class ReporterAgent(dashboard_utils.DashboardAgentModule, reporter_pb2_grpc.ReporterServiceServicer): """A monitor process for monitoring Ray nodes. Attributes: dashboard_agent: The DashboardAgent object contains global config """ def __init__(self, dashboard_agent): """Initialize the reporter object.""" super().__init__(dashboard_agent) if IN_KUBERNETES_POD: # psutil does not compute this correctly when in a K8s pod. # Use ray._private.utils instead. cpu_count = ray._private.utils.get_num_cpus() self._cpu_counts = (cpu_count, cpu_count) else: self._cpu_counts = (psutil.cpu_count(), psutil.cpu_count(logical=False)) self._ip = ray._private.services.get_node_ip_address() self._hostname = socket.gethostname() self._workers = set() self._network_stats_hist = [(0, (0.0, 0.0))] # time, (sent, recv) self._metrics_agent = MetricsAgent(dashboard_agent.metrics_export_port) self._key = f"{reporter_consts.REPORTER_PREFIX}" \ f"{self._dashboard_agent.node_id}" async def GetProfilingStats(self, request, context): pid = request.pid duration = request.duration profiling_file_path = os.path.join( ray._private.utils.get_ray_temp_dir(), f"{pid}_profiling.txt") sudo = "sudo" if ray._private.utils.get_user() != "root" else "" process = await asyncio.create_subprocess_shell( f"{sudo} $(which py-spy) record " f"-o {profiling_file_path} -p {pid} -d {duration} -f speedscope", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) stdout, stderr = await process.communicate() if process.returncode != 0: profiling_stats = "" else: with open(profiling_file_path, "r") as f: profiling_stats = f.read() return reporter_pb2.GetProfilingStatsReply( profiling_stats=profiling_stats, std_out=stdout, std_err=stderr) async def ReportOCMetrics(self, request, context): # This function receives a GRPC containing OpenCensus (OC) metrics # from a Ray process, then exposes those metrics to Prometheus. try: self._metrics_agent.record_metric_points_from_protobuf( request.metrics) except Exception: logger.error(traceback.format_exc()) return reporter_pb2.ReportOCMetricsReply() @staticmethod def _get_cpu_percent(): if IN_KUBERNETES_POD: return k8s_utils.cpu_percent() else: return psutil.cpu_percent() @staticmethod def _get_gpu_usage(): if gpustat is None: return [] gpu_utilizations = [] gpus = [] try: gpus = gpustat.new_query().gpus except Exception as e: logger.debug(f"gpustat failed to retrieve GPU information: {e}") for gpu in gpus: # Note the keys in this dict have periods which throws # off javascript so we change .s to _s gpu_data = { "_".join(key.split(".")): val for key, val in gpu.entry.items() } gpu_utilizations.append(gpu_data) return gpu_utilizations @staticmethod def _get_boot_time(): if IN_KUBERNETES_POD: # Return start time of container entrypoint return psutil.Process(pid=1).create_time() else: return psutil.boot_time() @staticmethod def _get_network_stats(): ifaces = [ v for k, v in psutil.net_io_counters(pernic=True).items() if k[0] == "e" ] sent = sum((iface.bytes_sent for iface in ifaces)) recv = sum((iface.bytes_recv for iface in ifaces)) return sent, recv @staticmethod def _get_mem_usage(): total = ray._private.utils.get_system_memory() used = ray._private.utils.get_used_memory() available = total - used percent = round(used / total, 3) * 100 return total, available, percent, used @staticmethod def _get_disk_usage(): dirs = [ os.environ["USERPROFILE"] if sys.platform == "win32" else os.sep, ray._private.utils.get_user_temp_dir(), ] return {x: psutil.disk_usage(x) for x in dirs} def _get_workers(self): raylet_proc = self._get_raylet_proc() if raylet_proc is None: return [] else: workers = set(raylet_proc.children()) self._workers.intersection_update(workers) self._workers.update(workers) self._workers.discard(psutil.Process()) return [ w.as_dict(attrs=[ "pid", "create_time", "cpu_percent", "cpu_times", "cmdline", "memory_info", ]) for w in self._workers if w.status() != psutil.STATUS_ZOMBIE ] @staticmethod def _get_raylet_proc(): try: curr_proc = psutil.Process() # Here, parent is always raylet because the # dashboard agent is a child of the raylet process. parent = curr_proc.parent() if parent is not None: if parent.pid == 1: return None if parent.status() == psutil.STATUS_ZOMBIE: return None return parent except (psutil.AccessDenied, ProcessLookupError): pass return None def _get_raylet(self): raylet_proc = self._get_raylet_proc() if raylet_proc is None: return {} else: return raylet_proc.as_dict(attrs=[ "pid", "create_time", "cpu_percent", "cpu_times", "cmdline", "memory_info", ]) def _get_load_avg(self): if sys.platform == "win32": cpu_percent = psutil.cpu_percent() load = (cpu_percent, cpu_percent, cpu_percent) else: load = os.getloadavg() per_cpu_load = tuple((round(x / self._cpu_counts[0], 2) for x in load)) return load, per_cpu_load def _get_all_stats(self): now = dashboard_utils.to_posix_time(datetime.datetime.utcnow()) network_stats = self._get_network_stats() self._network_stats_hist.append((now, network_stats)) self._network_stats_hist = self._network_stats_hist[-7:] then, prev_network_stats = self._network_stats_hist[0] prev_send, prev_recv = prev_network_stats now_send, now_recv = network_stats network_speed_stats = ((now_send - prev_send) / (now - then), (now_recv - prev_recv) / (now - then)) return { "now": now, "hostname": self._hostname, "ip": self._ip, "cpu": self._get_cpu_percent(), "cpus": self._cpu_counts, "mem": self._get_mem_usage(), "workers": self._get_workers(), "raylet": self._get_raylet(), "bootTime": self._get_boot_time(), "loadAvg": self._get_load_avg(), "disk": self._get_disk_usage(), "gpus": self._get_gpu_usage(), "network": network_stats, "network_speed": network_speed_stats, # Deprecated field, should be removed with frontend. "cmdline": self._get_raylet().get("cmdline", []), } @staticmethod def _record_stats(stats): records_reported = [] ip = stats["ip"] # -- CPU per node -- cpu_usage = float(stats["cpu"]) cpu_record = Record( gauge=METRICS_GAUGES["node_cpu_utilization"], value=cpu_usage, tags={"ip": ip}) cpu_count, _ = stats["cpus"] cpu_count_record = Record( gauge=METRICS_GAUGES["node_cpu_count"], value=cpu_count, tags={"ip": ip}) # -- Mem per node -- mem_total, mem_available, _, mem_used = stats["mem"] mem_used_record = Record( gauge=METRICS_GAUGES["node_mem_used"], value=mem_used, tags={"ip": ip}) mem_available_record = Record( gauge=METRICS_GAUGES["node_mem_available"], value=mem_available, tags={"ip": ip}) mem_total_record = Record( gauge=METRICS_GAUGES["node_mem_total"], value=mem_total, tags={"ip": ip}) # -- GPU per node -- gpus = stats["gpus"] gpus_available = len(gpus) if gpus_available: gpus_utilization, gram_used, gram_total = 0, 0, 0 for gpu in gpus: gpus_utilization += gpu["utilization_gpu"] gram_used += gpu["memory_used"] gram_total += gpu["memory_total"] gram_available = gram_total - gram_used gpus_available_record = Record( gauge=METRICS_GAUGES["node_gpus_available"], value=gpus_available, tags={"ip": ip}) gpus_utilization_record = Record( gauge=METRICS_GAUGES["node_gpus_utilization"], value=gpus_utilization, tags={"ip": ip}) gram_used_record = Record( gauge=METRICS_GAUGES["node_gram_used"], value=gram_used, tags={"ip": ip}) gram_available_record = Record( gauge=METRICS_GAUGES["node_gram_available"], value=gram_available, tags={"ip": ip}) records_reported.extend([ gpus_available_record, gpus_utilization_record, gram_used_record, gram_available_record ]) # -- Disk per node -- used, free = 0, 0 for entry in stats["disk"].values(): used += entry.used free += entry.free disk_utilization = float(used / (used + free)) * 100 disk_usage_record = Record( gauge=METRICS_GAUGES["node_disk_usage"], value=used, tags={"ip": ip}) disk_utilization_percentage_record = Record( gauge=METRICS_GAUGES["node_disk_utilization_percentage"], value=disk_utilization, tags={"ip": ip}) # -- Network speed (send/receive) stats per node -- network_stats = stats["network"] network_sent_record = Record( gauge=METRICS_GAUGES["node_network_sent"], value=network_stats[0], tags={"ip": ip}) network_received_record = Record( gauge=METRICS_GAUGES["node_network_received"], value=network_stats[1], tags={"ip": ip}) # -- Network speed (send/receive) per node -- network_speed_stats = stats["network_speed"] network_send_speed_record = Record( gauge=METRICS_GAUGES["node_network_send_speed"], value=network_speed_stats[0], tags={"ip": ip}) network_receive_speed_record = Record( gauge=METRICS_GAUGES["node_network_receive_speed"], value=network_speed_stats[1], tags={"ip": ip}) raylet_stats = stats["raylet"] if raylet_stats: raylet_pid = str(raylet_stats["pid"]) # -- raylet CPU -- raylet_cpu_usage = float(raylet_stats["cpu_percent"]) * 100 raylet_cpu_record = Record( gauge=METRICS_GAUGES["raylet_cpu"], value=raylet_cpu_usage, tags={ "ip": ip, "pid": raylet_pid }) # -- raylet mem -- raylet_mem_usage = float(raylet_stats["memory_info"].rss) / 1e6 raylet_mem_record = Record( gauge=METRICS_GAUGES["raylet_mem"], value=raylet_mem_usage, tags={ "ip": ip, "pid": raylet_pid }) records_reported.extend([raylet_cpu_record, raylet_mem_record]) records_reported.extend([ cpu_record, cpu_count_record, mem_used_record, mem_available_record, mem_total_record, disk_usage_record, disk_utilization_percentage_record, network_sent_record, network_received_record, network_send_speed_record, network_receive_speed_record ]) return records_reported async def _perform_iteration(self, aioredis_client): """Get any changes to the log files and push updates to Redis.""" while True: try: stats = self._get_all_stats() records_reported = self._record_stats(stats) self._metrics_agent.record_reporter_stats(records_reported) await aioredis_client.publish(self._key, jsonify_asdict(stats)) except Exception: logger.exception("Error publishing node physical stats.") await asyncio.sleep( reporter_consts.REPORTER_UPDATE_INTERVAL_MS / 1000) async def run(self, server): aioredis_client = await aioredis.create_redis_pool( address=self._dashboard_agent.redis_address, password=self._dashboard_agent.redis_password) reporter_pb2_grpc.add_ReporterServiceServicer_to_server(self, server) await self._perform_iteration(aioredis_client)
class ReporterAgent(dashboard_utils.DashboardAgentModule, reporter_pb2_grpc.ReporterServiceServicer): """A monitor process for monitoring Ray nodes. Attributes: dashboard_agent: The DashboardAgent object contains global config """ def __init__(self, dashboard_agent): """Initialize the reporter object.""" super().__init__(dashboard_agent) if IN_KUBERNETES_POD: # psutil does not compute this correctly when in a K8s pod. # Use ray._private.utils instead. cpu_count = ray._private.utils.get_num_cpus() self._cpu_counts = (cpu_count, cpu_count) else: self._cpu_counts = (psutil.cpu_count(), psutil.cpu_count(logical=False)) self._ip = dashboard_agent.ip self._is_head_node = self._ip == dashboard_agent.gcs_address.split( ":")[0] self._hostname = socket.gethostname() self._workers = set() self._network_stats_hist = [(0, (0.0, 0.0))] # time, (sent, recv) self._disk_io_stats_hist = [ (0, (0.0, 0.0, 0, 0)) ] # time, (bytes read, bytes written, read ops, write ops) self._metrics_collection_disabled = dashboard_agent.metrics_collection_disabled