/' + flag
fields = dict(path=path, dirty_version=version)
try:
yield Effect(DeleteNode(path=path, version=version))
except BadVersionError:
# BadVersionError shouldn't be logged as an error because it's an
# expected occurrence any time convergence is requested multiple times
# rapidly.
yield msg('mark-clean-skipped', **fields)
except NoNodeError:
yield msg('mark-clean-not-found', **fields)
except Exception:
yield err(None, 'mark-clean-failure', **fields)
else:
yield msg('mark-clean-success')
def test_boundfields(self):
"""
When an effect is wrapped `BoundFields` then any logging effect
inside is performed with fields setup in `BoundFields`
"""
f = object()
eff = Effect(Constant("foo")).on(
lambda _: err(f, "yo", a='b')).on(
lambda _: msg("foo", m='d')).on(
lambda _: Effect(Constant("goo")))
eff = with_log(eff, bf='new')
self.assertEqual(sync_perform(self.disp, eff), "goo")
self.log.msg.assert_called_once_with("foo", f1='v', bf='new', m='d')
self.log.err.assert_called_once_with(f, "yo", f1='v', bf='new', a='b')
def delete_divergent_flag(tenant_id, group_id, version):
"""
Delete the dirty flag, if its version hasn't changed. See note [Divergent
flags] for more info.
:return: Effect of None.
"""
flag = format_dirty_flag(tenant_id, group_id)
path = CONVERGENCE_DIRTY_DIR + '/' + flag
fields = dict(path=path, dirty_version=version)
try:
yield Effect(DeleteNode(path=path, version=version))
except BadVersionError:
# BadVersionError shouldn't be logged as an error because it's an
# expected occurrence any time convergence is requested multiple times
# rapidly.
yield msg('mark-clean-skipped', **fields)
except NoNodeError:
yield msg('mark-clean-not-found', **fields)
except Exception:
yield err(None, 'mark-clean-failure', **fields)
else:
yield msg('mark-clean-success')
def test_nested_boundfields(self):
"""
BoundFields effects can be nested and the log effects internally
will expand with all bound fields
"""
eff = Effect(Constant("foo")).on(lambda _: msg("foo", m='d')).on(
lambda _: Effect(Constant("goo")))
e = Effect(Constant("abc")).on(lambda _: with_log(eff, i='a')).on(
lambda _: Effect(Constant("def")))
self.assertEqual(sync_perform(self.disp, with_log(e, o='f')), "def")
self.log.msg.assert_called_once_with('foo',
i='a',
f1='v',
m='d',
o='f')
def converge(tenant_id, group_id, dirty_flag):
stat = yield Effect(GetStat(dirty_flag))
# If the node disappeared, ignore it. `stat` will be None here if the
# divergent flag was discovered only after the group is removed from
# currently_converging, but before the divergent flag is deleted, and
# then the deletion happens, and then our GetStat happens. This
# basically means it happens when one convergence is starting as
# another one for the same group is ending.
if stat is None:
yield msg('converge-divergent-flag-disappeared', znode=dirty_flag)
else:
eff = converge_one_group(currently_converging, recently_converged,
waiting, tenant_id, group_id,
stat.version, build_timeout,
limited_retry_iterations, step_limits)
result = yield Effect(TenantScope(eff, tenant_id))
yield do_return(result)
def check_and_trigger(tenant_id, group_id):
"""
Trigger convergence on given group if it is ACTIVE and not paused
"""
try:
group, info = yield Effect(
GetScalingGroupInfo(tenant_id=tenant_id, group_id=group_id))
except NoSuchScalingGroupError:
# Nothing to do if group has been deleted
yield msg("selfheal-group-deleted",
tenant_id=tenant_id, scaling_group_id=group_id)
else:
state = info["state"]
if state.status == ScalingGroupStatus.ACTIVE and (not state.paused):
yield with_log(
trigger_convergence(tenant_id, group_id),
tenant_id=tenant_id, scaling_group_id=group_id)
def converge(tenant_id, group_id, dirty_flag):
stat = yield Effect(GetStat(dirty_flag))
