def __wait_for_files(container_name):
cgroup_file_wait_timeout = get_config_manager().get_float(
WAIT_CGROUP_FILE_KEY, DEFAULT_WAIT_CGROUP_FILE_SEC)
json_file_wait_timeout = get_config_manager().get_float(
WAIT_JSON_FILE_KEY, DEFAULT_WAIT_JSON_FILE_SEC)
wait_for_files(container_name, cgroup_file_wait_timeout,
json_file_wait_timeout)
def get_workload_from_kubernetes(identifier) -> Optional[KubernetesWorkload]:
if not managers_are_initialized():
log.error(
"Cannot get workload from kubernetes because managers aren't initialized"
)
return None
retry_count = get_config_manager().get_int(
GET_WORKLOAD_RETRY_COUNT, DEFAULT_GET_WORKLOAD_RETRY_COUNT)
retry_interval = get_config_manager().get_float(
GET_WORKLOAD_RETRY_INTERVAL_SEC,
DEFAULT_GET_WORKLOAD_RETRY_INTERVAL_SEC)
pod_manager = get_pod_manager()
for i in range(retry_count):
log.info("Getting pod from kubernetes: %s", identifier)
pod = pod_manager.get_pod(identifier)
if pod is not None:
log.info("Got pod from kubernetes: %s", identifier)
return KubernetesWorkload(pod)
log.info("Retrying getting pod from kubernetes in %s seconds",
retry_interval)
time.sleep(retry_interval)
log.error("Failed to get pod from kubernetes: %s", identifier)
return None
def get_cpu_model_prefix_name():
config_manager = get_config_manager()
prefix = config_manager.get_str(MODEL_BUCKET_PREFIX,
DEFAULT_MODEL_BUCKET_PREFIX)
leaf = config_manager.get_str(MODEL_BUCKET_LEAF, DEFAULT_MODEL_BUCKET_LEAF)
format_str = get_config_manager().get_str(MODEL_PREFIX_FORMAT_STR)
if format_str is None:
return None
return format_str.format(prefix, leaf)
def get_cpu_predictions(self, workloads: List[Workload], resource_usage: GlobalResourceUsage) \
-> Optional[Dict[str, float]]:
config_manager = get_config_manager()
if config_manager is None:
log.warning("Config manager is not yet set")
return {}
cpu_usage = resource_usage.get_cpu_usage()
if cpu_usage is None:
log.warning("No cpu usage")
return {}
pred_env = PredEnvironment(config_manager.get_region(),
config_manager.get_environment(),
datetime.utcnow().hour)
predictions = {}
for workload in workloads:
workload_cpu_usage = cpu_usage.get(workload.get_id(), None)
if workload_cpu_usage is None:
log.warning("No CPU usage for workload: %s", workload.get_id())
continue
workload_cpu_usage = [float(u) for u in workload_cpu_usage]
pred_cpus = self.predict(workload, workload_cpu_usage, pred_env)
predictions[workload.get_id()] = pred_cpus
return predictions
def get_workload_response(workload: Workload,
cpu: Cpu) -> Optional[WorkloadAllocateResponse]:
thread_ids = get_threads(cpu, workload.get_id())
cpu_shares = get_cpu_shares(workload)
cpu_quota = get_cpu_quota(workload)
if len(thread_ids) < 1:
return None
memory_migrate = DEFAULT_TITUS_ISOLATE_MEMORY_MIGRATE
memory_spread_page = DEFAULT_TITUS_ISOLATE_MEMORY_SPREAD_PAGE
memory_spread_slab = DEFAULT_TITUS_ISOLATE_MEMORY_SPREAD_SLAB
config_manager = get_config_manager()
if config_manager is not None:
memory_migrate = config_manager.get_cached_bool(
TITUS_ISOLATE_MEMORY_MIGRATE, DEFAULT_TITUS_ISOLATE_MEMORY_MIGRATE)
memory_spread_page = config_manager.get_cached_bool(
TITUS_ISOLATE_MEMORY_SPREAD_PAGE,
DEFAULT_TITUS_ISOLATE_MEMORY_SPREAD_PAGE)
memory_spread_slab = config_manager.get_cached_bool(
TITUS_ISOLATE_MEMORY_SPREAD_SLAB,
DEFAULT_TITUS_ISOLATE_MEMORY_SPREAD_SLAB)
return WorkloadAllocateResponse(workload_id=workload.get_id(),
thread_ids=thread_ids,
cpu_shares=cpu_shares,
cpu_quota=cpu_quota,
memory_migrate=memory_migrate,
memory_spread_page=memory_spread_page,
memory_spread_slab=memory_spread_slab)
def get_required_property(key):
value = get_config_manager().get_str(key)
if value is None:
log.error("Failed to retrieve property: '{}'".format(key))
return None
return value
def __init__(self, primary_cpu_allocator: CpuAllocator, secondary_cpu_allocator: CpuAllocator):
if primary_cpu_allocator is None:
raise ValueError("Must be provided a primary cpu allocator.")