self._metrics_agent = None if not self._metrics_collection_disabled: self._metrics_agent = MetricsAgent( "127.0.0.1" if self._ip == "127.0.0.1" else "", dashboard_agent.metrics_export_port, ) self._key = (f"{reporter_consts.REPORTER_PREFIX}" f"{self._dashboard_agent.node_id}") async def GetProfilingStats(self, request, context): pid = request.pid duration = request.duration profiling_file_path = os.path.join( ray._private.utils.get_ray_temp_dir(), f"{pid}_profiling.txt") sudo = "sudo" if ray._private.utils.get_user() != "root" else "" process = await asyncio.create_subprocess_shell( f"{sudo} $(which py-spy) record " f"-o {profiling_file_path} -p {pid} -d {duration} -f speedscope", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True, ) stdout, stderr = await process.communicate() if process.returncode != 0: profiling_stats = "" else: with open(profiling_file_path, "r") as f: profiling_stats = f.read() return reporter_pb2.GetProfilingStatsReply( profiling_stats=profiling_stats, std_out=stdout, std_err=stderr) async def ReportOCMetrics(self, request, context): # Do nothing if metrics collection is disabled. if self._metrics_collection_disabled: return reporter_pb2.ReportOCMetricsReply() # This function receives a GRPC containing OpenCensus (OC) metrics # from a Ray process, then exposes those metrics to Prometheus. try: self._metrics_agent.record_metric_points_from_protobuf( request.metrics) except Exception: logger.error(traceback.format_exc()) return reporter_pb2.ReportOCMetricsReply() @staticmethod def _get_cpu_percent(): if IN_KUBERNETES_POD: return k8s_utils.cpu_percent() else: return psutil.cpu_percent() @staticmethod def _get_gpu_usage(): global enable_gpu_usage_check if gpustat is None or not enable_gpu_usage_check: return [] gpu_utilizations = [] gpus = [] try: gpus = gpustat.new_query().gpus except Exception as e: logger.debug(f"gpustat failed to retrieve GPU information: {e}") # gpustat calls pynvml.nvmlInit() # On machines without GPUs, this can run subprocesses that spew to # stderr. Then with log_to_driver=True, we get log spew from every # single raylet. To avoid this, disable the GPU usage check on # certain errors. # https://github.com/ray-project/ray/issues/14305 # https://github.com/ray-project/ray/pull/21686 if type(e).__name__ == "NVMLError_DriverNotLoaded": enable_gpu_usage_check = False for gpu in gpus: # Note the keys in this dict have periods which throws # off javascript so we change .s to _s gpu_data = { "_".join(key.split(".")): val for key, val in gpu.entry.items() } gpu_utilizations.append(gpu_data) return gpu_utilizations @staticmethod def _get_boot_time(): if IN_KUBERNETES_POD: # Return start time of container entrypoint return psutil.Process(pid=1).create_time() else: return psutil.boot_time() @staticmethod def _get_network_stats(): ifaces = [ v for k, v in psutil.net_io_counters(pernic=True).items() if k[0] == "e" ] sent = sum((iface.bytes_sent for iface in ifaces)) recv = sum((iface.bytes_recv for iface in ifaces)) return sent, recv @staticmethod def _get_mem_usage(): total = ray._private.utils.get_system_memory() used = ray._private.utils.get_used_memory() available = total - used percent = round(used / total, 3) * 100 return total, available, percent, used @staticmethod def _get_disk_usage(): if IN_KUBERNETES_POD and not ENABLE_K8S_DISK_USAGE: # If in a K8s pod, disable disk display by passing in dummy values. return { "/": psutil._common.sdiskusage(total=1, used=0, free=1, percent=0.0) } if sys.platform == "win32": root = psutil.disk_partitions()[0].mountpoint else: root = os.sep tmp = ray._private.utils.get_user_temp_dir() return { "/": psutil.disk_usage(root), tmp: psutil.disk_usage(tmp), } @staticmethod