def test_service_check_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0')
stats.submit_packets('_sc|check.2|0|#t1')
stats.submit_packets('_sc|check.3|0|h:i-abcd1234|#t1,t2|m:fakeout#t5')
stats.submit_packets('_sc|check.4|0|#t1,t2:v2,t3,t4')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
nt.assert_equal(first['check'], 'check.1')
assert first.get('tags') is None, "service_check['tags'] shouldn't be" + \
"defined when no tags aren't explicited in the packet"
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['host_name'], 'i-abcd1234')
nt.assert_equal(third['message'], 'fakeout#t5')
nt.assert_equal(third['tags'], sorted(['t1', 't2']))
nt.assert_equal(fourth['check'], 'check.4')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
def test_custom_aggregate(self):
configstr = 'median, max'
stats = MetricsAggregator(
'myhost',
histogram_aggregates=get_histogram_aggregates(configstr)
)
self.assertEquals(
sorted(stats.metric_config[Histogram]['aggregates']),
['max', 'median'],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 3, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram')+1:]] = k['points'][0][1]
self.assertEquals(value_by_type['median'], 9, value_by_type)
self.assertEquals(value_by_type['max'], 19, value_by_type)
self.assertEquals(value_by_type['95percentile'], 18, value_by_type)
def test_custom_single_percentile(self):
configstr = '0.40'
stats = MetricsAggregator(
'myhost',
histogram_percentiles=get_histogram_percentiles(configstr)
)
self.assertEquals(
stats.metric_config[Histogram]['percentiles'],
[0.40],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 5, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k[0][len('myhistogram')+1:]] = k[2]
self.assertEquals(value_by_type['40percentile'], 7, value_by_type)
def test_tags(self):
stats = MetricsAggregator("myhost")
stats.submit_packets("gauge:1|c")
stats.submit_packets("gauge:2|c|@1")
stats.submit_packets("gauge:4|c|#tag1,tag2")
stats.submit_packets("gauge:8|c|#tag2,tag1") # Should be the same as above
stats.submit_packets("gauge:16|c|#tag3,tag4")
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
nt.assert_equal(first["metric"], "gauge")
nt.assert_equal(first["tags"], None)
nt.assert_equal(first["points"][0][1], 3)
nt.assert_equal(first["host"], "myhost")
nt.assert_equal(second["metric"], "gauge")
nt.assert_equal(second["tags"], ("tag1", "tag2"))
nt.assert_equal(second["points"][0][1], 12)
nt.assert_equal(second["host"], "myhost")
nt.assert_equal(third["metric"], "gauge")
nt.assert_equal(third["tags"], ("tag3", "tag4"))
nt.assert_equal(third["points"][0][1], 16)
nt.assert_equal(third["host"], "myhost")
def test_custom_multiple_percentile(self):
configstr = '0.4, 0.65, 0.999'
stats = MetricsAggregator(
'myhost',
histogram_percentiles=get_histogram_percentiles(configstr)
)
self.assertEquals(
stats.metric_config[Histogram]['percentiles'],
[0.4, 0.65, 0.99],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 7, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram')+1:]] = k['points'][0][1]
self.assertEquals(value_by_type['40percentile'], 7, value_by_type)
self.assertEquals(value_by_type['65percentile'], 12, value_by_type)
self.assertEquals(value_by_type['99percentile'], 19, value_by_type)
def test_event_tags(self):
stats = MetricsAggregator("myhost")
stats.submit_packets("_e{6,4}:title1|text")
stats.submit_packets("_e{6,4}:title2|text|#t1")
stats.submit_packets("_e{6,4}:title3|text|#t1,t2:v2,t3,t4")
stats.submit_packets("_e{6,4}:title4|text|k:key|p:normal|#t1,t2")
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
try:
first["tags"]
except Exception:
assert True
else:
assert False, "event['tags'] shouldn't be defined when no tags aren't explicited in the packet"
nt.assert_equal(first["msg_title"], "title1")
nt.assert_equal(first["msg_text"], "text")
nt.assert_equal(second["msg_title"], "title2")
nt.assert_equal(second["msg_text"], "text")
nt.assert_equal(second["tags"], sorted(["t1"]))
nt.assert_equal(third["msg_title"], "title3")
nt.assert_equal(third["msg_text"], "text")
nt.assert_equal(third["tags"], sorted(["t1", "t2:v2", "t3", "t4"]))
nt.assert_equal(fourth["msg_title"], "title4")
nt.assert_equal(fourth["msg_text"], "text")
nt.assert_equal(fourth["aggregation_key"], "key")
nt.assert_equal(fourth["priority"], "normal")
nt.assert_equal(fourth["tags"], sorted(["t1", "t2"]))
def test_event_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_e{6,4}:title1|text')
stats.submit_packets('_e{6,4}:title2|text|#t1')
stats.submit_packets('_e{6,4}:title3|text|#t1,t2:v2,t3,t4')
stats.submit_packets('_e{6,4}:title4|text|k:key|p:normal|#t1,t2')
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
try:
first['tags']
except Exception:
assert True
else:
assert False, "event['tags'] shouldn't be defined when no tags aren't explicited in the packet"
nt.assert_equal(first['msg_title'], 'title1')
nt.assert_equal(first['msg_text'], 'text')
nt.assert_equal(second['msg_title'], 'title2')
nt.assert_equal(second['msg_text'], 'text')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['msg_title'], 'title3')
nt.assert_equal(third['msg_text'], 'text')
nt.assert_equal(third['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
nt.assert_equal(fourth['msg_title'], 'title4')
nt.assert_equal(fourth['msg_text'], 'text')
nt.assert_equal(fourth['aggregation_key'], 'key')
nt.assert_equal(fourth['priority'], 'normal')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2']))
def test_histogram(self):
stats = MetricsAggregator('myhost')
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
percentiles = range(100)
random.shuffle(percentiles) # in place
for i in percentiles:
for j in xrange(20):
for type_ in ['h', 'ms']:
m = 'my.p:%s|%s' % (i, type_)
stats.submit_packets(m)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 5)
p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics)
nt.assert_equal(p95['metric'], 'my.p.95percentile')
self.assert_almost_equal(p95['points'][0][1], 95, 10)
self.assert_almost_equal(pmax['points'][0][1], 99, 1)
self.assert_almost_equal(pmed['points'][0][1], 50, 2)
self.assert_almost_equal(pavg['points'][0][1], 50, 2)
self.assert_almost_equal(pcount['points'][0][1], 4000, 0) # 100 * 20 * 2
nt.assert_equals(p95['host'], 'myhost')
# Ensure that histograms are reset.
metrics = self.sort_metrics(stats.flush())
assert not metrics
def test_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('gauge:1|c')
stats.submit_packets('gauge:2|c|@1')
stats.submit_packets('gauge:4|c|#tag1,tag2')
stats.submit_packets('gauge:8|c|#tag2,tag1') # Should be the same as above
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
nt.assert_equal(first['metric'], 'gauge')
nt.assert_equal(first['tags'], None)
nt.assert_equal(first['points'][0][1], 3)
nt.assert_equal(first['host'], 'myhost')
nt.assert_equal(second['metric'], 'gauge')
nt.assert_equal(second['tags'], ('tag1', 'tag2'))
nt.assert_equal(second['points'][0][1], 12)
nt.assert_equal(second['host'], 'myhost')
nt.assert_equal(third['metric'], 'gauge')
nt.assert_equal(third['tags'], ('tag3', 'tag4'))
nt.assert_equal(third['points'][0][1], 16)
nt.assert_equal(third['host'], 'myhost')
def test_magic_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.gauge.a:1|c|#host:test-a')
stats.submit_packets('my.gauge.b:4|c|#tag1,tag2,host:test-b')
stats.submit_packets('my.gauge.b:8|c|#host:test-b,tag2,tag1')
stats.submit_packets('my.gauge.c:10|c|#tag3')
stats.submit_packets('my.gauge.c:16|c|#device:floppy,tag3')
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 4)
first, second, third, fourth = metrics
nt.assert_equal(first['metric'], 'my.gauge.a')
nt.assert_equal(first['tags'], None)
nt.assert_equal(first['points'][0][1], 1)
nt.assert_equal(first['host'], 'test-a')
nt.assert_equal(second['metric'], 'my.gauge.b')
nt.assert_equal(second['tags'], ('tag1', 'tag2'))
nt.assert_equal(second['points'][0][1], 12)
nt.assert_equal(second['host'], 'test-b')
nt.assert_equal(third['metric'], 'my.gauge.c')
nt.assert_equal(third['tags'], ('tag3', ))
nt.assert_equal(third['points'][0][1], 10)
nt.assert_equal(third['device_name'], None)
nt.assert_equal(fourth['metric'], 'my.gauge.c')
nt.assert_equal(fourth['tags'], ('tag3', ))
nt.assert_equal(fourth['points'][0][1], 16)
nt.assert_equal(fourth['device_name'], 'floppy')
def test_histogram(self):
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
percentiles = range(100)
random.shuffle(percentiles) # in place
for i in percentiles:
for j in xrange(20):
for type_ in ['h', 'ms']:
m = 'my.p:%s|%s' % (i, type_)
stats.submit_packets(m)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 6)
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
nt.assert_equal(p95[0], 'my.p.95percentile')
self.assert_almost_equal(p95[2], 95, 10)
self.assert_almost_equal(pmax[2], 99, 1)
self.assert_almost_equal(pmed[2], 50, 2)
self.assert_almost_equal(pavg[2], 50, 2)
self.assert_almost_equal(pmin[2], 1, 1)
self.assert_almost_equal(pcount[2], 4000, 0) # 100 * 20 * 2
nt.assert_equals(p95[3]['hostname'], 'myhost')
