blob: a5db6f94d4f23d427502844a1732b051ef3bf08f [file] [log] [blame]
#!/usr/bin/env python2
# Copyright 2015 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Adjust pool balances to cover DUT shortfalls.
This command takes all broken DUTs in a specific pool for specific
models and swaps them with working DUTs taken from a selected pool
of spares. The command is meant primarily for replacing broken DUTs
in critical pools like BVT or CQ, but it can also be used to adjust
pool sizes, or to create or remove pools.
usage: [ options ] POOL MODEL [ MODEL ... ]
positional arguments:
POOL Name of the pool to balance
MODEL Names of models to balance
optional arguments:
-h, --help show this help message and exit
-t COUNT, --total COUNT
Set the number of DUTs in the pool to the specified
count for every MODEL
-a COUNT, --grow COUNT
Add the specified number of DUTs to the pool for every
-d COUNT, --shrink COUNT
Remove the specified number of DUTs from the pool for
every MODEL
-s POOL, --spare POOL
Pool from which to draw replacement spares (default:
-p PHASE, --phase PHASE
Phase to restrict the balance pool operation to
--sku SKU The specific SKU we intend to swap with
-n, --dry-run Report actions to take in the form of shell commands
The command attempts to remove all broken DUTs from the target POOL
for every MODEL, and replace them with enough working DUTs taken
from the spare pool to bring the strength of POOL to the requested
total COUNT.
If no COUNT options are supplied (i.e. there are no --total, --grow,
or --shrink options), the command will maintain the current totals of
DUTs for every MODEL in the target POOL.
If not enough working spares are available, broken DUTs may be left
in the pool to keep the pool at the target COUNT.
When reducing pool size, working DUTs will be returned after broken
DUTs, if it's necessary to achieve the target COUNT.
import argparse
import os
import re
import sys
import time
import common
from autotest_lib.server import constants
from autotest_lib.server import site_utils
from autotest_lib.server.cros.dynamic_suite import frontend_wrappers
from autotest_lib.server.lib import status_history
from autotest_lib.site_utils import lab_inventory
from autotest_lib.utils import labellib
from chromite.lib import metrics
from chromite.lib import parallel
#This must be imported after chromite.lib.metrics
from infra_libs import ts_mon
_POOL_PREFIX = constants.Labels.POOL_PREFIX
# This is the ratio of all models we should calculate the default max
# number of broken models against. It seemed like the best choice that
# was neither too strict nor lax.
_ALL_CRITICAL_POOLS = 'all_critical_pools'
# _VALID_POOL_PATTERN - Regular expression matching pool names that will
# be accepted on the command line.
# Note: This pattern was selected merely to recognize all existing pool
# names; there's no underlying technical restriction motivating this
# pattern. No reasonable request to add more special characters to the
# allowed set should be refused.
_VALID_POOL_PATTERN = re.compile('^[a-zA-z0-9_\-]+$')
def _log_message(message, *args):
"""Log a message with optional format arguments to stdout.
This function logs a single line to stdout, with formatting
if necessary, and without adornments.
If `*args` are supplied, the message will be formatted using
the arguments.
@param message Message to be logged, possibly after formatting.
@param args Format arguments. If empty, the message is logged
without formatting.
if args:
message = message % args
sys.stdout.write('%s\n' % message)
def _log_info(dry_run, message, *args):
"""Log information in a dry-run dependent fashion.
This function logs a single line to stdout, with formatting
if necessary. When logging for a dry run, the message is
printed as a shell comment, rather than as unadorned text.
If `*args` are supplied, the message will be formatted using
the arguments.
@param message Message to be logged, possibly after formatting.
@param args Format arguments. If empty, the message is logged
without formatting.
if dry_run:
message = '# ' + message
_log_message(message, *args)
def _log_error(message, *args):
"""Log an error to stderr, with optional format arguments.
This function logs a single line to stderr, prefixed to indicate
that it is an error message.
If `*args` are supplied, the message will be formatted using
the arguments.
@param message Message to be logged, possibly after formatting.
@param args Format arguments. If empty, the message is logged
without formatting.
if args:
message = message % args
sys.stderr.write('ERROR: %s\n' % message)
class _DUTPool(object):
"""Information about a pool of DUTs matching given labels.
This class collects information about all DUTs for a given pool and matching
the given labels, and divides them into three categories:
+ Working - the DUT is working for testing, and not locked.
+ Broken - the DUT is unable to run tests, or it is locked.
+ Ineligible - the DUT is not available to be removed from this pool. The
DUT may be either working or broken.
DUTs with more than one pool: label are ineligible for exchange
during balancing. This is done for the sake of chameleon hosts,
which must always be assigned to pool:suites. These DUTs are
always marked with pool:chameleon to prevent their reassignment.
