def test_duplicate_metrics_raises(self):
registry = CollectorRegistry()
Counter('c_total', 'help', registry=registry)
self.assertRaises(ValueError, Counter, 'c_total', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'c_total', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'c_created', 'help', registry=registry)
Gauge('g_created', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'g_created', 'help', registry=registry)
self.assertRaises(ValueError, Counter, 'g', 'help', registry=registry)
Summary('s', 'help', registry=registry)
self.assertRaises(ValueError, Summary, 's', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 's_created', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 's_sum', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 's_count', 'help', registry=registry)
# We don't currently expose quantiles, but let's prevent future
# clashes anyway.
self.assertRaises(ValueError, Gauge, 's', 'help', registry=registry)
Histogram('h', 'help', registry=registry)
self.assertRaises(ValueError, Histogram, 'h', 'help', registry=registry)
# Clashes aggaint various suffixes.
self.assertRaises(ValueError, Summary, 'h', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'h_count', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'h_sum', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'h_bucket', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'h_created', 'help', registry=registry)
# The name of the histogram itself isn't taken.
Gauge('h', 'help', registry=registry)
Info('i', 'help', registry=registry)
self.assertRaises(ValueError, Gauge, 'i_info', 'help', registry=registry)
def test_timer_not_observable(self):
g = Gauge('test', 'help', labelnames=('label',), registry=self.registry)
try:
g.time()
except ValueError as e:
self.assertIn('missing label values', str(e))
def test_gauge_min(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='min')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(1, self.registry.get_sample_value('g'))
def test_gauge_max(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='max')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(2, self.registry.get_sample_value('g'))
class ZpoolCollector(object):
"""
'zpool status' checker
"""
# timeout how match seconds is allowed to collect data
max_time_to_run = 4
zpool_collector_timeouts = Counter('solaris_exporter_zpool_timeouts',
'timeouts')
zpool_collector_errors = Counter(
'solaris_exporter_zpool_errors',
'Number of times when collector ran' + ' with errors')
zpool_collector_run_time = Gauge('solaris_exporter_zpool_processing',
'Time spent processing request')
def collect(self):
with self.zpool_collector_run_time.time():
output, task_return_code, task_timeouted = run_shell_command(
'/usr/sbin/zpool status', self.max_time_to_run)
if task_return_code == 0 and task_timeouted is False:
lines = output.splitlines()
zpool = GaugeMetricFamily("solaris_exporter_zpool_faults",
'faults in zpool status',
labels=['host'])
faults = 0
for line in lines:
line = line.strip()
if any(s in line for s in ['FAILED', 'DEGRADED']):
faults += 1
zpool.add_metric([host_name], float(faults))
yield zpool
else:
self.zpool_collector_errors.inc()
if task_timeouted:
self.zpool_collector_timeouts.inc()
class FmadmCollector(object):
"""
'fmadm faulty' checker
"""
# timeout how match seconds is allowed to collect data
max_time_to_run = 15
fmadm_collector_timeouts = Counter('solaris_exporter_fmadm_timeouts',
'timeouts')
fmadm_collector_errors = Counter(
'solaris_exporter_fmadm_errors',
'Number of times when collector ran' + ' with errors')
fmadm_collector_run_time = Gauge('solaris_exporter_fmadm_processing',
'Time spent processing request')
def collect(self):
with self.fmadm_collector_run_time.time():
output, task_return_code, task_timeouted = run_shell_command(
'/usr/bin/pfexec /usr/sbin/fmadm faulty', self.max_time_to_run)
if task_return_code == 0 and task_timeouted is False:
lines = output.splitlines()
fmadm = GaugeMetricFamily("solaris_exporter_fmadm_faults",
'faults in fmadm faulty',
labels=['host'])
faults = 0
for line in lines:
if line.strip().startswith('TIME'):
faults += 1
fmadm.add_metric([host_name], float(faults))
yield fmadm
else:
self.fmadm_collector_errors.inc()
if task_timeouted:
self.fmadm_collector_timeouts.inc()
class SVCSCollector(object):
"""
'svcs -x' checker
"""
# timeout how match seconds is allowed to collect data
max_time_to_run = 4