# Ensure that histograms are reset.
metrics = self.sort_metrics(stats.flush())
assert not metrics
def test_scientific_notation(self):
stats = MetricsAggregator('myhost', interval=10)
stats.submit_packets('test.scinot:9.512901e-05|g')
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
ts, val = metrics[0].get('points')[0]
nt.assert_almost_equal(val, 9.512901e-05)
class TestAggregator(unittest.TestCase):
def setUp(self):
self.aggr = MetricsAggregator("test-aggr")
def test_dupe_tags(self):
self.aggr.increment("test-counter", 1, tags=["a", "b"])
self.aggr.increment("test-counter", 1, tags=["a", "b", "b"])
self.assertEquals(len(self.aggr.metrics), 1, self.aggr.metrics)
metric = self.aggr.metrics.values()[0]
self.assertEquals(metric.value, 2)
class TestAggregator(unittest.TestCase):
def setUp(self):
self.aggr = MetricsAggregator('test-aggr')
def test_dupe_tags(self):
self.aggr.increment('test-counter', 1, tags=['a', 'b'])
self.aggr.increment('test-counter', 1, tags=['a', 'b', 'b'])
self.assertEquals(len(self.aggr.metrics), 1, self.aggr.metrics)
metric = self.aggr.metrics.values()[0]
self.assertEquals(metric.value, 2)
def test_sampled_counter(self):
# Submit a sampled counter.
stats = MetricsAggregator('myhost')
stats.submit_packets('sampled.counter:1|c|@0.5')
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m['metric'] == 'sampled.counter'
nt.assert_equal(m['points'][0][1], 2)
def test_sampled_counter(self):
# Submit a sampled counter.
stats = MetricsAggregator("myhost")
stats.submit_packets("sampled.counter:1|c|@0.5")
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m["metric"] == "sampled.counter"
nt.assert_equal(m["points"][0][1], 2)
def test_counter(self):
stats = MetricsAggregator('myhost')
# Track some counters.
stats.submit_packets('my.first.counter:1|c')
stats.submit_packets('my.first.counter:5|c')
stats.submit_packets('my.second.counter:1|c')
stats.submit_packets('my.third.counter:3|c')
# Ensure they roll up nicely.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
nt.assert_equals(first['metric'], 'my.first.counter')
nt.assert_equals(first['points'][0][1], 6)
nt.assert_equals(first['host'], 'myhost')
nt.assert_equals(second['metric'], 'my.second.counter')
nt.assert_equals(second['points'][0][1], 1)
nt.assert_equals(third['metric'], 'my.third.counter')
nt.assert_equals(third['points'][0][1], 3)
# Ensure that counters reset to zero.
metrics = self.sort_metrics(stats.flush())
first, second, third = metrics
nt.assert_equals(first['metric'], 'my.first.counter')
nt.assert_equals(first['points'][0][1], 0)
nt.assert_equals(second['metric'], 'my.second.counter')
nt.assert_equals(second['points'][0][1], 0)
nt.assert_equals(third['metric'], 'my.third.counter')
nt.assert_equals(third['points'][0][1], 0)
def test_gauge_sample_rate(self):
stats = MetricsAggregator('myhost')
# Submit a sampled gauge metric.
stats.submit_packets('sampled.gauge:10|g|@0.1')
# Assert that it's treated normally.
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m['metric'], 'sampled.gauge')
nt.assert_equal(m['points'][0][1], 10)
def test_gauge_sample_rate(self):
stats = MetricsAggregator("myhost")
# Submit a sampled gauge metric.
stats.submit_packets("sampled.gauge:10|g|@0.1")
# Assert that it's treated normally.
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m["metric"], "sampled.gauge")
nt.assert_equal(m["points"][0][1], 10)
def test_batch_submission(self):
# Submit a sampled histogram.
stats = MetricsAggregator("myhost")
metrics = ["counter:1|c", "counter:1|c", "gauge:1|g"]
packet = "\n".join(metrics)
stats.submit_packets(packet)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(2, len(metrics))
counter, gauge = metrics
assert counter["points"][0][1] == 2
assert gauge["points"][0][1] == 1
def test_sampled_histogram(self):
# Submit a sampled histogram.
stats = MetricsAggregator("myhost")
stats.submit_packets("sampled.hist:5|h|@0.5")
# Assert we scale up properly.
metrics = self.sort_metrics(stats.flush())
p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics)
nt.assert_equal(pcount["points"][0][1], 2)
for p in [p95, pavg, pmed, pmax]:
nt.assert_equal(p["points"][0][1], 5)
def test_monokey_batching_withtags_with_sampling(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
stats.submit_packets('test_metric:1.5|c|#tag1:one,tag2:two:2.3|g|#tag3:three:3|g:42|h|#tag1:12,tag42:42|@0.22')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
packets = [
'test_metric:1.5|c|#tag1:one,tag2:two',
'test_metric:2.3|g|#tag3:three',
'test_metric:3|g',
'test_metric:42|h|#tag1:12,tag42:42|@0.22'
]
stats_ref.submit_packets("\n".join(packets))
metrics = self.sort_metrics(stats.flush())
metrics_ref = self.sort_metrics(stats_ref.flush())
self.assertTrue(len(metrics) == len(metrics_ref) == 9, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i]['points'][0][1], metrics_ref[i]['points'][0][1])
nt.assert_equal(metrics[i]['tags'], metrics_ref[i]['tags'])
def test_monokey_batching_notags(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
stats.submit_packets('test_hist:0.3|ms:2.5|ms|@0.5:3|ms')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
packets = [
'test_hist:0.3|ms',
'test_hist:2.5|ms|@0.5',
'test_hist:3|ms'
]
stats_ref.submit_packets("\n".join(packets))
metrics = stats.flush()
metrics_ref = stats_ref.flush()
self.assertTrue(len(metrics) == len(metrics_ref) == 6, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i]['points'][0][1], metrics_ref[i]['points'][0][1])
def test_sampled_histogram(self):
# Submit a sampled histogram.
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
stats.submit_packets('sampled.hist:5|h|@0.5')
# Assert we scale up properly.
metrics = self.sort_metrics(stats.flush())
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
nt.assert_equal(pcount['points'][0][1], 2)
for p in [p95, pavg, pmed, pmax, pmin]:
nt.assert_equal(p['points'][0][1], 5)
def test_event_text(self):
stats = MetricsAggregator("myhost")
stats.submit_packets("_e{2,0}:t1|")
stats.submit_packets("_e{2,12}:t2|text|content")
stats.submit_packets("_e{2,23}:t3|First line\\nSecond line") # \n is a newline
stats.submit_packets(u"_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪") # utf-8 compliant
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
nt.assert_equal(first["msg_text"], "")
nt.assert_equal(second["msg_text"], "text|content")
nt.assert_equal(third["msg_text"], "First line\nSecond line")
nt.assert_equal(fourth["msg_text"], u"♬ †øU †øU ¥ºu T0µ ♪")
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get('developer_mode') and psutil is not None
self._internal_profiling_stats = None
self.hostname = agentConfig.get('checksd_hostname') or get_hostname(agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.aggregator = MetricsAggregator(
self.hostname,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get('recent_point_threshold', None),
histogram_aggregates=agentConfig.get('histogram_aggregates'),
histogram_percentiles=agentConfig.get('histogram_percentiles')
)
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
def test_event_text(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_e{2,0}:t1|')
stats.submit_packets('_e{2,12}:t2|text|content')
stats.submit_packets('_e{2,23}:t3|First line\\nSecond line') # \n is a newline
stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪') # utf-8 compliant
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
nt.assert_equal(first['msg_text'], '')
nt.assert_equal(second['msg_text'], 'text|content')
nt.assert_equal(third['msg_text'], 'First line\nSecond line')
nt.assert_equal(fourth['msg_text'], u'♬ †øU †øU ¥ºu T0µ ♪')
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self.name = name
self.init_config = init_config
self.agentConfig = agentConfig
self.hostname = get_hostname(agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.aggregator = MetricsAggregator(self.hostname, formatter=agent_formatter, recent_point_threshold=agentConfig.get('recent_point_threshold', None))
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
def test_batch_submission(self):
# Submit a sampled histogram.
stats = MetricsAggregator('myhost')
metrics = [
'counter:1|c',
'counter:1|c',
'gauge:1|g'
]
packet = "\n".join(metrics)
stats.submit_packets(packet)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(2, len(metrics))
counter, gauge = metrics
assert counter[2] == 2
assert gauge[2] == 1
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self._enabled_checks.append(name)
self._enabled_checks = list(set(self._enabled_checks))
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get("developer_mode") and psutil
self._internal_profiling_stats = None
self.default_integration_http_timeout = float(agentConfig.get("default_integration_http_timeout", 9))
self.hostname = agentConfig.get("checksd_hostname") or get_hostname(agentConfig)
self.log = logging.getLogger("%s.%s" % (__name__, name))
self.min_collection_interval = self.init_config.get(
"min_collection_interval", self.DEFAULT_MIN_COLLECTION_INTERVAL
)
self.aggregator = MetricsAggregator(
self.hostname,
expiry_seconds=self.min_collection_interval + self.DEFAULT_EXPIRY_SECONDS,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get("recent_point_threshold", None),
histogram_aggregates=agentConfig.get("histogram_aggregates"),
histogram_percentiles=agentConfig.get("histogram_percentiles"),
)
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
self._instance_metadata = []
self.svc_metadata = []
self.historate_dict = {}
# Set proxy settings
self.proxy_settings = get_proxy(self.agentConfig)
self._use_proxy = False if init_config is None else init_config.get("use_agent_proxy", True)
self.proxies = {"http": None, "https": None}
if self.proxy_settings and self._use_proxy:
uri = "{host}:{port}".format(host=self.proxy_settings["host"], port=self.proxy_settings["port"])
if self.proxy_settings["user"] and self.proxy_settings["password"]:
uri = "{user}:{password}@{uri}".format(
user=self.proxy_settings["user"], password=self.proxy_settings["password"], uri=uri
)
self.proxies["http"] = "http://{uri}".format(uri=uri)
self.proxies["https"] = "https://{uri}".format(uri=uri)
def test_histogram_normalization(self):
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
interval=10,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
for i in range(5):
stats.submit_packets('h1:1|h')
for i in range(20):
stats.submit_packets('h2:1|h')
metrics = self.sort_metrics(stats.flush())
_, _, h1count, _, _, _, \
_, _, h2count, _, _, _ = metrics
nt.assert_equal(h1count['points'][0][1], 0.5)
nt.assert_equal(h2count['points'][0][1], 2)
def test_service_check_basic(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0')
stats.submit_packets('_sc|check.2|1')
stats.submit_packets('_sc|check.3|2')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 3
first, second, third = service_checks
assert first['check'] == 'check.1'
assert first['status'] == 0
assert second['check'] == 'check.2'
assert second['status'] == 1
assert third['check'] == 'check.3'
assert third['status'] == 2
def test_service_check_basic(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0')
stats.submit_packets('_sc|check.2|1')
stats.submit_packets('_sc|check.3|2')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 3
first, second, third = service_checks
nt.assert_equal(first['check'], 'check.1')
nt.assert_equal(first['status'], 0)
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['status'], 1)
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['status'], 2)
def test_event_text_utf8(self):
stats = MetricsAggregator('myhost', utf8_decoding=True)
# Should raise because content is not encoded
self.assertRaises(Exception, stats.submit_packets,
u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪'.encode(
'utf-8')) # utf-8 compliant
# Normal packet
stats.submit_packets(
'_e{2,23}:t3|First line\\nSecond line') # \n is a newline
events = self.sort_events(stats.flush_events())
assert len(events) == 2
nt.assert_equal(events[0]['msg_text'], 'First line\nSecond line')
nt.assert_equal(events[1]['msg_text'], u'♬ †øU †øU ¥ºu T0µ ♪')
def test_spurr(subprocess_patch):
