def faas_idler(env: Environment,
inactivity_duration=300,
reconcile_interval=30):
"""
https://github.com/openfaas-incubator/faas-idler
https://github.com/openfaas-incubator/faas-idler/blob/master/main.go
default values:
https://github.com/openfaas-incubator/faas-idler/blob/668991c532156275993399ee79a297a4c2d651ec/docker-compose.yml
:param env: the faas environment
:param inactivity_duration: i.e. 15m (Golang duration)
:param reconcile_interval: i.e. 1m (default value)
:return: an event generator
"""
faas: FaasSystem = env.faas
while True:
yield env.timeout(reconcile_interval)
for deployment in faas.get_deployments():
if not deployment.scale_zero:
continue
for function in deployment.function_definitions.values():
if len(faas.get_replicas(function.name,
FunctionState.RUNNING)) == 0:
continue
idle_time = env.now - env.metrics.last_invocation[
function.name]
if idle_time >= inactivity_duration:
env.process(faas.suspend(function.name))
logger.debug('%.2f function %s has been idle for %.2fs',
env.now, function.name, idle_time)
def run(self, env: Environment):
# deploy functions
deployments = self.prepare_deployments()
for deployment in deployments:
yield from env.faas.deploy(deployment)
# block until replicas become available (scheduling has finished and replicas have been deployed on the node)
logger.info('waiting for replica')
yield env.process(env.faas.poll_available_replica('python-pi'))
yield env.process(env.faas.poll_available_replica('resnet50-inference'))
# run workload
ps = []
# execute 10 requests in parallel
logger.info('executing 10 python-pi requests')
for i in range(10):
ps.append(env.process(env.faas.invoke(FunctionRequest('python-pi'))))
logger.info('executing 10 resnet50-inference requests')
for i in range(10):
ps.append(env.process(env.faas.invoke(FunctionRequest('resnet50-inference'))))
# wait for invocation processes to finish
for p in ps:
yield p
def function_trigger(env: Environment,
deployment: FunctionDeployment,
ia_generator,
max_requests=None):
try:
if max_requests is None:
while True:
ia = next(ia_generator)
yield env.timeout(ia)
env.process(env.faas.invoke(FunctionRequest(deployment.name)))
else:
for _ in range(max_requests):
ia = next(ia_generator)
yield env.timeout(ia)
env.process(env.faas.invoke(FunctionRequest(deployment.name)))
except simpy.Interrupt:
pass
except StopIteration:
logging.error(f'{deployment.name} gen has finished')
def run(self, env: Environment):
for deployment in self.deployments:
yield from env.faas.deploy(deployment)
for deployment in self.deployments:
yield env.process(env.faas.poll_available_replica(deployment.name))
ps = []
logging.info('executing requests')
for deployment in self.deployments:
try:
ia_generator = self.arrival_profiles[deployment.name]
if self.duration is None:
p = env.process(function_trigger(env, deployment, ia_generator, max_requests=1000))
else:
p = env.process(function_trigger(env, deployment, ia_generator))
ps.append(p)
except KeyError:
logging.warning('no arrival profile for deployment %s', deployment.name)
if self.duration is not None:
env.process(self.wait(env, ps))
yield from ps
def run(self, env: Environment):
# deploy functions
deployments = self.prepare_deployments()
for deployment in deployments:
yield from env.faas.deploy(deployment)
# block until replicas become available (scheduling has finished and replicas have been deployed on the node)
logger.info('waiting for replica')
yield env.process(env.faas.poll_available_replica('python-pi'))
# generate profile
ia_generator = expovariate_arrival_profile(
constant_rps_profile(rps=20))
# run profile
yield from function_trigger(env,
deployments[0],
ia_generator,
max_requests=100)
