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external_package.py
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external_package.py
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# Copyright (c) 2018 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import time
import socket
import hashlib
from owca.metrics import Metric
from owca.detectors import (TasksMeasurements, ContentionAnomaly,
ContendedResource, AnomalyDetector, TasksResources, TasksLabels)
from owca.platforms import Platform
import logging
log = logging.getLogger(__name__)
class ExampleDetector(AnomalyDetector):
"""Simulation for anomaly detection based on deterministic
schema based on phases in cycle"""
def __init__(self, cycle_length: int = 90, skew: bool = False):
self.cycle_length = cycle_length
self.skew = skew
def detect(self, platform: Platform,
tasks_measurements: TasksMeasurements,
tasks_resources: TasksResources,
tasks_labels: TasksLabels
):
anomalies = []
# Based on hostname generate skew of phase for different hosts,
# to simulate contention alerting firing from multiple sources at different time.
if self.skew:
phase_skew = sum(hashlib.sha256(socket.gethostname().encode('UTF-8')).digest())
else:
phase_skew = 0
# Find out moment of cycle.
second_of_cycle = int(time.time() + phase_skew) % self.cycle_length
# Make sure we have enough tasks (to simulate contention).
if len(tasks_measurements) >= 10:
resources = [
ContendedResource.CPUS,
ContendedResource.LLC,
ContendedResource.MEMORY_BW,
]
# Define phases of simulation.
if second_of_cycle < 10:
# Single contention on one resource with single contender task.
tasks_count = 1
resources_count = 1
metrics_count = 1
elif second_of_cycle < 20:
# Single contention on two resources with single contender task
# (with two additional metrics)
tasks_count = 1
resources_count = 2
metrics_count = 2
elif second_of_cycle < 30:
# Single contention on three resources with two contender tasks
# (with two additional metrics each)
tasks_count = 1
resources_count = 3
metrics_count = 2
elif second_of_cycle < 40:
# Two contentions each on two resources with two contender tasks
# (with two additional metrics each)
tasks_count = 2
resources_count = 2
metrics_count = 3
elif second_of_cycle < 50:
# Multiple (three) contentions each on single resource with single contender task
# (with two additional metrics each)
tasks_count = 3
resources_count = 1
metrics_count = 1
else:
# Contention free period.
resources_count = 0
tasks_count = 0
metrics_count = 0
log.info('detector simulation: tasks=%d resources=%d metrics=%d!',
tasks_count, resources_count, metrics_count)
# Make sure that we choose tasks pairs for generating faked contention.
task_ids = sorted(tasks_measurements.keys())
# Predefined pairs of contended and contending tasks.
task_pairs = [
(task_ids[0], task_ids[1:3]), # 0 vs 1,2
(task_ids[3], task_ids[4:5]), # 3 vs 4
(task_ids[6], task_ids[7:10]), # 6 vs 7,8,9
]
# Generate multiple contention based on scenario phase.
for resource_idx in range(resources_count):
for task_pair_idx in range(tasks_count):
contended_task_id, contending_task_ids = task_pairs[task_pair_idx]
resource = resources[resource_idx]
metrics = [
Metric(name="cpu_threshold_%d" % i, value="%d" % (i+1)*10, type="gauge")
for i in range(metrics_count)
]
anomalies.append(
ContentionAnomaly(
contended_task_id=contended_task_id,
contending_task_ids=contending_task_ids,
resource=resource,
metrics=metrics,
)
)
else:
log.warning('not enough tasks %d to simulate contention!', len(tasks_measurements))
debugging_metrics = [
Metric(
name='second_of_cycle',
value=second_of_cycle,
type="gauge",
)
]
return anomalies, debugging_metrics