TODO(jrbarnette): The use of `pool:chamelon` (instead of just
the `chameleon` label is a hack that should be eliminated.
_DUTPool instances are used to track both main pools that need
to be resupplied with working DUTs and spare pools that supply
those DUTs.
@property pool Name of the pool associated with
this pool of DUTs.
@property labels Labels that constrain the DUTs to consider.
@property working_hosts The list of this pool's working DUTs.
@property broken_hosts The list of this pool's broken DUTs.
@property ineligible_hosts The list of this pool's ineligible DUTs.
@property pool_labels A list of labels that identify a DUT as part
of this pool.
@property total_hosts The total number of hosts in pool.
def __init__(self, afe, pool, labels, start_time, end_time):
self.pool = pool
self.labels = labellib.LabelsMapping(labels)
self.labels['pool'] = pool
self._pool_labels = [_POOL_PREFIX + self.pool]
self.working_hosts = []
self.broken_hosts = []
self.ineligible_hosts = []
self.total_hosts = self._get_hosts(afe, start_time, end_time)
def _get_hosts(self, afe, start_time, end_time):
all_histories = status_history.HostJobHistory.get_multiple_histories(
afe, start_time, end_time, self.labels.getlabels())
for h in all_histories:
host =
host_pools = [l for l in host.labels
if l.startswith(_POOL_PREFIX)]
if len(host_pools) != 1:
diag = h.last_diagnosis()[0]
if (diag == status_history.WORKING and
not host.locked):
return len(all_histories)
def pool_labels(self):
"""Return the AFE labels that identify this pool.
The returned labels are the labels that must be removed
to remove a DUT from the pool, or added to add a DUT.
@return A list of AFE labels suitable for AFE.add_labels()
or AFE.remove_labels().
return self._pool_labels
def calculate_spares_needed(self, target_total):
"""Calculate and log the spares needed to achieve a target.
Return how many working spares are needed to achieve the
given `target_total` with all DUTs working.
The spares count may be positive or negative. Positive
values indicate spares are needed to replace broken DUTs in
order to reach the target; negative numbers indicate that
no spares are needed, and that a corresponding number of
working devices can be returned.
If the new target total would require returning ineligible
DUTs, an error is logged, and the target total is adjusted
so that those DUTs are not exchanged.
@param target_total The new target pool size.
@return The number of spares needed.
num_ineligible = len(self.ineligible_hosts)
spares_needed = target_total >= num_ineligible
'True for each pool/model which requests more DUTs than supplied',
# TODO(jrbarnette) The 'board' field is a legacy. We need
# to leave it here until we do the extra work Monarch
# requires to delete a field.
not spares_needed,
'pool': self.pool,
'board': self.labels.get('model', ''),
'model': self.labels.get('model', ''),
if not spares_needed:
'%s pool (%s): Target of %d is below minimum of %d DUTs.',
self.pool, self.labels, target_total, num_ineligible,
_log_error('Adjusting target to %d DUTs.', num_ineligible)
target_total = num_ineligible
_log_message('%s %s pool: Target of %d is above minimum.',
self.labels.get('model', ''), self.pool, target_total)
adjustment = target_total - self.total_hosts
return len(self.broken_hosts) + adjustment
def allocate_surplus(self, num_broken):
"""Allocate a list DUTs that can returned as surplus.
Return a list of devices that can be returned in order to
reduce this pool's supply. Broken DUTs will be preferred
over working ones.
The `num_broken` parameter indicates the number of broken
DUTs to be left in the pool. If this number exceeds the
number of broken DUTs actually in the pool, the returned
list will be empty. If this number is negative, it
indicates a number of working DUTs to be returned in
addition to all broken ones.
@param num_broken Total number of broken DUTs to be left in
this pool.
@return A list of DUTs to be returned as surplus.
if num_broken >= 0:
surplus = self.broken_hosts[num_broken:]
return surplus
return (self.broken_hosts +
def _exchange_labels(dry_run, hosts, target_pool, spare_pool):
"""Reassign a list of DUTs from one pool to another.
For all the given hosts, remove all labels associated with
`spare_pool`, and add the labels for `target_pool`.
If `dry_run` is true, perform no changes, but log the `atest`
commands needed to accomplish the necessary label changes.
@param dry_run Whether the logging is for a dry run or
for actual execution.
@param hosts List of DUTs (AFE hosts) to be reassigned.
@param target_pool The `_DUTPool` object from which the hosts
are drawn.
@param spare_pool The `_DUTPool` object to which the hosts
will be added.