svcs_x_collector_timeouts = Counter('solaris_exporter_svcs_x_timeouts',
'timeouts')
svcs_x_collector_errors = Counter(
'solaris_exporter_svcs_x_errors',
'Number of times when collector ran' + ' with errors')
svcs_x_collector_run_time = Gauge('solaris_exporter_svcs_x_processing',
'Time spent processing request')
def collect(self):
with self.svcs_x_collector_run_time.time():
output, task_return_code, task_timeouted = run_shell_command(
'/usr/bin/svcs -x', self.max_time_to_run)
if task_return_code == 0 and task_timeouted is False:
lines = output.splitlines()
svcs_x = GaugeMetricFamily(
"solaris_exporter_svcs_x_failed_services",
'failed services counter in svcs -x',
labels=['host'])
svcs_fail = 0
for line in lines:
if line.strip().startswith('svc:'):
svcs_fail += 1
svcs_x.add_metric([host_name], float(svcs_fail))
else:
self.svcs_x_collector_errors.inc()
if task_timeouted:
self.svcs_x_collector_timeouts.inc()
yield svcs_x
class MemCollector(object):
"""
Memory and SWAP Stats
"""
mem_collector_run_time = Gauge('solaris_exporter_MemCollector_processing',
'Time spent processing request')
def collect(self):
with self.mem_collector_run_time.time():
worker_stat_mem = GaugeMetricFamily(
'solaris_exporter_memory_usage_bytes',
'python psutil counters, Memory usage in bytes.',
labels=['host', 'type', 'counter'])
ram = psutil.virtual_memory()
swap = psutil.swap_memory()
worker_stat_mem.add_metric([host_name, 'virtual', 'used'],
ram.used)
worker_stat_mem.add_metric([host_name, 'virtual', 'available'],
ram.available)
worker_stat_mem.add_metric([host_name, 'virtual', 'total'],
ram.total)
worker_stat_mem.add_metric([host_name, 'virtual', 'free'],
ram.free)
worker_stat_mem.add_metric([host_name, 'swap', 'total'],
swap.total)
worker_stat_mem.add_metric([host_name, 'swap', 'used'], swap.used)
worker_stat_mem.add_metric([host_name, 'swap', 'free'], swap.free)
worker_stat_mem.add_metric([host_name, 'swap', 'sin'], swap.sin)
worker_stat_mem.add_metric([host_name, 'swap', 'sout'], swap.sout)
yield worker_stat_mem
def test_timer_not_observable(self):
g = Gauge('test', 'help', labelnames=('label',), registry=self.registry)
def manager():
with g.time():
pass
assert_not_observable(manager)
def test_gauge_livesum(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(3, self.registry.get_sample_value('g'))
mark_process_dead(123, os.environ['PROMETHEUS_MULTIPROC_DIR'])
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_gauge_livesum(self):
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='livesum')
self.assertEqual(0, self.registry.get_sample_value('g'))
g1.set(1)
g2.set(2)
self.assertEqual(3, self.registry.get_sample_value('g'))
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(2, self.registry.get_sample_value('g'))
def test_aggregates_live_and_archived_metrics(self):
pid = 456
values.ValueClass = MultiProcessValue(lambda: pid)
def files():
fs = os.listdir(os.environ['prometheus_multiproc_dir'])
fs.sort()
return fs
c1 = Counter('c1', 'c1', registry=None)
c1.inc(1)
self.assertIn('counter_456.db', files())
archive_metrics()
self.assertNotIn('counter_456.db', files())
self.assertEqual(1, self.registry.get_sample_value('c1_total'))
pid = 789
values.ValueClass = MultiProcessValue(lambda: pid)
c1 = Counter('c1', 'c1', registry=None)
c1.inc(2)
g1 = Gauge('g1', 'g1', registry=None, multiprocess_mode="liveall")
g1.set(5)
self.assertIn('counter_789.db', files())
# Pretend that pid 789 is live
archive_metrics(aggregate_only=True)
# The live counter should be merged with the archived counter, and the
# liveall gauge should be included
self.assertIn('counter_789.db', files())
self.assertIn('gauge_liveall_789.db', files())
self.assertEqual(3, self.registry.get_sample_value('c1_total'))
self.assertEqual(
5, self.registry.get_sample_value('g1', labels={u'pid': u'789'}))
# Now pid 789 is dead
archive_metrics()
# The formerly live counter's value should be archived, and the
# liveall gauge should be removed completely
self.assertNotIn('counter_789.db', files())
self.assertNotIn('gauge_liveall_789.db', files())
self.assertEqual(3, self.registry.get_sample_value('c1_total'))
self.assertEqual(
None, self.registry.get_sample_value('g1', labels={u'pid':
u'789'}))
def __init__(self, sonar_client: SonarQubeClient):
self._sonar_client = sonar_client
self._cached_metrics = []
# initialize gauges
logging.info("Intitializing...")
