def _iterate_body(self, containers, platform, tasks_data, common_labels):
"""Detector callback body."""
# Call Detector's detect function.
detection_start = time.time()
anomalies, extra_metrics = self._detector.detect(platform, tasks_data)
detection_duration = time.time() - detection_start
profiler.register_duration('detect', detection_duration)
log.debug('Anomalies detected: %d', len(anomalies))
# Prepare anomaly metrics
anomaly_metrics = convert_anomalies_to_metrics(anomalies, tasks_data)
update_anomalies_metrics_with_task_information(anomaly_metrics,
tasks_data)
# Prepare and send all output (anomalies) metrics.
anomalies_package = MetricPackage(self._anomalies_storage)
anomalies_package.add_metrics(
anomaly_metrics, extra_metrics,
self._anomalies_statistics.get_metrics(anomalies))
anomalies_package.send(common_labels)
def _iterate_body(self,
containers, platform,
tasks_measurements, tasks_resources,
tasks_labels, common_labels):
"""Allocator callback body."""
current_allocations = _get_tasks_allocations(containers)
# Allocator callback
allocate_start = time.time()
new_allocations, anomalies, extra_metrics = self._allocator.allocate(
platform, tasks_measurements, tasks_resources, tasks_labels,
current_allocations)
allocate_duration = time.time() - allocate_start
# Validate callback output
_validate_allocate_return_vals(new_allocations, anomalies, extra_metrics)
log.debug('Anomalies detected: %d', len(anomalies))
log.debug('Current allocations: %s', current_allocations)
# Create context aware allocations objects for current allocations.
current_allocations_values = TasksAllocationsValues.create(
self._rdt_enabled, current_allocations, self._containers_manager.containers, platform)
# Handle allocations: calculate changeset and target allocations.
allocations_changeset_values = None
target_allocations_values = current_allocations_values
try:
# Special validation step needed for Kubernetes.
validate_shares_allocation_for_kubernetes(tasks=containers.keys(),
allocations=new_allocations)
# Create and validate context aware allocations objects for new allocations.
log.debug('New allocations: %s', new_allocations)
new_allocations_values = TasksAllocationsValues.create(
self._rdt_enabled, new_allocations, self._containers_manager.containers, platform)
new_allocations_values.validate()
# Calculate changeset and target_allocations.
if new_allocations_values is not None:
target_allocations_values, allocations_changeset_values = \
new_allocations_values.calculate_changeset(current_allocations_values)
target_allocations_values.validate()
self._allocations_counter += len(new_allocations)
except InvalidAllocations as e:
# Handle any allocation validation error.
# Log errors and restore current to generate proper metrics.
log.error('Invalid allocations: %s', str(e))
log.warning('Ignoring all allocations in this iteration due to validation error!')
self._allocations_errors += 1
target_allocations_values = current_allocations_values
# Handle allocations: perform allocations based on changeset.
if allocations_changeset_values:
log.debug('Allocations changeset: %s', allocations_changeset_values)
log.info('Performing allocations on %d tasks.', len(
allocations_changeset_values))
allocations_changeset_values.perform_allocations()
# Prepare anomaly metrics.
anomaly_metrics = convert_anomalies_to_metrics(anomalies, tasks_labels)
update_anomalies_metrics_with_task_information(anomaly_metrics, tasks_labels)
# Store anomalies information
anomalies_package = MetricPackage(self._anomalies_storage)
anomalies_package.add_metrics(
anomaly_metrics,
extra_metrics,
self._anomalies_statistics.get_metrics(anomalies)
)
anomalies_package.send(common_labels)
# Prepare allocations metrics.
allocations_metrics = target_allocations_values.generate_metrics()
allocations_statistic_metrics = _get_allocations_statistics_metrics(
self._allocations_counter, self._allocations_errors, allocate_duration)
# Store allocations metrics.
allocations_package = MetricPackage(self._allocations_storage)
allocations_package.add_metrics(
allocations_metrics,
extra_metrics,
allocations_statistic_metrics,
)
allocations_package.send(common_labels)
