def configure_env(settings: EnvSettings, topology: Topology):
env = Environment()
env.simulator_factory = settings.simulator_factory
if settings.null_logger:
env.metrics = OurMetrics(env, log=NullLogger())
else:
env.metrics = OurMetrics(env, log=RuntimeLogger(SimulatedClock(env)))
env.topology = topology
env.faas = OurFaas(env, settings.scale_by_requests,
settings.scale_by_requests_per_replica,
settings.scale_by_queue_requests_per_replica)
env.container_registry = ContainerRegistry()
env.storage_index = settings.storage_index
env.cluster = SimulationClusterContext(env)
env.scheduler = Scheduler(env.cluster, **settings.sched_params)
env.metrics_server = MetricsServer()
# TODO inject resource oracle
resource_monitor = ResourceMonitor(
env, ResourceOracle(resources_per_node_image))
env.background_processes.append(lambda env: resource_monitor.run())
if settings.scale_by_resources:
hpa_settings = settings.hpaSettings
hpa = HorizontalPodAutoscaler(
env,
average_window=hpa_settings.average_window,
reconcile_interval=hpa_settings.reconcile_interval,
target_tolerance=hpa_settings.target_tolerance)
env.background_processes.append(lambda env: hpa.run())
if settings.label_problem_solver_settings is not None:
solver = LabelSolverProcess(settings.label_problem_solver_settings)
env.background_processes.append(lambda env: solver.solve(env))
return env
'predicates': predicates
}
# Set arrival profiles/workload pattern
benchmark = ConstantBenchmark('mixed', duration=200, rps=50)
# Initialize topology
storage_index = StorageIndex()
topology = urban_sensing_topology(ether_nodes, storage_index)
# Initialize environment
env = Environment()
env.simulator_factory = AIPythonHTTPSimulatorFactory(
get_raith21_function_characterizations(resource_oracle, fet_oracle))
env.metrics = Metrics(env, log=RuntimeLogger(SimulatedClock(env)))
env.topology = topology
env.faas = DefaultFaasSystem(env, scale_by_requests=True)
env.container_registry = ContainerRegistry()
env.storage_index = storage_index
env.cluster = SimulationClusterContext(env)
env.scheduler = Scheduler(env.cluster, **sched_params)
sim = Simulation(env.topology, benchmark, env=env)
result = sim.run()
dfs = {
"invocations_df":
sim.env.metrics.extract_dataframe('invocations'),
"scale_df":
sim.env.metrics.extract_dataframe('scale'),
