"""Prometheus monitoring queries.""" # pylint: disable=too-few-public-methods import requests import strawberry from dataclasses import dataclass from typing import Optional, Annotated, Union, List, Tuple from datetime import datetime, timedelta PROMETHEUS_URL = "http://localhost:9001" @strawberry.type @dataclass class MonitoringValue: timestamp: datetime value: str @strawberry.type @dataclass class MonitoringMetric: metric_id: str values: List[MonitoringValue] @strawberry.type class MonitoringQueryError: error: str @strawberry.type class MonitoringValues: values: List[MonitoringValue] @strawberry.type class MonitoringMetrics: metrics: List[MonitoringMetric] MonitoringValuesResult = Annotated[ Union[MonitoringValues, MonitoringQueryError], strawberry.union("MonitoringValuesResult"), ] MonitoringMetricsResult = Annotated[ Union[MonitoringMetrics, MonitoringQueryError], strawberry.union("MonitoringMetricsResult"), ] class MonitoringQueries: @staticmethod def _send_range_query( query: str, start: int, end: int, step: int, result_type: Optional[str] = None ) -> Union[dict, MonitoringQueryError]: try: response = requests.get( f"{PROMETHEUS_URL}/api/v1/query_range", params={ "query": query, "start": start, "end": end, "step": step, }, timeout=0.8, ) if response.status_code != 200: return MonitoringQueryError( error=f"Prometheus returned unexpected HTTP status code. Error: {response.text}. The query was {query}" ) json = response.json() if result_type and json["data"]["resultType"] != result_type: return MonitoringQueryError( error="Unexpected resultType returned from Prometheus, request failed" ) return json["data"] except Exception as error: return MonitoringQueryError( error=f"Prometheus request failed! Error: {str(error)}" ) @staticmethod def _send_query( query: str, result_type: Optional[str] = None ) -> Union[dict, MonitoringQueryError]: try: response = requests.get( f"{PROMETHEUS_URL}/api/v1/query", params={ "query": query, }, timeout=0.8, ) if response.status_code != 200: return MonitoringQueryError( error=f"Prometheus returned unexpected HTTP status code. Error: {response.text}. The query was {query}" ) json = response.json() if result_type and json["data"]["resultType"] != result_type: return MonitoringQueryError( error="Unexpected resultType returned from Prometheus, request failed" ) return json["data"] except Exception as error: return MonitoringQueryError( error=f"Prometheus request failed! Error: {str(error)}" ) @staticmethod def _prometheus_value_to_monitoring_value(x: Tuple[int, str]): return MonitoringValue(timestamp=datetime.fromtimestamp(x[0]), value=x[1]) @staticmethod def _clean_slice_id(slice_id: str, clean_id: bool) -> str: """Slices come in form of `/slice_name.slice`, we need to remove the `.slice` and `/` part.""" if clean_id: parts = slice_id.split(".")[0].split("/") if len(parts) > 1: return parts[1] else: raise ValueError(f"Incorrect format slice_id: {slice_id}") return slice_id @staticmethod def _prometheus_response_to_monitoring_metrics( response: dict, id_key: str, clean_id: bool = False ) -> List[MonitoringMetric]: if response["resultType"] == "vector": return list( map( lambda x: MonitoringMetric( metric_id=MonitoringQueries._clean_slice_id( x["metric"].get(id_key, "/unknown.slice"), clean_id=clean_id, ), values=[ MonitoringQueries._prometheus_value_to_monitoring_value( x["value"] ) ], ), response["result"], ) ) else: return list( map( lambda x: MonitoringMetric( metric_id=MonitoringQueries._clean_slice_id( x["metric"].get(id_key, "/unknown.slice"), clean_id=clean_id ), values=list( map( MonitoringQueries._prometheus_value_to_monitoring_value, x["values"], ) ), ), response["result"], ) ) @staticmethod def _calculate_offset_and_duration( start: datetime, end: datetime ) -> Tuple[int, int]: """Calculate the offset and duration for Prometheus queries. They mast be in seconds. """ offset = int((datetime.now() - end).total_seconds()) duration = int((end - start).total_seconds()) return offset, duration @staticmethod def cpu_usage_overall( start: Optional[datetime] = None, end: Optional[datetime] = None, step: int = 60, # seconds ) -> MonitoringValuesResult: """ Get CPU information. Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. step (int): Interval in seconds for querying disk usage data. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() start_timestamp = int(start.timestamp()) end_timestamp = int(end.timestamp()) query = '100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)' data = MonitoringQueries._send_range_query( query, start_timestamp, end_timestamp, step, result_type="matrix" ) if isinstance(data, MonitoringQueryError): return data return MonitoringValues( values=list( map( MonitoringQueries._prometheus_value_to_monitoring_value, data["result"][0]["values"], ) ) ) @staticmethod def memory_usage_overall( start: Optional[datetime] = None, end: Optional[datetime] = None, step: int = 60, # seconds ) -> MonitoringValuesResult: """ Get memory usage. Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. step (int): Interval in seconds for querying memory usage data. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() start_timestamp = int(start.timestamp()) end_timestamp = int(end.timestamp()) query = "100 - (100 * (node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes))" data = MonitoringQueries._send_range_query( query, start_timestamp, end_timestamp, step, result_type="matrix" ) if isinstance(data, MonitoringQueryError): return data return MonitoringValues( values=list( map( MonitoringQueries._prometheus_value_to_monitoring_value, data["result"][0]["values"], ) ) ) @staticmethod def memory_usage_max_by_slice( start: Optional[datetime] = None, end: Optional[datetime] = None, ) -> MonitoringMetricsResult: """ Get maximum memory usage for each service (i.e. systemd slice). Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() offset, duration = MonitoringQueries._calculate_offset_and_duration(start, end) if offset == 0: query = f'max_over_time((container_memory_rss{{id!~".*slice.*slice", id=~".*slice"}}+container_memory_swap{{id!~".*slice.*slice", id=~".*slice"}})[{duration}s:])' else: query = f'max_over_time((container_memory_rss{{id!~".*slice.*slice", id=~".*slice"}}+container_memory_swap{{id!~".*slice.*slice", id=~".*slice"}})[{duration}s:] offset {offset}s)' data = MonitoringQueries._send_query(query, result_type="vector") if isinstance(data, MonitoringQueryError): return data return MonitoringMetrics( metrics=MonitoringQueries._prometheus_response_to_monitoring_metrics( data, "id", clean_id=True ) ) @staticmethod def memory_usage_average_by_slice( start: Optional[datetime] = None, end: Optional[datetime] = None, ) -> MonitoringMetricsResult: """ Get average memory usage for each service (i.e. systemd slice). Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() offset, duration = MonitoringQueries._calculate_offset_and_duration(start, end) if offset == 0: query = f'avg_over_time((container_memory_rss{{id!~".*slice.*slice", id=~".*slice"}}+container_memory_swap{{id!~".*slice.*slice", id=~".*slice"}})[{duration}s:])' else: query = f'avg_over_time((container_memory_rss{{id!~".*slice.*slice", id=~".*slice"}}+container_memory_swap{{id!~".*slice.*slice", id=~".*slice"}})[{duration}s:] offset {offset}s)' data = MonitoringQueries._send_query(query, result_type="vector") if isinstance(data, MonitoringQueryError): return data return MonitoringMetrics( metrics=MonitoringQueries._prometheus_response_to_monitoring_metrics( data, "id", clean_id=True ) ) @staticmethod def disk_usage_overall( start: Optional[datetime] = None, end: Optional[datetime] = None, step: int = 60, # seconds ) -> MonitoringMetricsResult: """ Get disk usage information. Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. step (int): Interval in seconds for querying disk usage data. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() start_timestamp = int(start.timestamp()) end_timestamp = int(end.timestamp()) query = """100 - (100 * sum by (device) (node_filesystem_avail_bytes{fstype!="rootfs",fstype!="ramfs",fstype!="tmpfs",mountpoint!="/efi"}) / sum by (device) (node_filesystem_size_bytes{fstype!="rootfs",fstype!="ramfs",fstype!="tmpfs",mountpoint!="/efi"}))""" data = MonitoringQueries._send_range_query( query, start_timestamp, end_timestamp, step, result_type="matrix" ) if isinstance(data, MonitoringQueryError): return data return MonitoringMetrics( metrics=MonitoringQueries._prometheus_response_to_monitoring_metrics( data, "device" ) ) @staticmethod def network_usage_overall( start: Optional[datetime] = None, end: Optional[datetime] = None, step: int = 60, # seconds ) -> MonitoringMetricsResult: """ Get network usage information for both download and upload. Args: start (datetime, optional): The start time. Defaults to 20 minutes ago if not provided. end (datetime, optional): The end time. Defaults to current time if not provided. step (int): Interval in seconds for querying network data. """ if start is None: start = datetime.now() - timedelta(minutes=20) if end is None: end = datetime.now() start_timestamp = int(start.timestamp()) end_timestamp = int(end.timestamp()) query = """ label_replace(rate(node_network_receive_bytes_total{device!="lo"}[5m]), "direction", "receive", "device", ".*") or label_replace(rate(node_network_transmit_bytes_total{device!="lo"}[5m]), "direction", "transmit", "device", ".*") """ data = MonitoringQueries._send_range_query( query, start_timestamp, end_timestamp, step, result_type="matrix" ) if isinstance(data, MonitoringQueryError): return data return MonitoringMetrics( metrics=MonitoringQueries._prometheus_response_to_monitoring_metrics( data, "direction" ) )