95 lines
4.0 KiB
Python
95 lines
4.0 KiB
Python
# Copyright 2022 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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'Prepares descriptors and timeseries for network-level route metrics.'
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import itertools
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import logging
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from . import MetricDescriptor, TimeSeries, register_timeseries
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DESCRIPTOR_ATTRS = {
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'network/routes_dynamic_used':
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'Dynamic routes limit per network',
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'network/routes_dynamic_available':
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'Dynamic routes used per network',
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'network/routes_dynamic_used_ratio':
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'Dynamic routes used ratio per network',
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'network/routes_static_used':
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'Static routes limit per network',
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'project/routes_dynamic_used':
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'Dynamic routes limit per project',
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'project/routes_dynamic_available':
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'Dynamic routes used per project',
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'project/routes_dynamic_used_ratio':
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'Dynamic routes used ratio per project',
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'project/routes_static_used':
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'Static routes limit per project',
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'project/routes_static_available':
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'Static routes used per project',
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'project/routes_static_used_ratio':
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'Static routes used ratio per project'
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}
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LIMITS = {'ROUTES': 250, 'ROUTES_DYNAMIC': 100}
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LOGGER = logging.getLogger('net-dash.timeseries.routes')
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def _dynamic(resources):
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'Computes network-level timeseries for dynamic routes.'
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for network_id, router_counts in resources['routes_dynamic'].items():
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network = resources['networks'][network_id]
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count = sum(router_counts.values())
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labels = {'project': network['project_id'], 'network': network['name']}
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limit = LIMITS['ROUTES_DYNAMIC']
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yield TimeSeries('network/routes_dynamic_used', count, labels)
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yield TimeSeries('network/routes_dynamic_available', limit, labels)
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yield TimeSeries('network/routes_dynamic_used_ratio', count / limit, labels)
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def _static(resources):
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'Computes network and project-level timeseries for dynamic routes.'
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filter = lambda v: v['next_hop_type'] in ('peering', 'network')
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routes = itertools.filterfalse(filter, resources['routes'].values())
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grouped = itertools.groupby(sorted(routes, key=lambda i: i['network']),
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lambda i: i['network'])
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project_counts = {}
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for network_id, elements in grouped:
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network = resources['networks'].get(network_id)
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count = len(list(elements))
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labels = {'project': network['project_id'], 'network': network['name']}
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yield TimeSeries('network/routes_static_used', count, labels)
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project_counts[network['project_id']] = project_counts.get(
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network['project_id'], 0) + count
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for project_id, count in project_counts.items():
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labels = {'project': project_id}
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quota = resources['quota'][project_id]['global']
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limit = quota.get('ROUTES', LIMITS['ROUTES'])
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yield TimeSeries('project/routes_static_used', count, labels)
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yield TimeSeries('project/routes_static_available', limit, labels)
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yield TimeSeries('project/routes_static_used_ratio', count / limit, labels)
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@register_timeseries
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def timeseries(resources):
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'Returns used/available/ratio timeseries by network and project.'
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LOGGER.info('timeseries')
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# return descriptors
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for dtype, name in DESCRIPTOR_ATTRS.items():
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labels = ('project') if dtype.startswith('project') else ('project',
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'network')
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yield MetricDescriptor(dtype, name, labels, dtype.endswith('ratio'))
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# chain static and dynamic route timeseries then return each one individually
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results = itertools.chain(_static(resources), _dynamic(resources))
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for result in results:
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yield result
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