# defer import to test to avoid breaking get_subprocess_output
# patching.
from datadog_checks.lparstats import LPARStats
hostname = 'foo'
aggregator = MetricsAggregator(
hostname,
interval=1.0,
histogram_aggregates=None,
histogram_percentiles=None,
)
c = LPARStats("lparstats", {}, {}, aggregator)
c.collect_spurr()
metrics = c.aggregator.flush(
)[:-1] # we remove the datadog.agent.running metric
expected_metrics = [
'system.lpar.spurr.user',
'system.lpar.spurr.sys',
'system.lpar.spurr.wait',
'system.lpar.spurr.idle',
'system.lpar.spurr.user.norm',
'system.lpar.spurr.sys.norm',
'system.lpar.spurr.wait.norm',
'system.lpar.spurr.idle.norm',
'system.lpar.spurr.user.pct',
'system.lpar.spurr.sys.pct',
'system.lpar.spurr.wait.pct',
'system.lpar.spurr.idle.pct',
'system.lpar.spurr.user.norm.pct',
'system.lpar.spurr.sys.norm.pct',
'system.lpar.spurr.wait.norm.pct',
'system.lpar.spurr.idle.norm.pct',
]
assert len(metrics) == len(expected_metrics)
for metric in metrics:
assert metric['metric'] in expected_metrics
def init(config_path=None, use_watchdog=False, use_forwarder=False):
"""Configure the server and the reporting thread.
"""
c = get_config(parse_args=False, cfg_path=config_path)
log.debug("Configuration dogstatsd")
port = c['dogstatsd_port']
interval = int(c['dogstatsd_interval'])
api_key = c['api_key']
non_local_traffic = c['non_local_traffic']
target = c['dd_url']
if use_forwarder:
target = c['dogstatsd_target']
hostname = get_hostname(c)
# Create the aggregator (which is the point of communication between the
# server and reporting threads.
assert 0 < interval
aggregator = MetricsAggregator(hostname,
interval,
recent_point_threshold=c.get(
'recent_point_threshold', None))
# Start the reporting thread.
reporter = Reporter(interval, aggregator, target, api_key, use_watchdog)
# Start the server on an IPv4 stack
# Default to loopback
server_host = '127.0.0.1'
# If specified, bind to all addressses
if non_local_traffic:
server_host = ''
server = Server(aggregator, server_host, port)
return reporter, server, c
def test_memory_entitlements(subprocess_patch):
# defer import to test to avoid breaking get_subprocess_output
# patching.
from datadog_checks.lparstats import LPARStats
hostname = 'foo'
aggregator = MetricsAggregator(
hostname,
interval=1.0,
histogram_aggregates=None,
histogram_percentiles=None,
)
c = LPARStats("lparstats", {}, {}, aggregator)
c.collect_memory_entitlements()
metrics = c.aggregator.flush(
)[:-1] # we remove the datadog.agent.running metric
expected_metrics = [
'system.lpar.memory.entitlement.iomin',
'system.lpar.memory.entitlement.iodes',
'system.lpar.memory.entitlement.iomu',
'system.lpar.memory.entitlement.iores',
'system.lpar.memory.entitlement.iohwm',
'system.lpar.memory.entitlement.iomaf',
]
# compile entitlements from mock output
output = list(filter(None, AIX_LPARSTATS_MEMORY_ENTITLEMENTS.splitlines()))
output = output[c.MEMORY_ENTITLEMENTS_START_IDX + 1:]
entitlements = collect_column(output, 0)
assert len(metrics) == (len(expected_metrics) * len(entitlements))
for metric in metrics:
for tag in metric['tags']:
tag = tag.decode('utf-8')
if 'iompn' in tag:
assert tag.split(':')[1] in entitlements
def test_memory_page(subprocess_patch):
# defer import to test to avoid breaking get_subprocess_output
# patching.
from datadog_checks.lparstats import LPARStats
hostname = 'foo'
aggregator = MetricsAggregator(
hostname,
interval=1.0,
histogram_aggregates=None,
histogram_percentiles=None,
)
c = LPARStats("lparstats", {}, {}, aggregator)
c.collect_memory(page_stats=True)
metrics = c.aggregator.flush(
)[:-1] # we remove the datadog.agent.running metric
# NOTE: iomf unavailable
expected_metrics = [
'system.lpar.memory.physb',
'system.lpar.memory.hpi',
'system.lpar.memory.hpit',
'system.lpar.memory.pmem',
'system.lpar.memory.iomu',
'system.lpar.memory.iomin',
'system.lpar.memory.iohwm',
'system.lpar.memory.iomaf',
'system.lpar.memory.pgcol',
'system.lpar.memory.mpgcol',
'system.lpar.memory.ccol',
'system.lpar.memory.entc',
'system.lpar.memory.vcsw',
]
assert len(metrics) == len(expected_metrics)
for metric in metrics:
assert metric['metric'] in expected_metrics
def test_disk_basic(disk_io_counters, disk_usage, disk_partitions):
from datadog_checks.disk import Disk # delayed import for good patching
disk_partitions.return_value = MOCK_PARTITIONS
aggregator = MetricsAggregator(
HOSTNAME,
interval=1.0,
histogram_aggregates=None,
histogram_percentiles=None,
)
total_gauges, expected_gauges = generate_expected_gauges()
total_rates, expected_rates = generate_expected_rates()
c = Disk("disk", {}, {}, aggregator)
c.check({})
metrics = c.aggregator.flush(
)[:-1] # we remove the datadog.agent.running metric
assert len(metrics) == total_gauges
time.sleep(1)
c.check({})
metrics = c.aggregator.flush(
)[:-1] # we remove the datadog.agent.running metric
assert len(metrics) == (total_gauges + total_rates)
for metric in metrics:
assert metric['metric'] in expected_gauges or metric[
'metric'] in expected_rates
assert len(metric['points']) == 1
assert metric['host'] == HOSTNAME
assert metric['type'] == GAUGE
assert is_metric_expected(expected_gauges,
metric) or is_metric_expected(
expected_rates, metric)
class AgentCheck(object):
OK, WARNING, CRITICAL, UNKNOWN = (0, 1, 2, 3)
SOURCE_TYPE_NAME = None
DEFAULT_MIN_COLLECTION_INTERVAL = 0
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get(
'developer_mode') and psutil is not None
self._internal_profiling_stats = None
self.hostname = agentConfig.get('checksd_hostname') or get_hostname(
agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.aggregator = MetricsAggregator(
self.hostname,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get('recent_point_threshold',
None),
histogram_aggregates=agentConfig.get('histogram_aggregates'),
histogram_percentiles=agentConfig.get('histogram_percentiles'))
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
self._instance_metadata = []
self.svc_metadata = []
def instance_count(self):
""" Return the number of instances that are configured for this check. """
return len(self.instances)
def gauge(self,
metric,
value,
tags=None,
hostname=None,
device_name=None,
timestamp=None):
"""
Record the value of a gauge, with optional tags, hostname and device
name.
:param metric: The name of the metric
:param value: The value of the gauge
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
:param timestamp: (optional) The timestamp for this metric value
"""
self.aggregator.gauge(metric, value, tags, hostname, device_name,
timestamp)
def increment(self,
metric,
value=1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to increment by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.increment(metric, value, tags, hostname, device_name)
def decrement(self,
metric,
value=-1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to decrement by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.decrement(metric, value, tags, hostname, device_name)
def count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
"""
Submit a raw count with optional tags, hostname and device name
:param metric: The name of the metric
:param value: The value
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.submit_count(metric, value, tags, hostname,
device_name)
def monotonic_count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
"""
Submits a raw count with optional tags, hostname and device name
based on increasing counter values. E.g. 1, 3, 5, 7 will submit
6 on flush. Note that reset counters are skipped.
:param metric: The name of the metric
:param value: The value of the rate
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.count_from_counter(metric, value, tags, hostname,
device_name)
def rate(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Submit a point for a metric that will be calculated as a rate on flush.
Values will persist across each call to `check` if there is not enough
point to generate a rate on the flush.
:param metric: The name of the metric
:param value: The value of the rate
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.rate(metric, value, tags, hostname, device_name)
def histogram(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
"""
Sample a histogram value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to sample for the histogram
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.histogram(metric, value, tags, hostname, device_name)
def set(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Sample a set value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value for the set
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.set(metric, value, tags, hostname, device_name)
def event(self, event):
"""
Save an event.
:param event: The event payload as a dictionary. Has the following
structure:
{
"timestamp": int, the epoch timestamp for the event,
"event_type": string, the event time name,
"agent_key": string, the api key of the account to associate the event with,
"msg_title": string, the title of the event,
"msg_text": string, the text body of the event,
"alert_type": (optional) string, one of ('error', 'warning', 'success', 'info').
Defaults to 'info'.