self._metrics = {}
raw_metrics = self._sonar_client.get_metrics()["metrics"]
for raw_metric in raw_metrics:
metric = Metric()
for supported_m in CONF.supported_keys:
if "domain" in raw_metric and raw_metric[
"domain"] == supported_m["domain"] and raw_metric[
"key"] in supported_m["keys"]:
metric.domain = raw_metric["domain"]
metric.key = raw_metric["key"]
metric.type = raw_metric["type"]
if "description" in raw_metric:
metric.description = raw_metric["description"]
else:
metric.description = raw_metric["name"]
if "tranformKeys" in supported_m and raw_metric[
"key"] in supported_m["tranformKeys"].keys():
metric.tranform = True
metric.tranform_map = supported_m["tranformKeys"][
raw_metric["key"]]
self._metrics[metric.key] = metric
self._queried_metrics = str()
self._gauges = {}
labels = ("id", "key", "name", "domain", "type")
for key, m in self._metrics.items():
if m.tranform:
self._gauges[m.key] = Gauge(name="sonar_{}".format(m.key),
documentation=m.description,
labelnames=("id", "key", "name",
"domain", "type",
"value"))
else:
self._gauges[m.key] = Gauge(name="sonar_{}".format(m.key),
documentation=m.description,
labelnames=("id", "key", "name",
"domain", "type"))
self._queried_metrics = "{},{}".format(m.key,
self._queried_metrics)
logging.info("Initialized %s metrics." % len(self._metrics.keys()))
def test_gauge_max(self):
self.pid = 123
g1 = Gauge('gmax', 'help', registry=None, multiprocess_mode='max')
self.pid = 456
g2 = Gauge('gmax', 'help', registry=None, multiprocess_mode='max')
self.assertEqual(0, self.registry.get_sample_value('gmax', {'hostname':hostname}))
self.pid = 123
g1.set(1)
self.pid = 456
g2.set(2)
self.assertEqual(2, self.registry.get_sample_value('gmax', {'hostname':hostname}))
def test_gauge_all(self):
g1 = Gauge('g', 'help', registry=None)
core._ValueClass = core._MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None)
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0, self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(1, self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2, self.registry.get_sample_value('g', {'pid': '456'}))
def test_unregister_works(self):
registry = CollectorRegistry()
s = Summary('s', 'help', registry=registry)
self.assertRaises(ValueError,
Gauge,
's_count',
'help',
registry=registry)
registry.unregister(s)
Gauge('s_count', 'help', registry=registry)
def test_reset_registry_with_labels(self):
registry = CollectorRegistry()
gauge = Gauge('g', 'help', ['l'], registry=registry)
gauge.labels('a').inc()
self.assertEqual(1, registry.get_sample_value('g', {'l': 'a'}))
counter = Counter('c_total', 'help', ['l'], registry=registry)
counter.labels('a').inc()
self.assertEqual(1, registry.get_sample_value('c_total', {'l': 'a'}))
summary = Summary('s', 'help', ['l'], registry=registry)
summary.labels('a').observe(10)
self.assertEqual(1, registry.get_sample_value('s_count', {'l': 'a'}))
self.assertEqual(10, registry.get_sample_value('s_sum', {'l': 'a'}))
histogram = Histogram('h', 'help', ['l'], registry=registry)
histogram.labels('a').observe(2)
self.assertEqual(0, registry.get_sample_value('h_bucket', {'le': '1.0', 'l': 'a'}))