if secondary_cpu_allocator is None:
raise ValueError("Must be provided a secondary cpu allocator.")
self.__reg = None
self.__primary_allocator = primary_cpu_allocator
self.__secondary_allocator = secondary_cpu_allocator
self.__primary_assign_threads_call_count = 0
self.__primary_free_threads_call_count = 0
self.__primary_rebalance_call_count = 0
self.__secondary_assign_threads_call_count = 0
self.__secondary_free_threads_call_count = 0
self.__secondary_rebalance_call_count = 0
self.__queue_depth_fallback_count = 0
cm = get_config_manager()
self.__fallback_queue_depth = cm.get_cached_int(FALLBACK_QUEUE_DEPTH, DEFAULT_FALLBACK_QUEUE_DEPTH)
log.info(
"Created FallbackCpuAllocator with primary cpu allocator: '{}' and secondary cpu allocator: '{}', fallback queue depth: '{}'".format(
self.__primary_allocator.__class__.__name__,
self.__secondary_allocator.__class__.__name__,
self.__fallback_queue_depth))
def __init__(self,
event_iterable,
event_handlers,
event_timeout=DEFAULT_EVENT_TIMEOUT_SECS):
self.__reg = None
self.__stopped = False
self.__q = Queue()
self.__events = event_iterable
self.__event_handlers = event_handlers
self.__event_timeout = event_timeout
self.__success_event_count = 0
self.__error_event_count = 0
self.__processed_event_count = 0
self.__started = False
self.__started_lock = Lock()
self.__processing_thread = Thread(target=self.__process_events)
self.__pulling_thread = Thread(target=self.__pull_events)
config_manager = get_config_manager()
rebalance_frequency = config_manager.get_float(
REBALANCE_FREQUENCY_KEY, DEFAULT_REBALANCE_FREQUENCY)
if rebalance_frequency > 0:
schedule.every(rebalance_frequency).seconds.do(self.__rebalance)
reconcile_frequency = config_manager.get_float(
RECONCILE_FREQUENCY_KEY, DEFAULT_RECONCILE_FREQUENCY)
if reconcile_frequency > 0:
schedule.every(reconcile_frequency).seconds.do(self.__reconcile)
def get_cpu_shares(workload: Workload) -> int:
if workload.is_opportunistic():
opportunistic_shares_scale = get_config_manager().get_int(
OPPORTUNISTIC_SHARES_SCALE_KEY, DEFAULT_OPPORTUNISTIC_SHARES_SCALE)
return workload.get_thread_count() * opportunistic_shares_scale
return workload.get_thread_count() * DEFAULT_SHARES_SCALE
def get_prom_url() -> str:
cm = get_config_manager()
# e.g. titusprometheus.us-east-1.staging01cell001.test.netflix.net
default_host = f'titusprometheus.{cm.get_region()}.{cm.get_stack()}.{cm.get_environment()}.netflix.net'
host = cm.get_cached_str(PROMETHEUS_HOST_OVERRIDE, default_host)
return f'http://{host}/api/v1/query_range'
def get_predictions(
self, running_pods: List[V1Pod], resource_usage: GlobalResourceUsage
) -> Optional[ResourceUsagePredictions]:
config_manager = get_config_manager()
if config_manager is None:
log.warning("Config manager not yet set.")