# If the node disappeared, ignore it. `stat` will be None here if the
# divergent flag was discovered only after the group is removed from
# currently_converging, but before the divergent flag is deleted, and
# then the deletion happens, and then our GetStat happens. This
# basically means it happens when one convergence is starting as
# another one for the same group is ending.
if stat is None:
yield msg('converge-divergent-flag-disappeared', znode=dirty_flag)
else:
eff = converge_one_group(currently_converging, recently_converged,
waiting,
tenant_id, group_id,
stat.version, build_timeout,
limited_retry_iterations, step_limits)
result = yield Effect(TenantScope(eff, tenant_id))
yield do_return(result)
def check_and_trigger(tenant_id, group_id):
"""
Trigger convergence on given group if it is ACTIVE and not paused
"""
try:
group, info = yield Effect(
GetScalingGroupInfo(tenant_id=tenant_id, group_id=group_id))
except NoSuchScalingGroupError:
# Nothing to do if group has been deleted
yield msg("selfheal-group-deleted",
tenant_id=tenant_id,
scaling_group_id=group_id)
else:
state = info["state"]
if (state.status == ScalingGroupStatus.ACTIVE
and not (state.paused or state.suspended)):
yield with_log(trigger_convergence(tenant_id, group_id),
tenant_id=tenant_id,
scaling_group_id=group_id)
def converge_all_groups(currently_converging,
recently_converged,
waiting,
my_buckets,
all_buckets,
divergent_flags,
build_timeout,
interval,
limited_retry_iterations,
step_limits,
converge_one_group=converge_one_group):
"""
Check for groups that need convergence and which match up to the
buckets we've been allocated.
:param Reference currently_converging: pset of currently converging groups
:param Reference recently_converged: pmap of group ID to time last
convergence finished
:param Reference waiting: pmap of group ID to number of iterations already
waited
:param my_buckets: The buckets that should be checked for group IDs to
converge on.
:param all_buckets: The set of all buckets that can be checked for group
IDs to converge on. ``my_buckets`` should be a subset of this.
:param divergent_flags: divergent flags that were found in zookeeper.
:param number build_timeout: number of seconds to wait for servers to be in
building before it's is timed out and deleted
:param number interval: number of seconds between attempts at convergence.
Groups will not be converged if less than this amount of time has
passed since the end of its last convergence.
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step class to number of executions
allowed in a convergence cycle
:param callable converge_one_group: function to use to converge a single
group - to be used for test injection only
"""
group_infos = get_my_divergent_groups(my_buckets, all_buckets,
divergent_flags)
# filter out currently converging groups
cc = yield currently_converging.read()
group_infos = [info for info in group_infos if info['group_id'] not in cc]
if not group_infos:
return
yield msg('converge-all-groups',
group_infos=group_infos,
currently_converging=list(cc))
@do
def converge(tenant_id, group_id, dirty_flag):
stat = yield Effect(GetStat(dirty_flag))
# If the node disappeared, ignore it. `stat` will be None here if the
# divergent flag was discovered only after the group is removed from
# currently_converging, but before the divergent flag is deleted, and
# then the deletion happens, and then our GetStat happens. This
# basically means it happens when one convergence is starting as
# another one for the same group is ending.
if stat is None:
yield msg('converge-divergent-flag-disappeared', znode=dirty_flag)
else:
eff = converge_one_group(currently_converging, recently_converged,
waiting, tenant_id, group_id,
stat.version, build_timeout,
limited_retry_iterations, step_limits)
result = yield Effect(TenantScope(eff, tenant_id))
yield do_return(result)
recent_groups = yield get_recently_converged_groups(
recently_converged, interval)
effs = []
for info in group_infos:
tenant_id, group_id = info['tenant_id'], info['group_id']
if group_id in recent_groups:
# Don't converge a group if it has recently been converged.
continue
eff = converge(tenant_id, group_id, info['dirty-flag'])
effs.append(
with_log(eff, tenant_id=tenant_id, scaling_group_id=group_id))
yield do_return(parallel(effs))
def execute_convergence(tenant_id,
group_id,
build_timeout,
waiting,
limited_retry_iterations,
step_limits,
get_executor=get_executor):
"""
Gather data, plan a convergence, save active and pending servers to the
group state, and then execute the convergence.
:param str tenant_id: the tenant ID for the group to converge
:param str group_id: the ID of the group to be converged
:param number build_timeout: number of seconds to wait for servers to be in
building before it's is timed out and deleted
:param Reference waiting: pmap of waiting groups
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step class to number of executions
allowed in a convergence cycle
:param callable get_executor: like :func`get_executor`, used for testing.
:return: Effect of :obj:`ConvergenceIterationStatus`.
:raise: :obj:`NoSuchScalingGroupError` if the group doesn't exist.
"""
clean_waiting = _clean_waiting(waiting, group_id)
# Gather data
yield msg("begin-convergence")
now_dt = yield Effect(Func(datetime.utcnow))
all_data = yield msg_with_time(
"gather-convergence-data",
convergence_exec_data(tenant_id,
group_id,
now_dt,
get_executor=get_executor))
(executor, scaling_group, group_state, desired_group_state,
resources) = all_data
# prepare plan
steps = executor.plan(desired_group_state, datetime_to_epoch(now_dt),
build_timeout, step_limits, **resources)
yield log_steps(steps)
# Execute plan
yield msg('execute-convergence',
steps=steps,
now=now_dt,
desired=desired_group_state,
**resources)
worst_status, reasons = yield _execute_steps(steps)
if worst_status != StepResult.LIMITED_RETRY:
# If we're not waiting any more, there's no point in keeping track of
# the group
yield clean_waiting
# Handle the status from execution
if worst_status == StepResult.SUCCESS:
result = yield convergence_succeeded(executor, scaling_group,
group_state, resources, now_dt)
elif worst_status == StepResult.FAILURE:
result = yield convergence_failed(scaling_group, reasons)
elif worst_status is StepResult.LIMITED_RETRY:
# We allow further iterations to proceed as long as we haven't been
# waiting for a LIMITED_RETRY for N consecutive iterations.
current_iterations = (yield waiting.read()).get(group_id, 0)
if current_iterations > limited_retry_iterations:
yield msg('converge-limited-retry-too-long')
yield clean_waiting
# Prefix "Timed out" to all limited retry reasons
result = yield convergence_failed(scaling_group, reasons, True)
else:
yield waiting.modify(lambda group_iterations: group_iterations.set(
group_id, current_iterations + 1))
result = ConvergenceIterationStatus.Continue()
else:
result = ConvergenceIterationStatus.Continue()
yield do_return(result)
def execute_convergence(tenant_id, group_id, build_timeout, waiting,
limited_retry_iterations, get_executor=get_executor):
"""
Gather data, plan a convergence, save active and pending servers to the
group state, and then execute the convergence.
:param str tenant_id: the tenant ID for the group to converge
:param str group_id: the ID of the group to be converged
:param number build_timeout: number of seconds to wait for servers to be in
building before it's is timed out and deleted
:param Reference waiting: pmap of waiting groups
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param callable get_all_convergence_data: like
:func`get_all_convergence_data`, used for testing.
:param callable plan: like :func:`plan`, to be used for test injection only
:return: Effect of :obj:`ConvergenceIterationStatus`.
:raise: :obj:`NoSuchScalingGroupError` if the group doesn't exist.
"""
clean_waiting = _clean_waiting(waiting, group_id)
# Gather data
yield msg("begin-convergence")
now_dt = yield Effect(Func(datetime.utcnow))
all_data = yield msg_with_time(
"gather-convergence-data",
convergence_exec_data(tenant_id, group_id, now_dt,
get_executor=get_executor))
(executor, scaling_group, group_state, desired_group_state,
resources) = all_data
# prepare plan
steps = executor.plan(desired_group_state, datetime_to_epoch(now_dt),
build_timeout, **resources)
yield log_steps(steps)
# Execute plan
yield msg('execute-convergence',
steps=steps, now=now_dt, desired=desired_group_state,
**resources)
worst_status, reasons = yield _execute_steps(steps)
if worst_status != StepResult.LIMITED_RETRY:
# If we're not waiting any more, there's no point in keeping track of
# the group
yield clean_waiting
# Handle the status from execution
if worst_status == StepResult.SUCCESS:
result = yield convergence_succeeded(
executor, scaling_group, group_state, resources, now_dt)
elif worst_status == StepResult.FAILURE:
result = yield convergence_failed(scaling_group, reasons)
elif worst_status is StepResult.LIMITED_RETRY:
# We allow further iterations to proceed as long as we haven't been
# waiting for a LIMITED_RETRY for N consecutive iterations.
current_iterations = (yield waiting.read()).get(group_id, 0)
if current_iterations > limited_retry_iterations:
yield msg('converge-limited-retry-too-long')
yield clean_waiting
result = yield convergence_failed(scaling_group, reasons)
else:
yield waiting.modify(
lambda group_iterations:
group_iterations.set(group_id, current_iterations + 1))
result = ConvergenceIterationStatus.Continue()
else:
result = ConvergenceIterationStatus.Continue()
yield do_return(result)
def execute_convergence(tenant_id, group_id, build_timeout, waiting,
limited_retry_iterations, step_limits,
get_executor=get_executor):
"""
Gather data, plan a convergence, save active and pending servers to the
group state, and then execute the convergence.
:param str tenant_id: the tenant ID for the group to converge
:param str group_id: the ID of the group to be converged
:param number build_timeout: number of seconds to wait for servers to be in
building before it's is timed out and deleted
:param Reference waiting: pmap of waiting groups
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step class to number of executions
allowed in a convergence cycle
:param callable get_executor: like :func`get_executor`, used for testing.
:return: Effect of :obj:`ConvergenceIterationStatus`.
:raise: :obj:`NoSuchScalingGroupError` if the group doesn't exist.