self.assertEqual(1, registry.get_sample_value('h_bucket', {'le': '2.5', 'l': 'a'}))
self.assertEqual(1, registry.get_sample_value('h_bucket', {'le': '5.0', 'l': 'a'}))
self.assertEqual(1, registry.get_sample_value('h_bucket', {'le': '+Inf', 'l': 'a'}))
self.assertEqual(1, registry.get_sample_value('h_count', {'l': 'a'}))
self.assertEqual(2, registry.get_sample_value('h_sum', {'l': 'a'}))
registry.reset()
self.assertEqual(0, registry.get_sample_value('g', {'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('c_total', {'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('s_count', {'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('s_sum', {'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_bucket', {'le': '1.0', 'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_bucket', {'le': '2.5', 'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_bucket', {'le': '5.0', 'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_bucket', {'le': '+Inf', 'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_count', {'l': 'a'}))
self.assertEqual(0, registry.get_sample_value('h_sum', {'l': 'a'}))
def test_gauge_livesum(self):
self.pid = 123
g1 = Gauge('gls', 'help', registry=None, multiprocess_mode='livesum')
self.pid = 456
g2 = Gauge('gls', 'help', registry=None, multiprocess_mode='livesum')
self.assertEqual(0, self.registry.get_sample_value('gls', {'hostname':hostname}))
self.pid = 123
g1.set(1)
self.pid = 456
g2.set(2)
self.assertEqual(3, self.registry.get_sample_value('gls', {'hostname':hostname}))
from prometheus_client.distributed import mark_distributed_process_dead
mark_distributed_process_dead(123)
self.assertEqual(2, self.registry.get_sample_value('gls', {'hostname':hostname}))
def test_gauge_last(self):
self.pid = 123
g1 = Gauge('g1last', 'help', registry=None, multiprocess_mode='last')
g1.set(1)
self.pid = 456
g1.set(2)
self.assertEqual(2, self.registry.get_sample_value('g1last'))
def test_collect(self):
pid = 0
core._ValueClass = core._MultiProcessValue(lambda: pid)
labels = dict((i, i) for i in 'abcd')
def add_label(key, value):
l = labels.copy()
l[key] = value
return l
c = Counter('c', 'help', labelnames=labels.keys(), registry=None)
g = Gauge('g', 'help', labelnames=labels.keys(), registry=None)
h = Histogram('h', 'help', labelnames=labels.keys(), registry=None)
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(1)
pid = 1
c.labels(**labels).inc(1)
g.labels(**labels).set(1)
h.labels(**labels).observe(5)
metrics = dict((m.name, m) for m in self.collector.collect())
self.assertEqual(
metrics['c'].samples, [Sample('c_total', labels, 2.0)]
)
metrics['g'].samples.sort(key=lambda x: x[1]['pid'])
self.assertEqual(metrics['g'].samples, [
Sample('g', add_label('pid', '0'), 1.0),
Sample('g', add_label('pid', '1'), 1.0),
])
metrics['h'].samples.sort(
key=lambda x: (x[0], float(x[1].get('le', 0)))
)
expected_histogram = [
Sample('h_bucket', add_label('le', '0.005'), 0.0),
Sample('h_bucket', add_label('le', '0.01'), 0.0),
Sample('h_bucket', add_label('le', '0.025'), 0.0),
Sample('h_bucket', add_label('le', '0.05'), 0.0),
Sample('h_bucket', add_label('le', '0.075'), 0.0),
Sample('h_bucket', add_label('le', '0.1'), 0.0),