_log_info(dry_run, 'Transferring %d DUTs from %s to %s.',
len(hosts), spare_pool.pool, target_pool.pool)
'DUTs transferred between pools',
# TODO(jrbarnette) The 'board' field is a legacy. We need to
# leave it here until we do the extra work Monarch requires to
# delete a field.
'board': target_pool.labels.get('model', ''),
'model': target_pool.labels.get('model', ''),
'source_pool': spare_pool.pool,
'target_pool': target_pool.pool,
if not hosts:
additions = target_pool.pool_labels
removals = spare_pool.pool_labels
for host in hosts:
if not dry_run:
_log_message('Updating host: %s.', host.hostname)
_log_message('atest label remove -m %s %s',
host.hostname, ' '.join(removals))
_log_message('atest label add -m %s %s',
host.hostname, ' '.join(additions))
def _balance_model(arguments, afe, pool, labels, start_time, end_time):
"""Balance one model as requested by command line arguments.
@param arguments Parsed command line arguments.
@param afe AFE object to be used for the changes.
@param pool Pool of the model to be balanced.
@param labels Restrict the balancing operation within DUTs
that have these labels.
@param start_time Start time for HostJobHistory objects in
the DUT pools.
@param end_time End time for HostJobHistory objects in the
DUT pools.
spare_pool = _DUTPool(afe, arguments.spare, labels, start_time, end_time)
main_pool = _DUTPool(afe, pool, labels, start_time, end_time)
target_total = main_pool.total_hosts
if is not None:
target_total =
elif arguments.grow:
target_total += arguments.grow
elif arguments.shrink:
target_total -= arguments.shrink
spares_needed = main_pool.calculate_spares_needed(target_total)
if spares_needed > 0:
spare_duts = spare_pool.working_hosts[:spares_needed]
shortfall = spares_needed - len(spare_duts)
spare_duts = []
shortfall = spares_needed
surplus_duts = main_pool.allocate_surplus(shortfall)
if spares_needed or surplus_duts or arguments.verbose:
dry_run = arguments.dry_run
_log_info(dry_run, 'Balancing %s %s pool:', labels, main_pool.pool)
'Total %d DUTs, %d working, %d broken, %d reserved.',
main_pool.total_hosts, len(main_pool.working_hosts),
len(main_pool.broken_hosts), len(main_pool.ineligible_hosts))
if spares_needed > 0:
add_msg = 'grow pool by %d DUTs' % spares_needed
elif spares_needed < 0:
add_msg = 'shrink pool by %d DUTs' % -spares_needed
add_msg = 'no change to pool size'
_log_info(dry_run, 'Target is %d working DUTs; %s.',
target_total, add_msg)
'%s %s pool has %d spares available for balancing pool %s',
labels, spare_pool.pool, len(spare_pool.working_hosts),
if spares_needed > len(spare_duts):
_log_error('Not enough spares: need %d, only have %d.',
spares_needed, len(spare_duts))
elif shortfall >= 0:
'%s %s pool will return %d broken DUTs, '
'leaving %d still in the pool.',
labels, main_pool.pool,
len(main_pool.broken_hosts) - len(surplus_duts))
'%s %s pool will return %d surplus DUTs, '
'including %d working DUTs.',
labels, main_pool.pool,
len(main_pool.broken_hosts) - shortfall,
if (len(main_pool.broken_hosts) > arguments.max_broken and
not arguments.force_rebalance):
_log_error('%s %s pool: Refusing to act on pool with %d broken DUTs.',
labels, main_pool.pool, len(main_pool.broken_hosts))
_log_error('Please investigate this model to for a bug ')
_log_error('that is bricking devices. Once you have finished your ')
_log_error('investigation, you can force a rebalance with ')
spare_duts = []
surplus_duts = []
if not spare_duts and not surplus_duts:
if arguments.verbose:
_log_info(arguments.dry_run, 'No exchange required.')
_exchange_labels(arguments.dry_run, surplus_duts,
spare_pool, main_pool)
_exchange_labels(arguments.dry_run, spare_duts,
main_pool, spare_pool)
def _parse_command(argv):
"""Parse the command line arguments.
Create an argument parser for this command's syntax, parse the
command line, and return the result of the `ArgumentParser`
`parse_args()` method.
@param argv Standard command line argument vector; `argv[0]` is
assumed to be the command name.