return None
client_crt = get_client_cert_path(config_manager)
client_key = get_client_key_path(config_manager)
if client_crt is None or client_key is None:
log.error("Failed to generate credential paths")
return None
url = get_url(config_manager)
if url is None:
log.error("Unable to generate prediction service url")
return None
body = self.__get_body(running_pods, resource_usage)
if body is None:
log.error("Unable to generate a prediction request body")
return None
predictions = get_predictions(client_crt, client_key, url, body)
if predictions is None:
log.error("Failed to get predictions")
return None
return ResourceUsagePredictions(predictions)
def __get_request_metadata(self, request_type) -> dict:
config_manager = get_config_manager()
return {
"type": request_type,
"instance_id": self.__instance_id,
"region": config_manager.get_region(),
"environment": config_manager.get_environment()
}
def __update_local_model(self):
cpu_predictor = get_config_manager().get_str(CPU_PREDICTOR, DEFAULT_CPU_PREDICTOR)
if cpu_predictor == LEGACY_CPU_PREDICTOR:
download_latest_cpu_model()
with self.__lock:
self.__cpu_usage_predictor = CpuUsagePredictor(get_cpu_model_file_path())
else:
log.info("Skipping model update. CPU predictor: %s", cpu_predictor)
def __init__(self, free_thread_provider=EmptyFreeThreadProvider()):
self.__reg = None
self.__cache = {}
self.__time_bound_call_count = 0
self.__solver_max_runtime_secs = get_config_manager().get_float(
MAX_SOLVER_RUNTIME, DEFAULT_MAX_SOLVER_RUNTIME)
self.__free_thread_provider = free_thread_provider
def __init__(self, free_thread_provider):
config_manager = get_config_manager()
self.__url = config_manager.get_str(REMOTE_ALLOCATOR_URL, "http://localhost:7501")
solver_max_runtime_secs = config_manager.get_float(MAX_SOLVER_RUNTIME, DEFAULT_MAX_SOLVER_RUNTIME)
solver_max_connect_secs = config_manager.get_float(MAX_SOLVER_CONNECT_SEC, DEFAULT_MAX_SOLVER_CONNECT_SEC)
self.__timeout = (solver_max_connect_secs, solver_max_runtime_secs)
self.__headers = {'Content-Type': "application/json"}
self.__reg = None
def __init__(self, exit_handler: ExitHandler):
self.__exit_handler = exit_handler
self.__config_manager = get_config_manager()
self.__registry = None
self.__oppo = None
self.__custom_api = kubernetes.client.CustomObjectsApi(
kubernetes.config.new_client_from_config(
config_file=DEFAULT_KUBECONFIG_PATH))
def __set_address(self):
config_manager = get_config_manager()
region = config_manager.get_region()
env = config_manager.get_environment()
format_str = config_manager.get_str(EVENT_LOG_FORMAT_STR)
stream = 'titus_isolate'
self.__address = format_str.format(region, env, stream)
log.info("Set keystone address to: {}".format(self.__address))
def __init__(self):
self.__config_manager = get_config_manager()
self.__node_name = self.__config_manager.get_str(EC2_INSTANCE_ID)
kubeconfig = self.get_kubeconfig_path()
self.__core_api = kubernetes.client.CoreV1Api(
kubernetes.config.new_client_from_config(config_file=kubeconfig))