Sample('h_bucket', add_label('le', '0.25'), 0.0),
Sample('h_bucket', add_label('le', '0.5'), 0.0),
Sample('h_bucket', add_label('le', '0.75'), 0.0),
Sample('h_bucket', add_label('le', '1.0'), 1.0),
Sample('h_bucket', add_label('le', '2.5'), 1.0),
Sample('h_bucket', add_label('le', '5.0'), 2.0),
Sample('h_bucket', add_label('le', '7.5'), 2.0),
Sample('h_bucket', add_label('le', '10.0'), 2.0),
Sample('h_bucket', add_label('le', '+Inf'), 2.0),
Sample('h_count', labels, 2.0),
Sample('h_sum', labels, 6.0),
]
self.assertEqual(metrics['h'].samples, expected_histogram)
def test_gauge_all(self):
g1 = Gauge('g', 'help', registry=None)
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None)
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
mark_process_dead(123)
self.assertEqual(1,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2,
self.registry.get_sample_value('g', {'pid': '456'}))
class FCinfoCollector(object):
"""
FC links Multipath
"""
# timeout how match seconds is allowed to collect data
max_time_to_run = 4
fc_lun_collector_timeouts = Counter('solaris_exporter_fc_paths_timeouts',
'timeouts')
fc_lun_collector_errors = Counter(
'solaris_exporter_fc_paths_errors',
'Number of times when collector ran' + ' with errors')
fc_lun_collector_run_time = Gauge('solaris_exporter_fc_paths_processing',
'Time spent processing request')
def collect(self):
with self.fc_lun_collector_run_time.time():
output, task_return_code, task_timeouted = run_shell_command(
'/usr/sbin/mpathadm list lu', self.max_time_to_run)
if task_return_code == 0 and task_timeouted is False:
lines = output.splitlines()
fc_lun = GaugeMetricFamily("solaris_exporter_fc_paths",
'/usr/sbin/mpathadm list lu',
labels=['device', 'stat', 'host'])
fc_total_paths = {}
fc_active_paths = {}
for line in lines:
content = line.strip()
if '/dev/rdsk/' in content:
device = re.sub(r'/dev/rdsk/(.*)s2', r'\1', content)
elif 'Total Path Count' in content:
content = content.split(':')
fc_total_paths[device] = content[1]
elif 'Operational Path Count:' in content:
content = content.split(':')
fc_active_paths[device] = content[1]
else:
device = "unknown"
for device in fc_total_paths.keys():
if device == "unknown":
continue
fc_lun.add_metric([device, 'active', host_name],
float(fc_active_paths.get(device, 0)))
fc_lun.add_metric([device, 'total', host_name],
float(fc_total_paths.get(device, 0)))
yield fc_lun
else:
self.fc_lun_collector_errors.inc()
if task_timeouted:
self.fc_lun_collector_timeouts.inc()
def test_gauge_all(self):
values.ValueClass = MultiProcessValue(lambda: 123)
g1 = Gauge('g', 'help', registry=None, multiprocess_mode='all')
values.ValueClass = MultiProcessValue(lambda: 456)
g2 = Gauge('g', 'help', registry=None, multiprocess_mode='all')
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(0,
self.registry.get_sample_value('g', {'pid': '456'}))
g1.set(1)
g2.set(2)
archive_metrics()
mark_process_dead(123, os.environ['prometheus_multiproc_dir'])
self.assertEqual(1,
self.registry.get_sample_value('g', {'pid': '123'}))
self.assertEqual(2,
self.registry.get_sample_value('g', {'pid': '456'}))
class DiskSpaceCollector(object):
"""
Disk space stats
Note that UFS inode info is NOT collected.