"source_type_name": (optional) string, the source type name,
"host": (optional) string, the name of the host,
"tags": (optional) list, a list of tags to associate with this event
}
"""
# Events are disabled.
return
if event.get('agent_key') is None:
event['agent_key'] = self.agentConfig['agent_key']
self.events.append(event)
def service_check(self,
check_name,
status,
tags=None,
timestamp=None,
hostname=None,
check_run_id=None,
message=None):
"""
Save a service check.
:param check_name: string, name of the service check
:param status: int, describing the status.
0 for success, 1 for warning, 2 for failure
:param tags: (optional) list of strings, a list of tags for this run
:param timestamp: (optional) float, unix timestamp for when the run occurred
:param hostname: (optional) str, host that generated the service
check. Defaults to the host_name of the agent
:param check_run_id: (optional) int, id used for logging and tracing
purposes. Don't need to be unique. If not
specified, one will be generated.
"""
if hostname is None:
hostname = self.hostname
if message is not None:
message = str(message)
self.service_checks.append(
create_service_check(check_name, status, tags, timestamp, hostname,
check_run_id, message))
def service_metadata(self, meta_name, value):
"""
Save metadata.
:param meta_name: metadata key name
:type meta_name: string
:param value: metadata value
:type value: string
"""
self._instance_metadata.append((meta_name, str(value)))
def has_events(self):
"""
Check whether the check has saved any events
@return whether or not the check has saved any events
@rtype boolean
"""
return len(self.events) > 0
def get_metrics(self):
"""
Get all metrics, including the ones that are tagged.
@return the list of samples
@rtype [(metric_name, timestamp, value, {"tags": ["tag1", "tag2"]}), ...]
"""
return self.aggregator.flush()
def get_events(self):
"""
Return a list of the events saved by the check, if any
@return the list of events saved by this check
@rtype list of event dictionaries
"""
events = self.events
self.events = []
return events
def get_service_checks(self):
"""
Return a list of the service checks saved by the check, if any
and clears them out of the instance's service_checks list
@return the list of service checks saved by this check
@rtype list of service check dicts
"""
service_checks = self.service_checks
self.service_checks = []
return service_checks
def _roll_up_instance_metadata(self):
"""
Concatenate and flush instance metadata.
"""
self.svc_metadata.append(
dict((k, v) for (k, v) in self._instance_metadata))
self._instance_metadata = []
def get_service_metadata(self):
"""
Return a list of the metadata dictionaries saved by the check -if any-
and clears them out of the instance's service_checks list
@return the list of metadata saved by this check
@rtype list of metadata dicts
"""
if self._instance_metadata:
self._roll_up_instance_metadata()
service_metadata = self.svc_metadata
self.svc_metadata = []
return service_metadata
def has_warnings(self):
"""
Check whether the instance run created any warnings
"""
return len(self.warnings) > 0
def warning(self, warning_message):
""" Add a warning message that will be printed in the info page
:param warning_message: String. Warning message to be displayed
"""
self.warnings.append(str(warning_message))
def get_library_info(self):
if self.library_versions is not None:
return self.library_versions
try:
self.library_versions = self.get_library_versions()
except NotImplementedError:
pass
def get_library_versions(self):
""" Should return a string that shows which version
of the needed libraries are used """
raise NotImplementedError
def get_warnings(self):
"""
Return the list of warnings messages to be displayed in the info page
"""
warnings = self.warnings
self.warnings = []
return warnings
@staticmethod
def _get_statistic_name_from_method(method_name):
return method_name[4:] if method_name.startswith(
'get_') else method_name
@staticmethod
def _collect_internal_stats(methods=None):
current_process = psutil.Process(os.getpid())
methods = methods or DEFAULT_PSUTIL_METHODS
filtered_methods = [m for m in methods if hasattr(current_process, m)]
stats = {}
for method in filtered_methods:
# Go from `get_memory_info` -> `memory_info`
stat_name = AgentCheck._get_statistic_name_from_method(method)
try:
raw_stats = getattr(current_process, method)()
try:
stats[stat_name] = raw_stats._asdict()
except AttributeError:
if isinstance(raw_stats, numbers.Number):
stats[stat_name] = raw_stats
else:
log.warn(
"Could not serialize output of {0} to dict".format(
method))
except psutil.AccessDenied:
log.warn(
"Cannot call psutil method {0} : Access Denied".format(
method))
return stats
def _set_internal_profiling_stats(self, before, after):
self._internal_profiling_stats = {'before': before, 'after': after}
def _get_internal_profiling_stats(self):
"""
If in developer mode, return a dictionary of statistics about the check run
"""
stats = self._internal_profiling_stats
self._internal_profiling_stats = None
return stats
def run(self):
""" Run all instances. """
# Store run statistics if needed
before, after = None, None
if self.in_developer_mode and self.name != AGENT_METRICS_CHECK_NAME:
try:
before = AgentCheck._collect_internal_stats()
except Exception: # It's fine if we can't collect stats for the run, just log and proceed
self.log.debug(
"Failed to collect Agent Stats before check {0}".format(
self.name))
instance_statuses = []
for i, instance in enumerate(self.instances):
try:
min_collection_interval = instance.get(
'min_collection_interval',
self.init_config.get('min_collection_interval',
self.DEFAULT_MIN_COLLECTION_INTERVAL))
now = time.time()
if now - self.last_collection_time[i] < min_collection_interval:
self.log.debug(
"Not running instance #{0} of check {1} as it ran less than {2}s ago"
.format(i, self.name, min_collection_interval))
continue
self.last_collection_time[i] = now
check_start_time = None
if self.in_developer_mode:
check_start_time = timeit.default_timer()
self.check(copy.deepcopy(instance))
instance_check_stats = None
if check_start_time is not None:
instance_check_stats = {
'run_time': timeit.default_timer() - check_start_time
}
if self.has_warnings():
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_WARNING,
warnings=self.get_warnings(),
instance_check_stats=instance_check_stats)
else:
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_OK,
instance_check_stats=instance_check_stats)
except Exception, e:
self.log.exception("Check '%s' instance #%s failed" %
(self.name, i))
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_ERROR,
error=str(e),
tb=traceback.format_exc())
finally:
def test_gauge(self):
stats = MetricsAggregator('myhost')
# Track some counters.
stats.submit_packets('my.first.gauge:1|g')
stats.submit_packets('my.first.gauge:5|g')
stats.submit_packets('my.second.gauge:1.5|g')
# Ensure that gauges roll up correctly.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
first, second = metrics
nt.assert_equals(first['metric'], 'my.first.gauge')
nt.assert_equals(first['points'][0][1], 5)
nt.assert_equals(first['host'], 'myhost')
nt.assert_equals(second['metric'], 'my.second.gauge')
nt.assert_equals(second['points'][0][1], 1.5)
# Ensure that old gauges get dropped due to old timestamps
stats.gauge('my.first.gauge', 5)
stats.gauge('my.first.gauge', 1, timestamp=1000000000)
stats.gauge('my.second.gauge', 20, timestamp=1000000000)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
first = metrics[0]
nt.assert_equals(first['metric'], 'my.first.gauge')
nt.assert_equals(first['points'][0][1], 5)
nt.assert_equals(first['host'], 'myhost')
def test_event_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_e{6,4}:title1|text')
stats.submit_packets('_e{6,4}:title2|text|#t1')
stats.submit_packets('_e{6,4}:title3|text|#t1,t2:v2,t3,t4')
stats.submit_packets('_e{6,4}:title4|text|k:key|p:normal|#t1,t2')
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
try:
first['tags']
except Exception:
assert True
else:
assert False, "event['tags'] shouldn't be defined when no tags aren't explicited in the packet"
nt.assert_equal(first['msg_title'], 'title1')
nt.assert_equal(first['msg_text'], 'text')
nt.assert_equal(second['msg_title'], 'title2')
nt.assert_equal(second['msg_text'], 'text')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['msg_title'], 'title3')
nt.assert_equal(third['msg_text'], 'text')
nt.assert_equal(third['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
nt.assert_equal(fourth['msg_title'], 'title4')
nt.assert_equal(fourth['msg_text'], 'text')
nt.assert_equal(fourth['aggregation_key'], 'key')
nt.assert_equal(fourth['priority'], 'normal')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2']))
def test_event_title(self):
stats = MetricsAggregator('myhost', utf8_decoding=True)
stats.submit_packets('_e{0,4}:|text')
stats.submit_packets(
u'_e{9,4}:2intitulé|text'.encode('utf-8')) # comes from socket
stats.submit_packets('_e{14,4}:3title content|text')
stats.submit_packets('_e{14,4}:4title|content|text')
stats.submit_packets(
'_e{13,4}:5title\\ntitle|text') # \n stays escaped
events = self.sort_events(stats.flush_events())
assert len(events) == 5
nt.assert_equal(events[0]['msg_title'], '')
nt.assert_equal(events[1]['msg_title'], u'2intitulé')
nt.assert_equal(events[2]['msg_title'], '3title content')
nt.assert_equal(events[3]['msg_title'], '4title|content')
nt.assert_equal(events[4]['msg_title'], '5title\\ntitle')
def test_metrics_expiry(self):
# Ensure metrics eventually expire and stop submitting.
ag_interval = 1
expiry = ag_interval * 4 + 2
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
interval=ag_interval,
expiry_seconds=expiry,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
stats.submit_packets('test.counter:123|c')
stats.submit_packets('test.gauge:55|g')
stats.submit_packets('test.set:44|s')
stats.submit_packets('test.histogram:11|h')
# Ensure points keep submitting
time.sleep(ag_interval)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 9)
nt.assert_equal(metrics[0]['metric'], 'test.counter')
nt.assert_equal(metrics[0]['points'][0][1], 123)
time.sleep(ag_interval)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 1)
nt.assert_equal(metrics[0]['metric'], 'test.counter')
nt.assert_equal(metrics[0]['points'][0][1], 0)
time.sleep(ag_interval)
time.sleep(0.5)
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 1)
nt.assert_equal(metrics[0]['metric'], 'test.counter')
nt.assert_equal(metrics[0]['points'][0][1], 0)
# Now sleep for longer than the expiry window and ensure
# no points are submitted
time.sleep(ag_interval)
time.sleep(2)
m = stats.flush()
assert not m, str(m)
