async def test_distributed_tracing_sub_span(app_tracer, aiohttp_client):
app, tracer = app_tracer
client = await aiohttp_client(app)
tracer.priority_sampler = RateSampler(1.0)
# activate distributed tracing
tracing_headers = {
"x-datadog-trace-id": "100",
"x-datadog-parent-id": "42",
"x-datadog-sampling-priority": "0",
}
request = await client.request("GET", "/sub_span", headers=tracing_headers)
assert 200 == request.status
text = await request.text()
assert "OK" == text
# the trace is created
traces = tracer.pop_traces()
assert 1 == len(traces)
assert 2 == len(traces[0])
span, sub_span = traces[0][0], traces[0][1]
# with the right trace_id and parent_id
assert 100 == span.trace_id
assert 42 == span.parent_id
assert 0 == span.get_metric(SAMPLING_PRIORITY_KEY)
# check parenting is OK with custom sub-span created within server code
assert 100 == sub_span.trace_id
assert span.span_id == sub_span.parent_id
assert sub_span.get_metric(SAMPLING_PRIORITY_KEY) is None
def test_distributed_tracing_sub_span(self):
self.tracer.priority_sampler = RateSampler(1.0)
# activate distributed tracing
tracing_headers = {
'x-datadog-trace-id': '100',
'x-datadog-parent-id': '42',
'x-datadog-sampling-priority': '0',
}
request = yield from self.client.request('GET',
'/sub_span',
headers=tracing_headers)
assert 200 == request.status
text = yield from request.text()
assert 'OK' == text
# the trace is created
traces = self.tracer.writer.pop_traces()
assert 1 == len(traces)
assert 2 == len(traces[0])
span, sub_span = traces[0][0], traces[0][1]
# with the right trace_id and parent_id
assert 100 == span.trace_id
assert 42 == span.parent_id
assert 0 == span.get_metric(SAMPLING_PRIORITY_KEY)
# check parenting is OK with custom sub-span created within server code
assert 100 == sub_span.trace_id
assert span.span_id == sub_span.parent_id
assert sub_span.get_metric(SAMPLING_PRIORITY_KEY) is None
async def test_distributed_tracing_with_sampling_false(app_tracer,
aiohttp_client):
app, tracer = app_tracer
client = await aiohttp_client(app)
tracer.priority_sampler = RateSampler(0.9)
tracing_headers = {
"x-datadog-trace-id": "100",
"x-datadog-parent-id": "42",
"x-datadog-sampling-priority": "0",
}
request = await client.request("GET", "/", headers=tracing_headers)
assert 200 == request.status
text = await request.text()
assert "What's tracing?" == text
# the trace is created
traces = tracer.pop_traces()
assert 1 == len(traces)
assert 1 == len(traces[0])
span = traces[0][0]
# with the right trace_id and parent_id
assert 100 == span.trace_id
assert 42 == span.parent_id
assert 0 == span.get_metric(SAMPLING_PRIORITY_KEY)
def test_distributed_tracing_sub_span(self):
self.tracer.priority_sampler = RateSampler(1.0)
# activate distributed tracing
tracing_headers = {
'x-datadog-trace-id': '100',
'x-datadog-parent-id': '42',
'x-datadog-sampling-priority': '0',
}
request = yield from self.client.request('GET', '/sub_span', headers=tracing_headers)
eq_(200, request.status)
text = yield from request.text()
eq_("OK", text)
# the trace is created
traces = self.tracer.writer.pop_traces()
eq_(1, len(traces))
eq_(2, len(traces[0]))
span, sub_span = traces[0][0], traces[0][1]
# with the right trace_id and parent_id
eq_(100, span.trace_id)
eq_(42, span.parent_id)
eq_(0, span.get_metric(SAMPLING_PRIORITY_KEY))
# check parenting is OK with custom sub-span created within server code
eq_(100, sub_span.trace_id)
eq_(span.span_id, sub_span.parent_id)
eq_(None, sub_span.get_metric(SAMPLING_PRIORITY_KEY))
def test_distributed_tracing_with_sampling_false(self):
self.tracer.priority_sampler = RateSampler(0.9)
# activate distributed tracing
self.app['datadog_trace']['distributed_tracing_enabled'] = True
tracing_headers = {
'x-datadog-trace-id': '100',
'x-datadog-parent-id': '42',
'x-datadog-sampling-priority': '0',
}
request = yield from self.client.request('GET',
'/',
headers=tracing_headers)
eq_(200, request.status)
text = yield from request.text()
eq_("What's tracing?", text)
# the trace is created
traces = self.tracer.writer.pop_traces()
eq_(1, len(traces))
eq_(1, len(traces[0]))
span = traces[0][0]
# with the right trace_id and parent_id
eq_(100, span.trace_id)
eq_(42, span.parent_id)
eq_(0, span.get_metric(SAMPLING_PRIORITY_KEY))
def test_sample_rate_deviation(self):
for sample_rate in [0.1, 0.25, 0.5, 1]:
tracer = get_dummy_tracer()
writer = tracer.writer
tracer.sampler = RateSampler(sample_rate)
random.seed(1234)
iterations = int(1e4 / sample_rate)
for i in range(iterations):
span = tracer.trace(i)
span.finish()
samples = writer.pop()
# We must have at least 1 sample, check that it has its sample rate properly assigned
assert samples[0].get_metric(SAMPLE_RATE_METRIC_KEY) == sample_rate
# Less than 2% deviation when "enough" iterations (arbitrary, just check if it converges)
deviation = abs(len(samples) -
(iterations * sample_rate)) / (iterations *
sample_rate)
assert deviation < 0.02, "Deviation too high %f with sample_rate %f" % (
deviation, sample_rate)
def test_sampling(self, tracer):
with tracer.trace("trace1"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1.0)
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace2"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=0.000001)
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace3"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1,
rules=[SamplingRule(1.0)])
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace4"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1,