def _get_disk_io_stats(): stats = psutil.disk_io_counters() return ( stats.read_bytes, stats.write_bytes, stats.read_count, stats.write_count, ) def _get_workers(self): raylet_proc = self._get_raylet_proc() if raylet_proc is None: return [] else: workers = set(raylet_proc.children()) # Remove the current process (reporter agent), which is also a child of # the Raylet. workers.discard(psutil.Process()) self._workers = workers return [ w.as_dict(attrs=[ "pid", "create_time", "cpu_percent", "cpu_times", "cmdline", "memory_info", "memory_full_info", ]) for w in self._workers if w.status() != psutil.STATUS_ZOMBIE ] @staticmethod def _get_raylet_proc(): try: curr_proc = psutil.Process() # Here, parent is always raylet because the # dashboard agent is a child of the raylet process. parent = curr_proc.parent() if parent is not None: if parent.pid == 1: return None if parent.status() == psutil.STATUS_ZOMBIE: return None return parent except (psutil.AccessDenied, ProcessLookupError): pass return None def _get_raylet(self): raylet_proc = self._get_raylet_proc() if raylet_proc is None: return {} else: return raylet_proc.as_dict(attrs=[ "pid", "create_time", "cpu_percent", "cpu_times", "cmdline", "memory_info", "memory_full_info", ]) def _get_load_avg(self): if sys.platform == "win32": cpu_percent = psutil.cpu_percent() load = (cpu_percent, cpu_percent, cpu_percent) else: load = os.getloadavg() per_cpu_load = tuple((round(x / self._cpu_counts[0], 2) for x in load)) return load, per_cpu_load @staticmethod def _compute_speed_from_hist(hist): while len(hist) > 7: hist.pop(0) then, prev_stats = hist[0] now, now_stats = hist[-1] time_delta = now - then return tuple( (y - x) / time_delta for x, y in zip(prev_stats, now_stats)) def _get_all_stats(self): now = dashboard_utils.to_posix_time(datetime.datetime.utcnow()) network_stats = self._get_network_stats() self._network_stats_hist.append((now, network_stats)) network_speed_stats = self._compute_speed_from_hist( self._network_stats_hist) disk_stats = self._get_disk_io_stats() self._disk_io_stats_hist.append((now, disk_stats)) disk_speed_stats = self._compute_speed_from_hist( self._disk_io_stats_hist) return { "now": now, "hostname": self._hostname, "ip": self._ip, "cpu": self._get_cpu_percent(), "cpus": self._cpu_counts, "mem": self._get_mem_usage(), "workers": self._get_workers(), "raylet": self._get_raylet(), "bootTime": self._get_boot_time(), "loadAvg": self._get_load_avg(), "disk": self._get_disk_usage(), "disk_io": disk_stats, "disk_io_speed": disk_speed_stats, "gpus": self._get_gpu_usage(), "network": network_stats, "network_speed": network_speed_stats, # Deprecated field, should be removed with frontend. "cmdline": self._get_raylet().get("cmdline", []), } def _record_stats(self, stats, cluster_stats): records_reported = [] ip = stats["ip"] # -- Instance count of cluster -- # Only report cluster stats on head node if "autoscaler_report" in cluster_stats and self._is_head_node: active_nodes = cluster_stats["autoscaler_report"]["active_nodes"] for node_type, active_node_count in active_nodes.items(): records_reported.append( Record( gauge=METRICS_GAUGES["cluster_active_nodes"], value=active_node_count, tags={"node_type": node_type}, )) failed_nodes = cluster_stats["autoscaler_report"]["failed_nodes"] failed_nodes_dict = {} for node_ip, node_type in failed_nodes: if node_type in failed_nodes_dict: failed_nodes_dict[node_type] += 1 else: failed_nodes_dict[node_type] = 1 for node_type, failed_node_count in failed_nodes_dict.items(): records_reported.append( Record( gauge=METRICS_GAUGES["cluster_failed_nodes"], value=failed_node_count, tags={"node_type": node_type}, )) pending_nodes = cluster_stats["autoscaler_report"]["pending_nodes"] pending_nodes_dict = {} for node_ip, node_type, status_message in pending_nodes: if node_type in pending_nodes_dict: pending_nodes_dict[node_type] += 1 else: pending_nodes_dict[node_type] = 1 for node_type, pending_node_count in pending_nodes_dict.items(): records_reported.append( Record( gauge=METRICS_GAUGES["cluster_pending_nodes"], value=pending_node_count, tags={"node_type": node_type}, )) # -- CPU per node -- cpu_usage = float(stats["cpu"]) cpu_record = Record( gauge=METRICS_GAUGES["node_cpu_utilization"], value=cpu_usage, tags={"ip": ip}, ) cpu_count, _ = stats["cpus"] cpu_count_record = Record(gauge=METRICS_GAUGES["node_cpu_count"], value=cpu_count, tags={"ip": ip}) # -- Mem per node -- mem_total, mem_available, _, mem_used = stats["mem"] mem_used_record = Record(gauge=METRICS_GAUGES["node_mem_used"], value=mem_used, tags={"ip": ip}) mem_available_record = Record( gauge=METRICS_GAUGES["node_mem_available"], value=mem_available, tags={"ip": ip}, ) mem_total_record = Record(gauge=METRICS_GAUGES["node_mem_total"], value=mem_total, tags={"ip": ip}) # -- GPU per node -- gpus = stats["gpus"] gpus_available = len(gpus) if gpus_available: gpus_utilization, gram_used, gram_total = 0, 0, 0 for gpu in gpus: # Consume GPU may not report its utilization. if gpu["utilization_gpu"] is not None: gpus_utilization += gpu["utilization_gpu"] gram_used += gpu["memory_used"] gram_total += gpu["memory_total"] gram_available = gram_total - gram_used gpus_available_record = Record( gauge=METRICS_GAUGES["node_gpus_available"], value=gpus_available, tags={"ip": ip}, ) gpus_utilization_record = Record( gauge=METRICS_GAUGES["node_gpus_utilization"], value=gpus_utilization, tags={"ip": ip}, ) gram_used_record = Record(gauge=METRICS_GAUGES["node_gram_used"], value=gram_used, tags={"ip": ip}) gram_available_record = Record( gauge=METRICS_GAUGES["node_gram_available"], value=gram_available, tags={"ip": ip}, ) records_reported.extend([ gpus_available_record, gpus_utilization_record, gram_used_record, gram_available_record, ]) # -- Disk per node -- disk_io_stats = stats["disk_io"] disk_read_record = Record( gauge=METRICS_GAUGES["node_disk_io_read"], value=disk_io_stats[0], tags={"ip": ip}, ) disk_write_record = Record( gauge=METRICS_GAUGES["node_disk_io_write"], value=disk_io_stats[1], tags={"ip": ip}, ) disk_read_count_record = Record( gauge=METRICS_GAUGES["node_disk_io_read_count"], value=disk_io_stats[2], tags={"ip": ip}, ) disk_write_count_record = Record( gauge=METRICS_GAUGES["node_disk_io_write_count"], value=disk_io_stats[3], tags={"ip": ip}, ) disk_io_speed_stats = stats["disk_io_speed"] disk_read_speed_record = Record( gauge=METRICS_GAUGES["node_disk_io_read_speed"], value=disk_io_speed_stats[0], tags={"ip": ip}, ) disk_write_speed_record = Record( gauge=METRICS_GAUGES["node_disk_io_write_speed"], value=disk_io_speed_stats[1], tags={"ip": ip}, ) disk_read_iops_record = Record( gauge=METRICS_GAUGES["node_disk_read_iops"], value=disk_io_speed_stats[2], tags={"ip": ip}, ) disk_write_iops_record = Record( gauge=METRICS_GAUGES["node_disk_write_iops"], value=disk_io_speed_stats[3], tags={"ip": ip}, ) used, free = 0, 0 for entry in stats["disk"].values(): used += entry.used free += entry.free disk_utilization = float(used / (used + free)) * 100 disk_usage_record = Record(gauge=METRICS_GAUGES["node_disk_usage"], value=used, tags={"ip": ip}) disk_free_record = Record(gauge=METRICS_GAUGES["node_disk_free"], value=free, tags={"ip": ip}) disk_utilization_percentage_record = Record( gauge=METRICS_GAUGES["node_disk_utilization_percentage"], value=disk_utilization, tags={"ip": ip}, ) # -- Network speed (send/receive) stats per node -- network_stats = stats["network"] network_sent_record = Record( gauge=METRICS_GAUGES["node_network_sent"], value=network_stats[0], tags={"ip": ip}, ) network_received_record = Record( gauge=METRICS_GAUGES["node_network_received"], value=network_stats[1], tags={"ip": ip}, ) # -- Network speed (send/receive) per node -- network_speed_stats = stats["network_speed"] network_send_speed_record = Record( gauge=METRICS_GAUGES["node_network_send_speed"], value=network_speed_stats[0], tags={"ip": ip}, ) network_receive_speed_record = Record( gauge=METRICS_GAUGES["node_network_receive_speed"], value=network_speed_stats[1], tags={"ip": ip}, ) raylet_stats = stats["raylet"] if raylet_stats: raylet_pid = str(raylet_stats["pid"]) # -- raylet CPU -- raylet_cpu_usage = float(raylet_stats["cpu_percent"]) * 100 records_reported.append( Record( gauge=METRICS_GAUGES["raylet_cpu"], value=raylet_cpu_usage, tags={ "ip": ip, "pid": raylet_pid }, )) # -- raylet mem -- raylet_rss = float(raylet_stats["memory_info"].rss) / 1.0e6 records_reported.append( Record( gauge=METRICS_GAUGES["raylet_mem"], value=raylet_rss, tags={ "ip": ip, "pid": raylet_pid }, )) raylet_mem_full_info = raylet_stats.get("memory_full_info") if raylet_mem_full_info is not None: raylet_uss = float(raylet_mem_full_info.uss) / 1.0e6 records_reported.append( Record( gauge=METRICS_GAUGES["raylet_mem_uss"], value=raylet_uss, tags={ "ip": ip, "pid": raylet_pid }, )) workers_stats = stats["workers"] if workers_stats: total_workers_cpu_percentage = 0.0 total_workers_rss = 0.0 total_workers_uss = 0.0 for worker in workers_stats: total_workers_cpu_percentage += float( worker["cpu_percent"]) * 100.0 total_workers_rss += float(worker["memory_info"].rss) / 1.0e6 worker_mem_full_info = worker.get("memory_full_info") if worker_mem_full_info is not None: total_workers_uss += float( worker_mem_full_info.uss) / 1.0e6 records_reported.append( Record( gauge=METRICS_GAUGES["workers_cpu"], value=total_workers_cpu_percentage, tags={"ip": ip}, )) records_reported.append( Record( gauge=METRICS_GAUGES["workers_mem"], value=total_workers_rss, tags={"ip": ip}, )) if total_workers_uss > 0.0: records_reported.append( Record( gauge=METRICS_GAUGES["workers_mem_uss"], value=total_workers_uss, tags={"ip": ip}, )) records_reported.extend([ cpu_record, cpu_count_record, mem_used_record, mem_available_record, mem_total_record, disk_read_record, disk_write_record, disk_read_count_record, disk_write_count_record, disk_read_speed_record, disk_write_speed_record, disk_read_iops_record, disk_write_iops_record, disk_usage_record, disk_free_record, disk_utilization_percentage_record, network_sent_record, network_received_record, network_send_speed_record, network_receive_speed_record, ]) return records_reported async def _perform_iteration(self, publisher): """Get any changes to the log files and push updates to kv.""" while True: try: formatted_status_string = internal_kv._internal_kv_get( DEBUG_AUTOSCALING_STATUS) stats = self._get_all_stats() # Report stats only when metrics collection is enabled. if not self._metrics_collection_disabled: cluster_stats = (json.loads( formatted_status_string.decode()) if formatted_status_string else {}) records_reported = self._record_stats(stats, cluster_stats) self._metrics_agent.record_reporter_stats(records_reported) await publisher.publish_resource_usage(self._key, jsonify_asdict(stats)) except Exception: logger.exception("Error publishing node physical stats.") await asyncio.sleep(reporter_consts.REPORTER_UPDATE_INTERVAL_MS / 1000) async def run(self, server): if server: reporter_pb2_grpc.add_ReporterServiceServicer_to_server( self, server) await self._perform_iteration(self._dashboard_agent.publisher) @staticmethod def is_minimal_module(): return False