# If we submit again, we're all good.
stats.submit_packets('test.counter:123|c')
stats.submit_packets('test.gauge:55|g')
stats.submit_packets('test.set:44|s')
stats.submit_packets('test.histogram:11|h')
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 9)
nt.assert_equal(metrics[0]['metric'], 'test.counter')
nt.assert_equal(metrics[0]['points'][0][1], 123)
def test_histogram_counter(self):
# Test whether histogram.count == increment
# same deal with a sample rate
cnt = 100000
for run in [1, 2]:
stats = MetricsAggregator('myhost')
for i in xrange(cnt):
if run == 2:
stats.submit_packets('test.counter:1|c|@0.5')
stats.submit_packets('test.hist:1|ms|@0.5')
else:
stats.submit_packets('test.counter:1|c')
stats.submit_packets('test.hist:1|ms')
metrics = self.sort_metrics(stats.flush())
assert len(metrics) > 0
nt.assert_equal([
m['points'][0][1]
for m in metrics if m['metric'] == 'test.counter'
], [cnt * run])
nt.assert_equal([
m['points'][0][1]
for m in metrics if m['metric'] == 'test.hist.count'
], [cnt * run])
class AgentCheck(object):
def __init__(self, name, init_config, agentConfig):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
"""
from aggregator import MetricsAggregator
self.name = name
self.init_config = init_config
self.agentConfig = agentConfig
self.hostname = gethostname(agentConfig)
self.log = logging.getLogger('checks.%s' % name)
self.aggregator = MetricsAggregator(self.hostname,
formatter=agent_formatter)
self.events = []
def gauge(self,
metric,
value,
tags=None,
hostname=None,
device_name=None,
timestamp=None):
"""
Record the value of a gauge, with optional tags, hostname and device
name.
:param metric: The name of the metric
:param value: The value of the gauge
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
:param timestamp: (optional) The timestamp for this metric value
"""
self.aggregator.gauge(metric, value, tags, hostname, device_name,
timestamp)
def increment(self,
metric,
value=1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to increment by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.increment(metric, value, tags, hostname, device_name)
def decrement(self,
metric,
value=-1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to decrement by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.decrement(metric, value, tags, hostname, device_name)
def rate(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Submit a point for a metric that will be calculated as a rate on flush.
Values will persist across each call to `check` if there is not enough
point to generate a rate on the flush.
:param metric: The name of the metric
:param value: The value of the rate
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.rate(metric, value, tags, hostname, device_name)
def histogram(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
"""
Sample a histogram value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to sample for the histogram
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.histogram(metric, value, tags, hostname, device_name)
def set(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Sample a set value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value for the set
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.set(metric, value, tags, hostname, device_name)
def event(self, event):
"""
Save an event.
:param event: The event payload as a dictionary. Has the following
structure:
{
"timestamp": int, the epoch timestamp for the event,
"event_type": string, the event time name,
"api_key": string, the api key of the account to associate the event with,
"msg_title": string, the title of the event,
"msg_text": string, the text body of the event,
"alert_type": (optional) string, one of ('error', 'warning', 'success', 'info').
Defaults to 'info'.
"source_type_name": (optional) string, the source type name,
"host": (optional) string, the name of the host,
"tags": (optional) list, a list of tags to associate with this event
}
"""
self.events.append(event)
def has_events(self):
"""
Check whether the check has saved any events
@return whether or not the check has saved any events
@rtype boolean
"""
return len(self.events) > 0
def get_metrics(self):
"""
Get all metrics, including the ones that are tagged.
@return the list of samples
@rtype [(metric_name, timestamp, value, {"tags": ["tag1", "tag2"]}), ...]
"""
return self.aggregator.flush()
def get_events(self):
"""
Return a list of the events saved by the check, if any
@return the list of events saved by this check
@rtype list of event dictionaries
"""
events = self.events
self.events = []
return events
def check(self, instance):
"""
Overriden by the check class. This will be called to run the check.
:param instance: A dict with the instance information. This will vary
depending on your config structure.
"""
raise NotImplementedError()
@classmethod
def from_yaml(cls,
path_to_yaml=None,
agentConfig=None,
yaml_text=None,
check_name=None):
"""
A method used for testing your check without running the agent.
"""
from util import yaml, yLoader
if path_to_yaml:
check_name = os.path.basename(path_to_yaml).split('.')[0]
try:
f = open(path_to_yaml)
except IOError:
raise Exception('Unable to open yaml config: %s' %
path_to_yaml)
yaml_text = f.read()
f.close()
config = yaml.load(yaml_text, Loader=yLoader)
check = cls(check_name,
config.get('init_config') or {}, agentConfig or {})
return check, config.get('instances', [])
def normalize(self, metric, prefix=None):
"""
Turn a metric into a well-formed metric name
prefix.b.c
:param metric The metric name to normalize
:param prefix A prefix to to add to the normalized name, default None
"""
name = re.sub(r"[,\+\*\-/()\[\]{}]", "_", metric)
# Eliminate multiple _
name = re.sub(r"__+", "_", name)
# Don't start/end with _
name = re.sub(r"^_", "", name)
name = re.sub(r"_$", "", name)
# Drop ._ and _.
name = re.sub(r"\._", ".", name)
name = re.sub(r"_\.", ".", name)
if prefix is not None:
return prefix + "." + name
else:
return name
def test_formatter(self):
stats = MetricsAggregator('myhost',
interval=10,
formatter=get_formatter(
{"statsd_metric_namespace": "datadog"}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "datadog.gauge")
stats = MetricsAggregator(
'myhost',
interval=10,
formatter=get_formatter({"statsd_metric_namespace": "datadoge."}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "datadoge.gauge")
stats = MetricsAggregator('myhost',
interval=10,
formatter=get_formatter(
{"statsd_metric_namespace": None}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "gauge")
def test_recent_point_threshold(self):
threshold = 100
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
recent_point_threshold=threshold,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
timestamp_beyond_threshold = time.time() - threshold * 2
timestamp_within_threshold = time.time() - threshold / 2
# Ensure that old gauges get dropped due to old timestamps
stats.submit_metric('my.first.gauge', 5, 'g')
stats.submit_metric('my.first.gauge',
1,
'g',
timestamp=timestamp_beyond_threshold)
stats.submit_metric('my.second.gauge',
20,
'g',
timestamp=timestamp_beyond_threshold)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
first = metrics[0]
nt.assert_equals(first['metric'], 'my.first.gauge')
nt.assert_equals(first['points'][0][1], 5)
nt.assert_equals(first['host'], 'myhost')
# Ensure that old gauges get dropped due to old timestamps
stats.submit_metric('my.1.gauge', 5, 'g')
stats.submit_metric('my.1.gauge',
1,
'g',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.2.counter',
20,
'c',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.3.set',
20,
's',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.4.histogram',
20,
'h',
timestamp=timestamp_within_threshold)
flush_timestamp = time.time()
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 9)
first, second, third, h1, h2, h3, h4, h5, h6 = metrics
nt.assert_equals(first['metric'], 'my.1.gauge')
nt.assert_equals(first['points'][0][1], 1)
nt.assert_equals(first['host'], 'myhost')
self.assert_almost_equal(first['points'][0][0],
timestamp_within_threshold, 0.1)
nt.assert_equals(second['metric'], 'my.2.counter')
nt.assert_equals(second['points'][0][1], 20)
self.assert_almost_equal(second['points'][0][0], flush_timestamp, 0.1)
nt.assert_equals(third['metric'], 'my.3.set')
nt.assert_equals(third['points'][0][1], 1)
self.assert_almost_equal(third['points'][0][0], flush_timestamp, 0.1)
nt.assert_equals(h1['metric'], 'my.4.histogram.95percentile')
nt.assert_equals(h1['points'][0][1], 20)
self.assert_almost_equal(h1['points'][0][0], flush_timestamp, 0.1)
nt.assert_equal(h1['points'][0][0], h2['points'][0][0])
nt.assert_equal(h1['points'][0][0], h3['points'][0][0])
nt.assert_equal(h1['points'][0][0], h4['points'][0][0])
nt.assert_equal(h1['points'][0][0], h5['points'][0][0])
def test_service_check_message(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0|m:testing')
stats.submit_packets('_sc|check.2|0|m:First line\\nSecond line')
stats.submit_packets(u'_sc|check.3|0|m:♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets('_sc|check.4|0|m:|t:|m\:|d:')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
nt.assert_equal(first['check'], 'check.1')
nt.assert_equal(first['message'], 'testing')
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['message'], 'First line\nSecond line')
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['message'], u'♬ †øU †øU ¥ºu T0µ ♪')
nt.assert_equal(fourth['check'], 'check.4')
nt.assert_equal(fourth['message'], '|t:|m:|d:')
def test_magic_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.gauge.a:1|c|#host:test-a')
stats.submit_packets('my.gauge.b:4|c|#tag1,tag2,host:test-b')
stats.submit_packets('my.gauge.b:8|c|#host:test-b,tag2,tag1')
stats.submit_packets('my.gauge.c:10|c|#tag3')
stats.submit_packets('my.gauge.c:16|c|#device:floppy,tag3')
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 4)
first, second, third, fourth = metrics
nt.assert_equal(first['metric'], 'my.gauge.a')
nt.assert_equal(first['tags'], None)
nt.assert_equal(first['points'][0][1], 1)
nt.assert_equal(first['host'], 'test-a')
nt.assert_equal(second['metric'], 'my.gauge.b')
nt.assert_equal(second['tags'], ('tag1', 'tag2'))
nt.assert_equal(second['points'][0][1], 12)
nt.assert_equal(second['host'], 'test-b')
nt.assert_equal(third['metric'], 'my.gauge.c')
nt.assert_equal(third['tags'], ('tag3', ))
nt.assert_equal(third['points'][0][1], 10)
nt.assert_equal(third['device_name'], None)
nt.assert_equal(fourth['metric'], 'my.gauge.c')
nt.assert_equal(fourth['tags'], ('tag3', ))
nt.assert_equal(fourth['points'][0][1], 16)
nt.assert_equal(fourth['device_name'], 'floppy')
def test_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('gauge:1|c')
stats.submit_packets('gauge:2|c|@1')
stats.submit_packets('gauge:4|c|#tag1,tag2')
stats.submit_packets(
'gauge:8|c|#tag2,tag1') # Should be the same as above
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
nt.assert_equal(first['metric'], 'gauge')
nt.assert_equal(first['tags'], None)
nt.assert_equal(first['points'][0][1], 3)
nt.assert_equal(first['host'], 'myhost')
nt.assert_equal(second['metric'], 'gauge')
nt.assert_equal(second['tags'], ('tag1', 'tag2'))
nt.assert_equal(second['points'][0][1], 12)
nt.assert_equal(second['host'], 'myhost')
