def test_get_limits_conf(self):
"""
`get_step_limits_from_conf` will return configured limit along with
default limit
"""
limits = get_step_limits_from_conf({"create_server": 100})
self.assertEqual(limits, {CreateServer: 100, CreateStack: 10})
def test_get_limits_conf(self):
"""
`get_step_limits_from_conf` will return configured limit along with
default limit
"""
limits = get_step_limits_from_conf({"create_server": 100})
self.assertEqual(limits, {CreateServer: 100, CreateStack: 10})
def __init__(self,
log,
dispatcher,
num_buckets,
partitioner_factory,
build_timeout,
interval,
limited_retry_iterations,
step_limits,
converge_all_groups=converge_all_groups):
"""
:param log: a bound log
:param dispatcher: The dispatcher to use to perform effects.
:param int buckets: the number of logical `buckets` which are be
shared between all Otter nodes running this service. The buckets
will be partitioned up between nodes to detirmine which nodes
should work on which groups.
:param partitioner_factory: Callable of (all_buckets, log, callback)
which should create an :obj:`Partitioner` to distribute the
buckets.
:param number build_timeout: number of seconds to wait for servers to
be in building before it's is timed out and deleted
:param interval: Interval between convergence steps, per group.
:param callable converge_all_groups: like :func:`converge_all_groups`,
to be used for test injection only
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step name to number of executions
allowed in a convergence cycle
"""
MultiService.__init__(self)
self.log = log.bind(otter_service='converger')
self._dispatcher = dispatcher
self._buckets = range(num_buckets)
self.partitioner = partitioner_factory(
buckets=self._buckets,
log=self.log,
got_buckets=self.buckets_acquired)
self.partitioner.setServiceParent(self)
self.build_timeout = build_timeout
self._converge_all_groups = converge_all_groups
self.interval = interval
self.limited_retry_iterations = limited_retry_iterations
self.step_limits = get_step_limits_from_conf(step_limits)
# ephemeral mutable state
self.currently_converging = Reference(pset())
self.recently_converged = Reference(pmap())
# Groups we're waiting on temporarily, and may give up on.
self.waiting = Reference(pmap()) # {group_id: num_iterations_waited}
def __init__(self, log, dispatcher, num_buckets, partitioner_factory,
build_timeout, interval,
limited_retry_iterations, step_limits,
converge_all_groups=converge_all_groups):
"""
:param log: a bound log
:param dispatcher: The dispatcher to use to perform effects.
:param int buckets: the number of logical `buckets` which are be
shared between all Otter nodes running this service. The buckets
will be partitioned up between nodes to detirmine which nodes
should work on which groups.
:param partitioner_factory: Callable of (all_buckets, log, callback)
which should create an :obj:`Partitioner` to distribute the
buckets.
:param number build_timeout: number of seconds to wait for servers to
be in building before it's is timed out and deleted
:param interval: Interval between convergence steps, per group.
:param callable converge_all_groups: like :func:`converge_all_groups`,
to be used for test injection only
:param int limited_retry_iterations: number of iterations to wait for
LIMITED_RETRY steps
:param dict step_limits: Mapping of step name to number of executions
allowed in a convergence cycle
"""
MultiService.__init__(self)
self.log = log.bind(otter_service='converger')
self._dispatcher = dispatcher
self._buckets = range(num_buckets)
self.partitioner = partitioner_factory(
buckets=self._buckets, log=self.log,
got_buckets=self.buckets_acquired)
self.partitioner.setServiceParent(self)
self.build_timeout = build_timeout
self._converge_all_groups = converge_all_groups
self.interval = interval
self.limited_retry_iterations = limited_retry_iterations
self.step_limits = get_step_limits_from_conf(step_limits)
# ephemeral mutable state
self.currently_converging = Reference(pset())
self.recently_converged = Reference(pmap())
# Groups we're waiting on temporarily, and may give up on.
self.waiting = Reference(pmap()) # {group_id: num_iterations_waited}