"""
disk_space_collector_run_time = Gauge('solaris_exporter_diskspace_worker',
'Time spent processing request')
def collect(self):
with self.disk_space_collector_run_time.time():
worker_stat_space = GaugeMetricFamily(
'solaris_exporter_diskspace_usage_bytes',
'python psutil counters, diskspace usage in bytes.',
labels=[
'host',
'statistic',
'mountpoint',
'device',
'fstype',
])
# disk_partitions = my_disk_partitions(all=False) # rewritten due to bug: https://github.com/giampaolo/psutil/issues/1674
disk_partitions = cext.disk_partitions()
for partition in disk_partitions:
device, mountpoint, fstype, opts = partition
if fstype not in ['zfs', 'ufs']:
continue
if '/VARSHARE' in device:
continue
try:
spaceinfo = psutil.disk_usage(mountpoint)
except OSError:
continue
worker_stat_space.add_metric(
[host_name, 'used', mountpoint, device, fstype],
spaceinfo.used)
worker_stat_space.add_metric(
[host_name, 'total', mountpoint, device, fstype],
spaceinfo.total)
worker_stat_space.add_metric(
[host_name, 'free', mountpoint, device, fstype],
spaceinfo.free)
worker_stat_space.add_metric(
[host_name, 'percent', mountpoint, device, fstype],
spaceinfo.percent)
yield worker_stat_space
class CpuTimeCollector(object):
"""
CPU time may be translated in percent later
"""
cpu_time_collector_run_time = Gauge('solaris_exporter_cpu_time_processing',
'Time spent processing request')
def collect(self):
with self.cpu_time_collector_run_time.time():
worker_stat_cpu_time = CounterMetricFamily(
'solaris_exporter_cpu_time',
'python psutil counters, CPU usage time.',
labels=['host', 'statistic'])
cpuinfo = psutil.cpu_times(percpu=False)
worker_stat_cpu_time.add_metric([host_name, 'user'], cpuinfo.user)
worker_stat_cpu_time.add_metric([host_name, 'system'],
cpuinfo.system)
worker_stat_cpu_time.add_metric([host_name, 'idle'], cpuinfo.idle)
worker_stat_cpu_time.add_metric([host_name, 'oiwait'],
cpuinfo.iowait)
yield worker_stat_cpu_time
class CpuLoadCollector(object):
"""
CPU load average 1, 5, 15 min, cpu count
"""
cpu_load_collector_run_time = Gauge('solaris_exporter_cpu_load_processing',
'Time spent processing request')
def collect(self):
with self.cpu_load_collector_run_time.time():
worker_stat_cpu_load = GaugeMetricFamily(
'solaris_exporter_cpu_load',
'python psutil counters, system load avg.',
labels=['host', 'statistic'])
cpuinfo = os.getloadavg()
worker_stat_cpu_load.add_metric([host_name, 'load1m'], cpuinfo[0])
worker_stat_cpu_load.add_metric([host_name, 'load5m '],
cpuinfo[1])
worker_stat_cpu_load.add_metric([host_name, 'load15m'], cpuinfo[2])
cpuinfo = len(psutil.cpu_percent(interval=None, percpu=True))
worker_stat_cpu_load.add_metric([host_name, 'vcpu'], cpuinfo)
yield worker_stat_cpu_load
def buckets_to_metrics(self, metric_name, buckets):
# Converts raw bucket metric into sorted list of buckets
unit = buckets['boundary_unit']
description = 'libmedida metric type: ' + buckets['type']
c = Counter(metric_name + '_count',
description,
self.label_names,
registry=self.registry)
s = Counter(metric_name + '_sum',
description,
self.label_names,
registry=self.registry)
g = Gauge(metric_name + '_bucket',
description,
self.label_names + ['le'],
registry=self.registry)
measurements = []
for bucket in buckets['buckets']:
measurements.append({
'boundary':
self.duration_to_seconds(bucket['boundary'], unit),
'count':
bucket['count'],
'sum':
bucket['sum']
})
count = 0
for m in sorted(measurements, key=lambda i: i['boundary']):