nt.assert_equal(third['metric'], 'gauge')
nt.assert_equal(third['tags'], ('tag3', 'tag4'))
nt.assert_equal(third['points'][0][1], 16)
nt.assert_equal(third['host'], 'myhost')
def test_event_text(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_e{2,0}:t1|')
stats.submit_packets('_e{2,12}:t2|text|content')
stats.submit_packets(
'_e{2,23}:t3|First line\\nSecond line') # \n is a newline
stats.submit_packets(
u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪') # utf-8 compliant
events = self.sort_events(stats.flush_events())
assert len(events) == 4
first, second, third, fourth = events
nt.assert_equal(first['msg_text'], '')
nt.assert_equal(second['msg_text'], 'text|content')
nt.assert_equal(third['msg_text'], 'First line\nSecond line')
nt.assert_equal(fourth['msg_text'], u'♬ †øU †øU ¥ºu T0µ ♪')
def test_service_check_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0')
stats.submit_packets('_sc|check.2|0|#t1')
stats.submit_packets('_sc|check.3|0|h:i-abcd1234|#t1,t2|m:fakeout#t5')
stats.submit_packets('_sc|check.4|0|#t1,t2:v2,t3,t4')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
nt.assert_equal(first['check'], 'check.1')
assert first.get('tags') is None, "service_check['tags'] shouldn't be" + \
"defined when no tags aren't explicited in the packet"
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['host_name'], 'i-abcd1234')
nt.assert_equal(third['message'], 'fakeout#t5')
nt.assert_equal(third['tags'], sorted(['t1', 't2']))
nt.assert_equal(fourth['check'], 'check.4')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
class AgentCheck(object):
OK, WARNING, CRITICAL, UNKNOWN = (0, 1, 2, 3)
SOURCE_TYPE_NAME = None
DEFAULT_EXPIRY_SECONDS = 300
DEFAULT_MIN_COLLECTION_INTERVAL = 0
_enabled_checks = []
@classmethod
def is_check_enabled(cls, name):
return name in cls._enabled_checks
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self._enabled_checks.append(name)
self._enabled_checks = list(set(self._enabled_checks))
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get('developer_mode') and psutil
self._internal_profiling_stats = None
self.default_integration_http_timeout = float(
agentConfig.get('default_integration_http_timeout', 9))
self.hostname = agentConfig.get('checksd_hostname') or get_hostname(
agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.min_collection_interval = self.init_config.get(
'min_collection_interval', self.DEFAULT_MIN_COLLECTION_INTERVAL)
self.aggregator = MetricsAggregator(
self.hostname,
expiry_seconds=self.min_collection_interval +
self.DEFAULT_EXPIRY_SECONDS,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get('recent_point_threshold',
None),
histogram_aggregates=agentConfig.get('histogram_aggregates'),
histogram_percentiles=agentConfig.get('histogram_percentiles'))
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
self._instance_metadata = []
self.svc_metadata = []
self.historate_dict = {}
# Set proxy settings
self.proxy_settings = get_proxy(self.agentConfig)
self._use_proxy = False if init_config is None else init_config.get(
"use_agent_proxy", True)
self.proxies = {
"http": None,
"https": None,
}
if self.proxy_settings and self._use_proxy:
uri = "{host}:{port}".format(host=self.proxy_settings['host'],
port=self.proxy_settings['port'])
if self.proxy_settings['user'] and self.proxy_settings['password']:
uri = "{user}:{password}@{uri}".format(
user=self.proxy_settings['user'],
password=self.proxy_settings['password'],
uri=uri)
self.proxies['http'] = "http://{uri}".format(uri=uri)
self.proxies['https'] = "https://{uri}".format(uri=uri)
def instance_count(self):
""" Return the number of instances that are configured for this check. """
return len(self.instances)
def gauge(self,
metric,
value,
tags=None,
hostname=None,
device_name=None,
timestamp=None):
"""
Record the value of a gauge, with optional tags, hostname and device
name.
:param metric: The name of the metric
:param value: The value of the gauge
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
:param timestamp: (optional) The timestamp for this metric value
"""
self.aggregator.gauge(metric, value, tags, hostname, device_name,
timestamp)
def increment(self,
metric,
value=1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to increment by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.increment(metric, value, tags, hostname, device_name)
def decrement(self,
metric,
value=-1,
tags=None,
hostname=None,
device_name=None):
"""
Increment a counter with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to decrement by
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.decrement(metric, value, tags, hostname, device_name)
def count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
"""
Submit a raw count with optional tags, hostname and device name
:param metric: The name of the metric
:param value: The value
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.submit_count(metric, value, tags, hostname,
device_name)
def monotonic_count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
"""
Submits a raw count with optional tags, hostname and device name
based on increasing counter values. E.g. 1, 3, 5, 7 will submit
6 on flush. Note that reset counters are skipped.
:param metric: The name of the metric
:param value: The value of the rate
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.count_from_counter(metric, value, tags, hostname,
device_name)
def rate(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Submit a point for a metric that will be calculated as a rate on flush.
Values will persist across each call to `check` if there is not enough
point to generate a rate on the flush.
:param metric: The name of the metric
:param value: The value of the rate
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.rate(metric, value, tags, hostname, device_name)
def histogram(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
"""
Sample a histogram value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value to sample for the histogram
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.histogram(metric, value, tags, hostname, device_name)
@classmethod
def generate_historate_func(cls, excluding_tags):
def fct(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
cls.historate(self,
metric,
value,
excluding_tags,
tags=tags,
hostname=hostname,
device_name=device_name)
return fct
@classmethod
def generate_histogram_func(cls, excluding_tags):
def fct(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
tags = list(
tags
) # Use a copy of the list to avoid removing tags from originial
for tag in list(tags):
for exc_tag in excluding_tags:
if tag.startswith(exc_tag + ":"):
tags.remove(tag)
cls.histogram(self,
metric,
value,
tags=tags,
hostname=hostname,
device_name=device_name)
return fct
def historate(self,
metric,
value,
excluding_tags,
tags=None,
hostname=None,
device_name=None):
"""
Function to create a histogram metric for "rate" like metrics.
Warning this doesn't use the harmonic mean, beware of what it means when using it.
:param metric: The name of the metric
:param value: The value to sample for the histogram
:param excluding_tags: A list of tags that will be removed when computing the histogram
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
tags = list(
tags
) # Use a copy of the list to avoid removing tags from originial
context = [metric]
if tags is not None:
context.append("-".join(sorted(tags)))
if hostname is not None:
context.append("host:" + hostname)
if device_name is not None:
context.append("device:" + device_name)
now = time.time()
context = tuple(context)
if context in self.historate_dict:
if tags is not None:
for tag in list(tags):
for exc_tag in excluding_tags:
if tag.startswith("{0}:".format(exc_tag)):
tags.remove(tag)
prev_value, prev_ts = self.historate_dict[context]
rate = float(value - prev_value) / float(now - prev_ts)
self.aggregator.histogram(metric, rate, tags, hostname,
device_name)
self.historate_dict[context] = (value, now)
def set(self, metric, value, tags=None, hostname=None, device_name=None):
"""
Sample a set value, with optional tags, hostname and device name.
:param metric: The name of the metric
:param value: The value for the set
:param tags: (optional) A list of tags for this metric
:param hostname: (optional) A hostname for this metric. Defaults to the current hostname.
:param device_name: (optional) The device name for this metric
"""
self.aggregator.set(metric, value, tags, hostname, device_name)
def event(self, event):
"""
Save an event.
:param event: The event payload as a dictionary. Has the following
structure:
{
"timestamp": int, the epoch timestamp for the event,
"event_type": string, the event time name,
"msg_title": string, the title of the event,
"msg_text": string, the text body of the event,
"alert_type": (optional) string, one of ('error', 'warning', 'success', 'info').
Defaults to 'info'.
"source_type_name": (optional) string, the source type name,
"host": (optional) string, the name of the host,
"tags": (optional) list, a list of tags to associate with this event
}
"""
self.events.append(event)
def service_check(self,
check_name,
status,
tags=None,
timestamp=None,
hostname=None,
check_run_id=None,
message=None):
"""
Save a service check.
:param check_name: string, name of the service check
:param status: int, describing the status.
0 for success, 1 for warning, 2 for failure
:param tags: (optional) list of strings, a list of tags for this run
:param timestamp: (optional) float, unix timestamp for when the run occurred
:param hostname: (optional) str, host that generated the service
check. Defaults to the host_name of the agent
:param check_run_id: (optional) int, id used for logging and tracing
purposes. Doesn't need to be unique. If not
specified, one will be generated.
"""
if hostname is None:
hostname = self.hostname
if message is not None:
message = unicode(
message) # ascii converts to unicode but not viceversa
self.service_checks.append(
create_service_check(check_name, status, tags, timestamp, hostname,
check_run_id, message))
def service_metadata(self, meta_name, value):
"""
Save metadata.
:param meta_name: metadata key name
:type meta_name: string
:param value: metadata value
:type value: string
"""
self._instance_metadata.append((meta_name, unicode(value)))
def has_events(self):
"""
Check whether the check has saved any events
@return whether or not the check has saved any events
@rtype boolean
"""
return len(self.events) > 0
def get_metrics(self):
"""
Get all metrics, including the ones that are tagged.
@return the list of samples
@rtype [(metric_name, timestamp, value, {"tags": ["tag1", "tag2"]}), ...]
"""
return self.aggregator.flush()
def get_events(self):
"""
Return a list of the events saved by the check, if any
@return the list of events saved by this check
@rtype list of event dictionaries
"""
events = self.events
self.events = []
return events
def get_service_checks(self):
"""
Return a list of the service checks saved by the check, if any
and clears them out of the instance's service_checks list
@return the list of service checks saved by this check
@rtype list of service check dicts
"""
service_checks = self.service_checks
self.service_checks = []
return service_checks
def _roll_up_instance_metadata(self):
"""
Concatenate and flush instance metadata.