# NOTE[jigish]: This API depends on the OpportunisticResource CRD. See the readme for how to create it.
self.__custom_api = kubernetes.client.CustomObjectsApi(
kubernetes.config.new_client_from_config(config_file=kubeconfig))
def get_cpu_model_bucket_name():
format_str = get_required_property(MODEL_BUCKET_FORMAT_STR)
if format_str is None:
return None
config_manager = get_config_manager()
region = config_manager.get_region()
env = config_manager.get_environment()
return format_str.format(region, env)
def __get_tags():
ec2_instance_id = 'EC2_INSTANCE_ID'
tags = {}
if ec2_instance_id in os.environ:
tags["node"] = os.environ[ec2_instance_id]
allocator_name = get_allocator_class(get_config_manager()).__name__
tags["cpu_allocator"] = allocator_name
return tags
def __get_address(self) -> Optional[str]:
config_manager = get_config_manager()
region = config_manager.get_region()
env = config_manager.get_environment()
format_str = config_manager.get_str(EVENT_LOG_FORMAT_STR)
if format_str is None:
log.warning("Keystone is not enabled in this region env: %s %s", region, env)
return None
stream = 'titus_isolate'
return format_str.format(region, env, stream)
def get_cpu_predictor(self) -> Optional[SimpleCpuPredictor]:
config_manager = get_config_manager()
cpu_predictor = config_manager.get_str(CPU_PREDICTOR, DEFAULT_CPU_PREDICTOR)
log.info("Using cpu predictor: %s", cpu_predictor)
if cpu_predictor == SERVICE_CPU_PREDICTOR:
return self.__resource_usage_predictor
if cpu_predictor == LEGACY_CPU_PREDICTOR:
with self.__lock:
return self.__cpu_usage_predictor
return None
def __watch(self):
while True:
try:
instance_id = get_config_manager().get_str("EC2_INSTANCE_ID")
field_selector = "spec.nodeName={}".format(instance_id)
log.info("Watching pods with field selector: %s",
field_selector)
v1 = client.CoreV1Api()
w = watch.Watch()
for event in w.stream(v1.list_pod_for_all_namespaces,
field_selector=field_selector):
self.__handle_event(event)
except:
log.exception("pod watch thread failed")
def __init__(self, workload_manager: WorkloadManager,
window_publisher: OpportunisticWindowPublisher):
super().__init__(workload_manager)
self.__window_publisher = window_publisher
self.__reg = None
self.__fail_count = 0
self.__skip_count = 0
self.__success_count = 0
self.__reclaimed_cpu_count = None
self.__config_manager = get_config_manager()
self.__workload_monitor_manager = get_workload_monitor_manager()
self.__cpu_usage_predictor_manager = get_cpu_usage_predictor_manager()
self.__node_name = self.__config_manager.get_str(EC2_INSTANCE_ID)
def update_numa_balancing(workload: Workload, cpu: Cpu):
try:
config_manager = get_config_manager()
dynamic_numa_balancing_enabled = config_manager.get_bool(
TITUS_ISOLATE_DYNAMIC_NUMA_BALANCING,
DEFAULT_TITUS_ISOLATE_DYNAMIC_NUMA_BALANCING)
if not dynamic_numa_balancing_enabled:
enable_numa_balancing()
return
if _occupies_entire_cpu(workload, cpu):
disable_numa_balancing()
else:
enable_numa_balancing()
except Exception:
log.error("Failed to update NUMA balancing.")
def isolate_workload(workload_id, timeout=None):
if timeout is None:
timeout = get_config_manager().get_float(
TITUS_ISOLATE_BLOCK_SEC, DEFAULT_TITUS_ISOLATE_BLOCK_SEC)
deadline = time.time() + timeout
while time.time() < deadline:
if get_workload_manager().is_isolated(workload_id):
return json.dumps({'workload_id': workload_id}), 200, {
'ContentType': 'application/json'
}
time.sleep(0.1)
log.error("Failed to isolate workload: '{}'".format(workload_id))
return json.dumps({'unknown_workload_id': workload_id}), 404, {
'ContentType': 'application/json'
}
def __init__(self, event_iterable, event_handlers, event_timeout=DEFAULT_EVENT_TIMEOUT_SECS):
self.__reg = None