@return Result returned by `ArgumentParser.parse_args()`.
parser = argparse.ArgumentParser(
description='Balance pool shortages from spares on reserve')
'-w', '--web', type=str, default=None,
help='AFE host to use. Default comes from shadow_config.',
count_group = parser.add_mutually_exclusive_group()
count_group.add_argument('-t', '--total', type=int,
metavar='COUNT', default=None,
help='Set the number of DUTs in the '
'pool to the specified count for '
'every MODEL')
count_group.add_argument('-a', '--grow', type=int,
metavar='COUNT', default=None,
help='Add the specified number of DUTs '
'to the pool for every MODEL')
count_group.add_argument('-d', '--shrink', type=int,
metavar='COUNT', default=None,
help='Remove the specified number of DUTs '
'from the pool for every MODEL')
parser.add_argument('-s', '--spare', default=_SPARE_DEFAULT,
help='Pool from which to draw replacement '
'spares (default: pool:%s)' % _SPARE_DEFAULT)
parser.add_argument('-n', '--dry-run', action='store_true',
help='Report actions to take in the form of '
'shell commands')
parser.add_argument('-v', '--verbose', action='store_true',
help='Print more detail about calculations for debug '
parser.add_argument('-m', '--max-broken', default=2, type=int,
help='Only rebalance a pool if it has at most '
'COUNT broken DUTs.')
parser.add_argument('-f', '--force-rebalance', action='store_true',
help='Forcefully rebalance all DUTs in a pool, even '
'if it has a large number of broken DUTs. '
'Before doing this, please investigate whether '
'there is a bug that is bricking devices in the '
parser.add_argument('--production', action='store_true',
help='Treat this as a production run. This will '
'collect metrics.')
help='Rebalance all managed models. This will do a very expensive '
'check to see how many models have at least one broken DUT. '
'To bypass that check, set --max-broken-models to 0.',
'--max-broken-models', default=None, type=int, metavar='COUNT',
help='Only rebalance all models if number of models with broken '
'DUTs in the specified pool is less than COUNT.',
help='Name of the pool to balance. Use %s to balance '
'all critical pools' % _ALL_CRITICAL_POOLS)
parser.add_argument('models', nargs='*', metavar='MODEL',
help='Names of models to balance.')
parser.add_argument('-p', '--phase', metavar='PHASE',
help='Optional phase label to restrict balance '
'operation to.')
parser.add_argument('--sku', type=str,
help='Optional name of sku to restrict to.')
arguments = parser.parse_args(argv[1:])
# Error-check arguments.
if arguments.models and arguments.all_models:
parser.error('Cannot specify individual models on the command line '
'when using --all-models.')
if (arguments.pool == _ALL_CRITICAL_POOLS and
arguments.spare != _SPARE_DEFAULT):
parser.error('Cannot specify --spare pool to be %s when balancing all '
'critical pools.' % _SPARE_DEFAULT)
for p in (arguments.spare, arguments.pool):
if not _VALID_POOL_PATTERN.match(p):
parser.error('Invalid pool name: %s' % p)
return arguments
def infer_balancer_targets(afe, arguments, pools):
"""Take some arguments and translate them to a list of models to balance
@param afe AFE object to be used for taking inventory.
@param arguments Parsed command line arguments.
@param pools The list of pools to balance.
@returns a list of (model, labels) tuples to be balanced
balancer_targets = []
for pool in pools:
if arguments.all_models:
inventory = lab_inventory.get_inventory(afe)
for model in inventory.get_pool_models(pool):
labels = labellib.LabelsMapping()
labels['model'] = model
if arguments.phase:
labels['phase'] = arguments.phase
balancer_targets.append((pool, labels.getlabels()))
for model in arguments.models:
labels = labellib.LabelsMapping()
labels['model'] = model
if arguments.sku:
labels['sku'] = arguments.sku
if arguments.phase:
labels['phase'] = arguments.phase
balancer_targets.append((pool, labels.getlabels()))
return balancer_targets
def main(argv):
"""Standard main routine.
@param argv Command line arguments including `sys.argv[0]`.
arguments = _parse_command(argv)
if arguments.production:
metrics_manager = site_utils.SetupTsMonGlobalState('balance_pools',
metrics_manager = site_utils.TrivialContextManager()
with metrics_manager:
with metrics.SuccessCounter('chromeos/autotest/balance_pools/runs'):
end_time = time.time()
start_time = end_time - 24 * 60 * 60
afe = frontend_wrappers.RetryingAFE(server=arguments.web)
def balancer(pool, labels):
"""Balance the specified model.
@param pool: The pool to rebalance for the model.
@param labels: labels to restrict to balancing operations
_balance_model(arguments, afe, pool, labels,
start_time, end_time)
pools = (lab_inventory.CRITICAL_POOLS
if arguments.pool == _ALL_CRITICAL_POOLS
else [arguments.pool])
balancer_targets = infer_balancer_targets(afe, arguments, pools)
except KeyboardInterrupt:
if __name__ == '__main__':