"""
self.svc_metadata.append(
dict((k, v) for (k, v) in self._instance_metadata))
self._instance_metadata = []
def get_service_metadata(self):
"""
Return a list of the metadata dictionaries saved by the check -if any-
and clears them out of the instance's service_checks list
@return the list of metadata saved by this check
@rtype list of metadata dicts
"""
if self._instance_metadata:
self._roll_up_instance_metadata()
service_metadata = self.svc_metadata
self.svc_metadata = []
return service_metadata
def has_warnings(self):
"""
Check whether the instance run created any warnings
"""
return len(self.warnings) > 0
def warning(self, warning_message):
""" Add a warning message that will be printed in the info page
:param warning_message: String. Warning message to be displayed
"""
warning_message = str(warning_message)
self.log.warning(warning_message)
self.warnings.append(warning_message)
def get_library_info(self):
if self.library_versions is not None:
return self.library_versions
try:
self.library_versions = self.get_library_versions()
except NotImplementedError:
pass
def get_library_versions(self):
""" Should return a string that shows which version
of the needed libraries are used """
raise NotImplementedError
def get_warnings(self):
"""
Return the list of warnings messages to be displayed in the info page
"""
warnings = self.warnings
self.warnings = []
return warnings
@staticmethod
def _get_statistic_name_from_method(method_name):
return method_name[4:] if method_name.startswith(
'get_') else method_name
@staticmethod
def _collect_internal_stats(methods=None):
current_process = psutil.Process(os.getpid())
methods = methods or DEFAULT_PSUTIL_METHODS
filtered_methods = [m for m in methods if hasattr(current_process, m)]
stats = {}
for method in filtered_methods:
# Go from `get_memory_info` -> `memory_info`
stat_name = AgentCheck._get_statistic_name_from_method(method)
try:
raw_stats = getattr(current_process, method)()
try:
stats[stat_name] = raw_stats._asdict()
except AttributeError:
if isinstance(raw_stats, numbers.Number):
stats[stat_name] = raw_stats
else:
log.warn(
"Could not serialize output of {0} to dict".format(
method))
except psutil.AccessDenied:
log.warn("Cannot call psutil method {} : Access Denied".format(
method))
return stats
def _set_internal_profiling_stats(self, before, after):
self._internal_profiling_stats = {'before': before, 'after': after}
def _get_internal_profiling_stats(self):
"""
If in developer mode, return a dictionary of statistics about the check run
"""
stats = self._internal_profiling_stats
self._internal_profiling_stats = None
return stats
def run(self):
""" Run all instances. """
# Store run statistics if needed
before, after = None, None
if self.in_developer_mode and self.name != AGENT_METRICS_CHECK_NAME:
try:
before = AgentCheck._collect_internal_stats()
except Exception: # It's fine if we can't collect stats for the run, just log and proceed
self.log.debug(
"Failed to collect Agent Stats before check {0}".format(
self.name))
instance_statuses = []
for i, instance in enumerate(self.instances):
try:
min_collection_interval = instance.get(
'min_collection_interval', self.min_collection_interval)
now = time.time()
if now - self.last_collection_time[i] < min_collection_interval:
self.log.debug(
"Not running instance #{0} of check {1} as it ran less than {2}s ago"
.format(i, self.name, min_collection_interval))
continue
self.last_collection_time[i] = now
check_start_time = None
if self.in_developer_mode:
check_start_time = timeit.default_timer()
self.check(copy.deepcopy(instance))
instance_check_stats = None
if check_start_time is not None:
instance_check_stats = {
'run_time': timeit.default_timer() - check_start_time
}
if self.has_warnings():
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_WARNING,
warnings=self.get_warnings(),
instance_check_stats=instance_check_stats)
else:
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_OK,
instance_check_stats=instance_check_stats)
except Exception as e:
self.log.exception("Check '%s' instance #%s failed" %
(self.name, i))
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_ERROR,
error=str(e),
tb=traceback.format_exc())
finally:
self._roll_up_instance_metadata()
instance_statuses.append(instance_status)
if self.in_developer_mode and self.name != AGENT_METRICS_CHECK_NAME:
try:
after = AgentCheck._collect_internal_stats()
self._set_internal_profiling_stats(before, after)
log.info("\n \t %s %s" %
(self.name,
pretty_statistics(self._internal_profiling_stats)))
except Exception: # It's fine if we can't collect stats for the run, just log and proceed
self.log.debug(
"Failed to collect Agent Stats after check {0}".format(
self.name))
return instance_statuses
def check(self, instance):
"""
Overriden by the check class. This will be called to run the check.
:param instance: A dict with the instance information. This will vary
depending on your config structure.
"""
raise NotImplementedError()
def stop(self):
"""
To be executed when the agent is being stopped to clean ressources
"""
pass
@classmethod
def from_yaml(cls,
path_to_yaml=None,
agentConfig=None,
yaml_text=None,
check_name=None):
"""
A method used for testing your check without running the agent.
"""
if path_to_yaml:
check_name = os.path.basename(path_to_yaml).split('.')[0]
try:
f = open(path_to_yaml)
except IOError:
raise Exception('Unable to open yaml config: %s' %
path_to_yaml)
yaml_text = f.read()
f.close()
config = yaml.load(yaml_text, Loader=yLoader)
try:
check = cls(check_name,
config.get('init_config') or {}, agentConfig or {},
config.get('instances'))
except TypeError:
# Compatibility for the check not supporting instances
check = cls(check_name,
config.get('init_config') or {}, agentConfig or {})
return check, config.get('instances', [])
def normalize(self, metric, prefix=None, fix_case=False):
"""
Turn a metric into a well-formed metric name
prefix.b.c
:param metric The metric name to normalize
:param prefix A prefix to to add to the normalized name, default None
:param fix_case A boolean, indicating whether to make sure that
the metric name returned is in underscore_case
"""
if isinstance(metric, unicode):
metric_name = unicodedata.normalize('NFKD', metric).encode(
'ascii', 'ignore')
else:
metric_name = metric
if fix_case:
name = self.convert_to_underscore_separated(metric_name)
if prefix is not None:
prefix = self.convert_to_underscore_separated(prefix)
else:
name = re.sub(r"[,\+\*\-/()\[\]{}\s]", "_", metric_name)
# Eliminate multiple _
name = re.sub(r"__+", "_", name)
# Don't start/end with _
name = re.sub(r"^_", "", name)
name = re.sub(r"_$", "", name)
# Drop ._ and _.
name = re.sub(r"\._", ".", name)
name = re.sub(r"_\.", ".", name)
if prefix is not None:
return prefix + "." + name
else:
return name
FIRST_CAP_RE = re.compile('(.)([A-Z][a-z]+)')
ALL_CAP_RE = re.compile('([a-z0-9])([A-Z])')
METRIC_REPLACEMENT = re.compile(r'([^a-zA-Z0-9_.]+)|(^[^a-zA-Z]+)')
DOT_UNDERSCORE_CLEANUP = re.compile(r'_*\._*')
def convert_to_underscore_separated(self, name):
"""
Convert from CamelCase to camel_case
And substitute illegal metric characters
"""
metric_name = self.FIRST_CAP_RE.sub(r'\1_\2', name)
metric_name = self.ALL_CAP_RE.sub(r'\1_\2', metric_name).lower()
metric_name = self.METRIC_REPLACEMENT.sub('_', metric_name)
return self.DOT_UNDERSCORE_CLEANUP.sub('.', metric_name).strip('_')
@staticmethod
def read_config(instance, key, message=None, cast=None):
val = instance.get(key)
if val is None:
message = message or 'Must provide `%s` value in instance config' % key
raise Exception(message)
if cast is None:
return val
else:
return cast(val)
def test_string_sets(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.set:string|s')
stats.submit_packets('my.set:sets|s')
stats.submit_packets('my.set:sets|s')
stats.submit_packets('my.set:test|s')
stats.submit_packets('my.set:test|s')
stats.submit_packets('my.set:test|s')