"""
clean_waiting = _clean_waiting(waiting, group_id)
# Begin convergence by updating group status to ACTIVE
yield msg("begin-convergence")
try:
yield Effect(LoadAndUpdateGroupStatus(tenant_id, group_id,
ScalingGroupStatus.ACTIVE))
except NoSuchScalingGroupError:
# Expected for DELETING group. Ignore.
pass
# Gather data
now_dt = yield Effect(Func(datetime.utcnow))
try:
all_data = yield msg_with_time(
"gather-convergence-data",
convergence_exec_data(tenant_id, group_id, now_dt,
get_executor=get_executor))
(executor, scaling_group, group_state, desired_group_state,
resources) = all_data
except FirstError as fe:
if fe.exc_info[0] is NoSuchEndpoint:
result = yield convergence_failed(
tenant_id, group_id, [ErrorReason.Exception(fe.exc_info)])
yield do_return(result)
raise fe
# prepare plan
steps = executor.plan(desired_group_state, datetime_to_epoch(now_dt),
build_timeout, step_limits, **resources)
yield log_steps(steps)
# Execute plan
yield msg('execute-convergence',
steps=steps, now=now_dt, desired=desired_group_state,
**resources)
worst_status, reasons = yield _execute_steps(steps)
if worst_status != StepResult.LIMITED_RETRY:
# If we're not waiting any more, there's no point in keeping track of
# the group
yield clean_waiting
# Handle the status from execution
if worst_status == StepResult.SUCCESS:
result = yield convergence_succeeded(
executor, scaling_group, group_state, resources)
elif worst_status == StepResult.FAILURE:
result = yield convergence_failed(tenant_id, group_id, reasons)
elif worst_status is StepResult.LIMITED_RETRY:
# We allow further iterations to proceed as long as we haven't been
# waiting for a LIMITED_RETRY for N consecutive iterations.
current_iterations = (yield waiting.read()).get(group_id, 0)
if current_iterations > limited_retry_iterations:
yield msg('converge-limited-retry-too-long')
yield clean_waiting
# Prefix "Timed out" to all limited retry reasons
result = yield convergence_failed(tenant_id, group_id, reasons,
True)
else:
yield waiting.modify(
lambda group_iterations:
group_iterations.set(group_id, current_iterations + 1))
result = ConvergenceIterationStatus.Continue()
else:
result = ConvergenceIterationStatus.Continue()
yield do_return(result)
def converge_all_groups(
currently_converging, recently_converged, waiting,
my_buckets, all_buckets,
divergent_flags, build_timeout, interval,
limited_retry_iterations, step_limits,
converge_one_group=converge_one_group):
"""
Check for groups that need convergence and which match up to the
buckets we've been allocated.
:param Reference currently_converging: pset of currently converging groups
:param Reference recently_converged: pmap of group ID to time last
convergence finished
:param Reference waiting: pmap of group ID to number of iterations already
waited
:param my_buckets: The buckets that should be checked for group IDs to
converge on.
:param all_buckets: The set of all buckets that can be checked for group
IDs to converge on. ``my_buckets`` should be a subset of this.
:param divergent_flags: divergent flags that were found in zookeeper.
:param number build_timeout: number of seconds to wait for servers to be in
building before it's is timed out and deleted
:param number interval: number of seconds between attempts at convergence.
Groups will not be converged if less than this amount of time has
passed since the end of its last convergence.
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step class to number of executions
allowed in a convergence cycle
:param callable converge_one_group: function to use to converge a single
group - to be used for test injection only
"""
group_infos = get_my_divergent_groups(
my_buckets, all_buckets, divergent_flags)
# filter out currently converging groups
cc = yield currently_converging.read()
group_infos = [info for info in group_infos if info['group_id'] not in cc]
if not group_infos:
return
yield msg('converge-all-groups', group_infos=group_infos,
currently_converging=list(cc))
@do
def converge(tenant_id, group_id, dirty_flag):
stat = yield Effect(GetStat(dirty_flag))
# If the node disappeared, ignore it. `stat` will be None here if the
# divergent flag was discovered only after the group is removed from
# currently_converging, but before the divergent flag is deleted, and
# then the deletion happens, and then our GetStat happens. This
# basically means it happens when one convergence is starting as
# another one for the same group is ending.
if stat is None:
yield msg('converge-divergent-flag-disappeared', znode=dirty_flag)
else:
eff = converge_one_group(currently_converging, recently_converged,
waiting,
tenant_id, group_id,
stat.version, build_timeout,
limited_retry_iterations, step_limits)
result = yield Effect(TenantScope(eff, tenant_id))
yield do_return(result)
recent_groups = yield get_recently_converged_groups(recently_converged,
interval)
effs = []
for info in group_infos:
tenant_id, group_id = info['tenant_id'], info['group_id']
if group_id in recent_groups:
# Don't converge a group if it has recently been converged.
continue
eff = converge(tenant_id, group_id, info['dirty-flag'])
effs.append(
with_log(eff, tenant_id=tenant_id, scaling_group_id=group_id))
yield do_return(parallel(effs))