# Buckets from core contain only values from their respective ranges.
# Prometheus expects "le" buckets to be cummulative so we need some extra math
count += m['count']
c.labels(*self.labels).inc(m['count'])
s.labels(*self.labels).inc(self.duration_to_seconds(
m['sum'], unit))
# Treat buckets larger than 30d as infinity
if float(m['boundary']) > 30 * 86400:
g.labels(*self.labels + ['+Inf']).inc(count)
else:
g.labels(*self.labels + [m['boundary']]).inc(count)
class TinvestCollector(object):
account_id: str
client: SyncClient
registry: CollectorRegistry = CollectorRegistry()
position_average_price: Gauge = Gauge("position_average_price",
"Average position price",
labelnames=["name", "currency"],
registry=registry)
position_average_price_no_nkd: Gauge = Gauge(
"position_average_price_no_nkd",
"Average position price",
labelnames=["name", "currency"],
registry=registry)
position_last_price: Gauge = Gauge("position_last_price",
"Position last price",
labelnames=["name"],
registry=registry)
position_close_price: Gauge = Gauge("position_close_price",
"Position close price",
labelnames=["name"],
registry=registry)
position_expected_yield: Gauge = Gauge("position_expected_yield",
"Expected yield",
labelnames=["name", "currency"],
registry=registry)
position_balance: Gauge = Gauge("position_balance",
"Balance",
labelnames=["name"],
registry=registry)
position_info: Info = Info("position",
"Position information",
labelnames=["name"],
registry=registry)
position_lots: Gauge = Gauge("position_lots",
"Lots count",
labelnames=["name"],
registry=registry)
currency_balance: Gauge = Gauge("currency_balance",
"Currency balance",
labelnames=["name"],
registry=registry)
etf_info: Info = Info("etf",
"ETF information",
labelnames=["name"],
registry=registry)
etf_last_price: Gauge = Gauge("etf_last_price",
"ETF last price",
labelnames=["name"],
registry=registry)
operation_commission: Gauge = Gauge(
"operation_commission",
"Operations commission",
labelnames=["figi", "currency", "instrument_type", "operation_type"],
registry=registry)
operation_broker_commission: Gauge = Gauge(
"operation_broker_commission",
"Broker commission",
labelnames=["figi", "currency", "instrument_type"],
registry=registry)
operation_coupon: Gauge = Gauge(
"operation_coupon",
"Coupon payments sum",
labelnames=["figi", "currency", "instrument_type"],
registry=registry)
operation_dividend: Gauge = Gauge(
"operation_dividend",
"Dividend payments sum",
labelnames=["figi", "currency", "instrument_type"],
registry=registry)
def __init__(self, token: str, account_id: str):
self.client = SyncClient(token, use_sandbox=False)
self.account_id = account_id
def collect(self):
self.__generate_positions_metrics()
self.__generate_currencies_metrics()
self.__generate_etfs_metrics()
self.__generate_operations_metrics()
for metric in self.registry.collect():
yield metric
def __generate_positions_metrics(self):
for position in self.__get_positions():
if position.average_position_price_no_nkd is not None:
self.position_average_price_no_nkd.labels(position.name,
position.average_position_price_no_nkd.currency.name). \
set(position.average_position_price_no_nkd.value)
currency = position.average_position_price_no_nkd.currency.name
else:
self.position_average_price.labels(
position.name, position.average_position_price.currency.name). \
set(position.average_position_price.value)
currency = position.average_position_price.currency.name
self.position_expected_yield.labels(position.name, position.expected_yield.currency.name). \
set(position.expected_yield.value)
self.position_balance.labels(position.name).set(position.balance)
orders = self.client.get_market_orderbook(position.figi, 0)
self.position_last_price.labels(position.name).set(
orders.payload.last_price)
self.position_close_price.labels(position.name).set(
orders.payload.close_price)
self.position_info.labels(position.name).info({
"currency":
currency,
"blocked":
position.blocked or "0",
"figi":
position.figi,
"instrument_type":
position.instrument_type,
"isin":
position.isin or "",
"ticker":
position.ticker,
})
self.position_lots.labels(position.name).set(position.lots)
def __generate_currencies_metrics(self):
for currency in self.__get_currencies():
self.currency_balance.labels(currency.currency.name).set(