# Assert that it's treated normally.
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m['metric'], 'my.set')
nt.assert_equal(m['points'][0][1], 3)
# Assert there are no more sets
assert not stats.flush()
class AgentCheck(object):
OK, WARNING, CRITICAL, UNKNOWN = (0, 1, 2, 3)
SOURCE_TYPE_NAME = None
DEFAULT_MIN_COLLECTION_INTERVAL = 0
_enabled_checks = []
@classmethod
def is_check_enabled(cls, name):
return name in cls._enabled_checks
def __init__(self, name, init_config, agentConfig, instances=None):
from aggregator import MetricsAggregator
self._enabled_checks.append(name)
self._enabled_checks = list(set(self._enabled_checks))
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get('developer_mode') and psutil
self._internal_profiling_stats = None
self.hostname = agentConfig.get('checksd_hostname') or get_hostname(
agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.aggregator = MetricsAggregator(
self.hostname,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get('recent_point_threshold',
None),
histogram_aggregates=agentConfig.get('histogram_aggregates'),
histogram_percentiles=agentConfig.get('histogram_percentiles'))
self.events = []
self.service_checks = []
if instances:
jsoned_instances = json.dumps(instances)
encrypted_passwd_list = re.findall('>>>.*?<<<', jsoned_instances)
if encrypted_passwd_list:
for encrypted_passwd in encrypted_passwd_list:
decrypted_passwd = decrypted(encrypted_passwd)
jsoned_instances = jsoned_instances.replace(
encrypted_passwd, decrypted_passwd)
self.instances = convert_to_str(
json.loads(jsoned_instances, encoding='utf-8'))
else:
self.instances = instances
else:
self.instances = []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
self._instance_metadata = []
self.svc_metadata = []
self.historate_dict = {}
def instance_count(self):
return len(self.instances)
def gauge(self,
metric,
value,
tags=None,
hostname=None,
device_name=None,
timestamp=None):
self.aggregator.gauge(metric, value, tags, hostname, device_name,
timestamp)
def increment(self,
metric,
value=1,
tags=None,
hostname=None,
device_name=None):
self.aggregator.increment(metric, value, tags, hostname, device_name)
def decrement(self,
metric,
value=-1,
tags=None,
hostname=None,
device_name=None):
self.aggregator.decrement(metric, value, tags, hostname, device_name)
def count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
self.aggregator.submit_count(metric, value, tags, hostname,
device_name)
def monotonic_count(self,
metric,
value=0,
tags=None,
hostname=None,
device_name=None):
self.aggregator.count_from_counter(metric, value, tags, hostname,
device_name)
def rate(self, metric, value, tags=None, hostname=None, device_name=None):
self.aggregator.rate(metric, value, tags, hostname, device_name)
def histogram(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
self.aggregator.histogram(metric, value, tags, hostname, device_name)
@classmethod
def generate_historate_func(cls, excluding_tags):
def fct(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
cls.historate(self,
metric,
value,
excluding_tags,
tags=tags,
hostname=hostname,
device_name=device_name)
return fct
@classmethod
def generate_histogram_func(cls, excluding_tags):
def fct(self,
metric,
value,
tags=None,
hostname=None,
device_name=None):
tags = list(tags)
for tag in list(tags):
for exc_tag in excluding_tags:
if tag.startswith(exc_tag + ":"):
tags.remove(tag)
cls.histogram(self,
metric,
value,
tags=tags,
hostname=hostname,
device_name=device_name)
return fct
def historate(self,
metric,
value,
excluding_tags,
tags=None,
hostname=None,
device_name=None):
tags = list(tags)
context = [metric]
if tags is not None:
context.append("-".join(sorted(tags)))
if hostname is not None:
context.append("host:" + hostname)
if device_name is not None:
context.append("device:" + device_name)
now = time.time()
context = tuple(context)
if context in self.historate_dict:
if tags is not None:
for tag in list(tags):
for exc_tag in excluding_tags:
if tag.startswith("{0}:".format(exc_tag)):
tags.remove(tag)
prev_value, prev_ts = self.historate_dict[context]
rate = float(value - prev_value) / float(now - prev_ts)
self.aggregator.histogram(metric, rate, tags, hostname,
device_name)
self.historate_dict[context] = (value, now)
def set(self, metric, value, tags=None, hostname=None, device_name=None):
self.aggregator.set(metric, value, tags, hostname, device_name)
def event(self, event):
if event.get('api_key') is None:
event['api_key'] = self.agentConfig['api_key']
self.events.append(event)
def service_check(self,
check_name,
status,
tags=None,
timestamp=None,
hostname=None,
check_run_id=None,
message=None):
if hostname is None:
hostname = self.hostname
if message is not None:
message = unicode(message)
self.service_checks.append(
create_service_check(check_name, status, tags, timestamp, hostname,
check_run_id, message))
def service_metadata(self, meta_name, value):
self._instance_metadata.append((meta_name, unicode(value)))
def has_events(self):
return len(self.events) > 0
def get_metrics(self):
return self.aggregator.flush()
def get_events(self):
events = self.events
self.events = []
return events
def get_service_checks(self):
service_checks = self.service_checks
self.service_checks = []
return service_checks
def _roll_up_instance_metadata(self):
self.svc_metadata.append(
dict((k, v) for (k, v) in self._instance_metadata))
self._instance_metadata = []
def get_service_metadata(self):
if self._instance_metadata:
self._roll_up_instance_metadata()
service_metadata = self.svc_metadata
self.svc_metadata = []
return service_metadata
def has_warnings(self):
return len(self.warnings) > 0
def warning(self, warning_message):
warning_message = str(warning_message)
self.log.warning(warning_message)
self.warnings.append(warning_message)
def get_library_info(self):
if self.library_versions is not None:
return self.library_versions
try:
self.library_versions = self.get_library_versions()
except NotImplementedError:
pass
def get_library_versions(self):
raise NotImplementedError
def get_warnings(self):
warnings = self.warnings
self.warnings = []
return warnings
@staticmethod
def _get_statistic_name_from_method(method_name):
return method_name[4:] if method_name.startswith(
'get_') else method_name
@staticmethod
def _collect_internal_stats(methods=None):
current_process = psutil.Process(os.getpid())
methods = methods or DEFAULT_PSUTIL_METHODS
filtered_methods = [m for m in methods if hasattr(current_process, m)]
stats = {}
for method in filtered_methods:
stat_name = AgentCheck._get_statistic_name_from_method(method)
try:
raw_stats = getattr(current_process, method)()
try:
stats[stat_name] = raw_stats._asdict()
except AttributeError:
if isinstance(raw_stats, numbers.Number):
stats[stat_name] = raw_stats
else:
log.warn(
"Could not serialize output of {0} to dict".format(
method))
except psutil.AccessDenied:
log.warn("Cannot call psutil method {} : Access Denied".format(
method))
return stats
def _set_internal_profiling_stats(self, before, after):
self._internal_profiling_stats = {'before': before, 'after': after}
def _get_internal_profiling_stats(self):
stats = self._internal_profiling_stats
self._internal_profiling_stats = None
return stats
def run(self):
before, after = None, None
if self.in_developer_mode and self.name != AGENT_METRICS_CHECK_NAME:
try:
before = AgentCheck._collect_internal_stats()
except Exception:
self.log.debug(
"Failed to collect Agent Stats before check {0}".format(
self.name))
instance_statuses = []
for i, instance in enumerate(self.instances):
try:
min_collection_interval = instance.get(
'min_collection_interval',
self.init_config.get('min_collection_interval',
self.DEFAULT_MIN_COLLECTION_INTERVAL))
now = time.time()
if now - self.last_collection_time[i] < min_collection_interval:
self.log.debug(
"Not running instance #{0} of check {1} as it ran less than {2}s ago"
.format(i, self.name, min_collection_interval))
continue
self.last_collection_time[i] = now
check_start_time = None
if self.in_developer_mode:
check_start_time = timeit.default_timer()
self.check(copy.deepcopy(instance))
instance_check_stats = None
if check_start_time is not None:
instance_check_stats = {
'run_time': timeit.default_timer() - check_start_time
}
if self.has_warnings():
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_WARNING,
warnings=self.get_warnings(),
instance_check_stats=instance_check_stats)
else:
instance_status = check_status.InstanceStatus(
i,
check_status.STATUS_OK,
instance_check_stats=instance_check_stats)
except Exception, e:
self.log.exception("Check '%s' instance #%s failed" %
(self.name, i))
instance_status = check_status.InstanceStatus(
i, check_status.STATUS_ERROR, error=str(e), tb=str(e))
finally:
def __init__(self, name, init_config, agentConfig, instances=None):
"""
Initialize a new check.
:param name: The name of the check
:param init_config: The config for initializing the check
:param agentConfig: The global configuration for the agent
:param instances: A list of configuration objects for each instance.
"""
from aggregator import MetricsAggregator
self._enabled_checks.append(name)
self._enabled_checks = list(set(self._enabled_checks))
self.name = name
self.init_config = init_config or {}
self.agentConfig = agentConfig
self.in_developer_mode = agentConfig.get('developer_mode') and psutil
self._internal_profiling_stats = None
self.default_integration_http_timeout = float(
agentConfig.get('default_integration_http_timeout', 9))
self.hostname = agentConfig.get('checksd_hostname') or get_hostname(
agentConfig)
self.log = logging.getLogger('%s.%s' % (__name__, name))
self.min_collection_interval = self.init_config.get(
'min_collection_interval', self.DEFAULT_MIN_COLLECTION_INTERVAL)
self.aggregator = MetricsAggregator(
self.hostname,
expiry_seconds=self.min_collection_interval +
self.DEFAULT_EXPIRY_SECONDS,
formatter=agent_formatter,
recent_point_threshold=agentConfig.get('recent_point_threshold',
None),
histogram_aggregates=agentConfig.get('histogram_aggregates'),
histogram_percentiles=agentConfig.get('histogram_percentiles'))
self.events = []
self.service_checks = []
self.instances = instances or []
self.warnings = []
self.library_versions = None
self.last_collection_time = defaultdict(int)
self._instance_metadata = []
self.svc_metadata = []
self.historate_dict = {}
# Set proxy settings
self.proxy_settings = get_proxy(self.agentConfig)
self._use_proxy = False if init_config is None else init_config.get(
"use_agent_proxy", True)
self.proxies = {
"http": None,
"https": None,
}
if self.proxy_settings and self._use_proxy:
uri = "{host}:{port}".format(host=self.proxy_settings['host'],
port=self.proxy_settings['port'])
if self.proxy_settings['user'] and self.proxy_settings['password']:
uri = "{user}:{password}@{uri}".format(
user=self.proxy_settings['user'],
password=self.proxy_settings['password'],
uri=uri)
self.proxies['http'] = "http://{uri}".format(uri=uri)
self.proxies['https'] = "https://{uri}".format(uri=uri)
def test_rate_errors(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.rate:10|_dd-r')
# Sleep 1 second so the time interval > 0 (timestamp is converted to an int)
time.sleep(1)
stats.submit_packets('my.rate:9|_dd-r')
# Since the difference < 0 we shouldn't get a value
metrics = stats.flush()
nt.assert_equal(len(metrics), 0)
stats.submit_packets('my.rate:10|_dd-r')
# Trying to have the times be the same
stats.submit_packets('my.rate:40|_dd-r')
metrics = stats.flush()
nt.assert_equal(len(metrics), 0)
def setUp(self):
self.aggr = MetricsAggregator('test-aggr')
def test_event_title(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_e{0,4}:|text')
stats.submit_packets(u'_e{9,4}:2intitulé|text')
stats.submit_packets('_e{14,4}:3title content|text')
stats.submit_packets('_e{14,4}:4title|content|text')
stats.submit_packets(
'_e{13,4}:5title\\ntitle|text') # \n stays escaped
events = self.sort_events(stats.flush_events())
assert len(events) == 5
first, second, third, fourth, fifth = events
nt.assert_equal(first['msg_title'], '')
nt.assert_equal(second['msg_title'], u'2intitulé')
nt.assert_equal(third['msg_title'], '3title content')
nt.assert_equal(fourth['msg_title'], '4title|content')
nt.assert_equal(fifth['msg_title'], '5title\\ntitle')