self.__tags = None
self.__stopped = False
self.__q = Queue()
self.__events = event_iterable
self.__event_handlers = event_handlers
self.__event_timeout = event_timeout
self.__processed_count = 0
self.__started = False
self.__started_lock = Lock()
self.__processing_thread = Thread(target=self.__process_events)
self.__pulling_thread = Thread(target=self.__pull_events)
self.last_successful_event_epoch_s = 0
config_manager = get_config_manager()
# Every instance of titus-isolate getting restarted at once produces scheduling spikes of events like
# rebalance
random_jitter = randrange(10) # 0-9 inclusive
rebalance_frequency = config_manager.get_float(REBALANCE_FREQUENCY_KEY, DEFAULT_REBALANCE_FREQUENCY)
if rebalance_frequency > 0:
schedule.every(rebalance_frequency + random_jitter).seconds.do(self.__rebalance)
reconcile_frequency = config_manager.get_float(RECONCILE_FREQUENCY_KEY, DEFAULT_RECONCILE_FREQUENCY)
if reconcile_frequency > 0:
schedule.every(reconcile_frequency + random_jitter).seconds.do(self.__reconcile)
oversubscribe_frequency = config_manager.get_float(OVERSUBSCRIBE_FREQUENCY_KEY,
DEFAULT_OVERSUBSCRIBE_FREQUENCY)
if oversubscribe_frequency > 0:
schedule.every(oversubscribe_frequency + random_jitter).seconds.do(self.__oversubscribe)
predict_resource_usage_frequency = config_manager.get_float(PREDICT_RESOURCE_USAGE_FREQUENCY_KEY,
DEFAULT_PREDICT_RESOURCE_USAGE_FREQUENCY)
if predict_resource_usage_frequency > 0:
schedule.every(predict_resource_usage_frequency + random_jitter).seconds.do(self.__predict_usage)
def __init__(self, free_thread_provider):
config_manager = get_config_manager()
self.__endpoint = config_manager.get_cached_str(
GRPC_REMOTE_ALLOC_ENDPOINT, None)
if self.__endpoint is None:
raise Exception("Could not get remote allocator endpoint address.")
self.__call_timeout_secs = 1000.0 * config_manager.get_cached_int(
GRPC_REMOTE_ALLOC_CLIENT_CALL_TIMEOUT_MS,
GRPC_REMOTE_ALLOC_DEFAULT_CLIENT_CALL_TIMEOUT_MS)
self.__stub = self.__create_stub()
self.__instance_ctx = self.__pull_context()
self.__reg = None
self.__empty_cpu = get_cpu_from_env()
self.__natural2original_indexing = self.__empty_cpu.get_natural_indexing_2_original_indexing(
)
self.__original2natural_indexing = {
v: k
for k, v in self.__natural2original_indexing.items()
}
def __init__(self, cpu: Cpu, cgroup_manager: CgroupManager, cpu_allocator: CpuAllocator):
self.__reg = None
self.__lock = Lock()
self.__instance_id = get_config_manager().get_str(EC2_INSTANCE_ID)
self.__cpu_allocator = cpu_allocator
self.__error_count = 0
self.__added_count = 0
self.__removed_count = 0
self.__rebalanced_count = 0
self.__added_to_full_cpu_count = 0
self.__allocator_call_duration_sum_secs = 0
self.__cpu = cpu
self.__cgroup_manager = cgroup_manager
self.__wmm = get_workload_monitor_manager()
self.__workloads = {}
log.info("Created workload manager")
def __init__(self, exit_handler: ExitHandler):
self.__exit_handler = exit_handler
self.__config_manager = get_config_manager()
self.__node_name = self.__config_manager.get_str(EC2_INSTANCE_ID)
kubeconfig = self.get_kubeconfig_path()
self.__core_api = kubernetes.client.CoreV1Api(
kubernetes.config.new_client_from_config(config_file=kubeconfig))
self.__custom_api = kubernetes.client.CustomObjectsApi(
kubernetes.config.new_client_from_config(config_file=kubeconfig))
self.__lock = Lock()
self.__opportunistic_resources = {}
oversubscribe_frequency = self.__config_manager.get_float(
OVERSUBSCRIBE_FREQUENCY_KEY, DEFAULT_OVERSUBSCRIBE_FREQUENCY)
if oversubscribe_frequency > 0:
watch_thread = Thread(target=self.__watch)
watch_thread.start()
else:
log.info(
"Skipping opportunistic resource watch, as opportunistic publishing is not configured."
)