currency.balance)
def __generate_etfs_metrics(self):
for etf in self.__get_etfs():
orders = self.client.get_market_orderbook(etf.figi, 0)
self.etf_last_price.labels(etf.name).set(orders.payload.last_price)
self.etf_info.labels(etf.name).info({
"currency":
etf.currency.name,
"figi":
etf.figi,
"isin":
etf.isin,
"ticker":
etf.ticker,
"trade_status":
orders.payload.trade_status.name,
})
def __generate_operations_metrics(self):
for operation in self.__get_operations():
if operation.commission is not None:
self.operation_commission.labels(operation.figi, operation.commission.currency.name,
operation.instrument_type.name, operation.operation_type.name). \
inc(float(operation.commission.value))
if operation.operation_type.name == 'broker_commission':
self.operation_broker_commission.labels(operation.figi, operation.currency.name,
operation.instrument_type.name). \
inc(float(operation.payment))
elif operation.operation_type.name == 'coupon':
self.operation_coupon.labels(operation.figi, operation.currency.name, operation.instrument_type.name). \
inc(float(operation.payment))
elif operation.operation_type.name == 'dividend':
self.operation_dividend.labels(operation.figi, operation.currency.name,
operation.instrument_type.name). \
inc(float(operation.payment))
def __get_positions(self):
portfolio = self.client.get_portfolio(self.account_id)
return portfolio.payload.positions
def __get_currencies(self):
currencies = self.client.get_portfolio_currencies(self.account_id)
return currencies.payload.currencies
def __get_etfs(self):
etfs = self.client.get_market_etfs()
return etfs.payload.instruments
def __get_operations(self):
operations = self.client.get_operations(
datetime.now() - timedelta(minutes=1),
datetime.now(),
broker_account_id=self.account_id)
return operations.payload.operations
def setUp(self):
self.registry = CollectorRegistry()
self.gauge = Gauge('g', 'help', registry=self.registry)
class TestGauge(unittest.TestCase):
def setUp(self):
self.registry = CollectorRegistry()
self.gauge = Gauge('g', 'help', registry=self.registry)
def test_gauge(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
self.gauge.inc()
self.assertEqual(1, self.registry.get_sample_value('g'))
self.gauge.dec(3)
self.assertEqual(-2, self.registry.get_sample_value('g'))
self.gauge.set(9)
self.assertEqual(9, self.registry.get_sample_value('g'))
def test_inprogress_function_decorator(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
@self.gauge.track_inprogress()
def f():
self.assertEqual(1, self.registry.get_sample_value('g'))
self.assertEqual(([], None, None, None), inspect.getargspec(f))
f()
self.assertEqual(0, self.registry.get_sample_value('g'))
def test_inprogress_block_decorator(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
with self.gauge.track_inprogress():
self.assertEqual(1, self.registry.get_sample_value('g'))
self.assertEqual(0, self.registry.get_sample_value('g'))
def test_gauge_function(self):
x = {}
self.gauge.set_function(lambda: len(x))
self.assertEqual(0, self.registry.get_sample_value('g'))
self.gauge.inc()
self.assertEqual(0, self.registry.get_sample_value('g'))
x['a'] = None
self.assertEqual(1, self.registry.get_sample_value('g'))
def test_time_function_decorator(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
@self.gauge.time()
def f():
time.sleep(.001)
self.assertEqual(([], None, None, None), inspect.getargspec(f))
f()
self.assertNotEqual(0, self.registry.get_sample_value('g'))
def test_function_decorator_multithread(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
workers = 2
pool = ThreadPoolExecutor(max_workers=workers)
@self.gauge.time()
def f(duration):
time.sleep(duration)
expected_duration = 1
pool.submit(f, expected_duration)
time.sleep(0.7 * expected_duration)
pool.submit(f, expected_duration * 2)
time.sleep(expected_duration)
rounding_coefficient = 0.9
adjusted_expected_duration = expected_duration * rounding_coefficient
self.assertLess(adjusted_expected_duration,
self.registry.get_sample_value('g'))
pool.shutdown(wait=True)
def test_time_block_decorator(self):
self.assertEqual(0, self.registry.get_sample_value('g'))
with self.gauge.time():
time.sleep(.001)
self.assertNotEqual(0, self.registry.get_sample_value('g'))