rules=[SamplingRule(0)])
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace5"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1)
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace6"):
with tracer.trace("child") as span:
span.set_tag(MANUAL_DROP_KEY)
sampler = DatadogSampler(default_sample_rate=1)
tracer.configure(sampler=sampler, writer=tracer.writer)
with tracer.trace("trace7"):
with tracer.trace("child") as span:
span.set_tag(MANUAL_KEEP_KEY)
sampler = RateSampler(0.0000000001)
tracer.configure(sampler=sampler, writer=tracer.writer)
# This trace should not appear in the snapshot
with tracer.trace("trace8"):
with tracer.trace("child"):
pass
tracer.shutdown()
def test_set_sample_rate(self):
sampler = RateSampler()
assert sampler.sample_rate == 1.0
for rate in [0.001, 0.01, 0.1, 0.25, 0.5, 0.75, 0.99999999, 1.0, 1]:
sampler.set_sample_rate(rate)
assert sampler.sample_rate == float(rate)
sampler.set_sample_rate(str(rate))
assert sampler.sample_rate == float(rate)
def test_deterministic_behavior(self):
""" Test that for a given trace ID, the result is always the same """
tracer = DummyTracer()
tracer.sampler = RateSampler(0.5)
for i in range(10):
span = tracer.trace(i)
span.finish()
samples = tracer.pop()
assert len(samples) <= 1, "there should be 0 or 1 spans"
sampled = 1 == len(samples)
for j in range(10):
other_span = Span(tracer, i, trace_id=span.trace_id)
assert sampled == tracer.sampler.sample(
other_span
), "sampling should give the same result for a given trace_id"
def test_deterministic_behavior(self):
""" Test that for a given trace ID, the result is always the same """
tracer = get_dummy_tracer()
writer = tracer.writer
tracer.sampler = RateSampler(0.5)
for i in range(10):
span = tracer.trace(i)
span.finish()
samples = writer.pop()
assert len(samples) <= 1, 'there should be 0 or 1 spans'
sampled = (1 == len(samples))
for j in range(10):
other_span = Span(tracer, i, trace_id=span.trace_id)
assert (
sampled == tracer.sampler.sample(other_span)
), 'sampling should give the same result for a given trace_id'
def test_distributed_tracing_with_sampling_false(self):
self.tracer.priority_sampler = RateSampler(0.9)
tracing_headers = {
'x-datadog-trace-id': '100',
'x-datadog-parent-id': '42',
'x-datadog-sampling-priority': '0',
}
request = yield from self.client.request('GET', '/', headers=tracing_headers)
assert 200 == request.status
text = yield from request.text()
assert "What's tracing?" == text
# the trace is created
traces = self.tracer.writer.pop_traces()
assert 1 == len(traces)
assert 1 == len(traces[0])
span = traces[0][0]
# with the right trace_id and parent_id
assert 100 == span.trace_id
assert 42 == span.parent_id
assert 0 == span.get_metric(SAMPLING_PRIORITY_KEY)
def test_distributed_tracing_with_sampling_true(self):
self.tracer.priority_sampler = RateSampler(0.1)
tracing_headers = {
"x-datadog-trace-id": "100",
"x-datadog-parent-id": "42",
"x-datadog-sampling-priority": "1",
}
request = yield from self.client.request("GET",
"/",
headers=tracing_headers)
assert 200 == request.status
text = yield from request.text()
assert "What's tracing?" == text
# the trace is created
traces = self.pop_traces()
assert 1 == len(traces)
assert 1 == len(traces[0])
span = traces[0][0]
# with the right trace_id and parent_id
assert 100 == span.trace_id
assert 42 == span.parent_id
assert 1 == span.get_metric(SAMPLING_PRIORITY_KEY)
def test_set_sample_rate_str(self):
sampler = RateSampler()
sampler.set_sample_rate("0.5")
assert sampler.sample_rate == 0.5
def test_sample_rate_0_does_not_reset_to_1(self):
# Regression test for case where a sample rate of 0 caused the sample rate to be reset to 1
tracer = DummyTracer()
tracer.sampler = RateSampler(sample_rate=0)
assert tracer.sampler.sample_rate == 0
def test_negative_sample_rate_raises_error(self):
tracer = DummyTracer()
with pytest.raises(ValueError,
match="sample_rate of -0.5 is negative"):
tracer.sampler = RateSampler(sample_rate=-0.5)
def test_sampling(writer, tracer):
if writer == "sync":
writer = AgentWriter(
tracer.writer.agent_url,
priority_sampler=tracer.priority_sampler,
sync_mode=True,
)
# Need to copy the headers which contain the test token to associate
# traces with this test case.
writer._headers = tracer.writer._headers
else:
writer = tracer.writer
tracer.configure(writer=writer)
with tracer.trace("trace1"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1.0)
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace2"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=0.000001)
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace3"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1, rules=[SamplingRule(1.0)])
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace4"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1, rules=[SamplingRule(0)])
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace5"):
with tracer.trace("child"):
pass
sampler = DatadogSampler(default_sample_rate=1)
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace6"):
with tracer.trace("child") as span:
span.set_tag(MANUAL_DROP_KEY)
sampler = DatadogSampler(default_sample_rate=1)
tracer.configure(sampler=sampler, writer=writer)
with tracer.trace("trace7"):
with tracer.trace("child") as span:
span.set_tag(MANUAL_KEEP_KEY)
sampler = RateSampler(0.0000000001)
tracer.configure(sampler=sampler, writer=writer)
# This trace should not appear in the snapshot
with tracer.trace("trace8"):
with tracer.trace("child"):
pass
tracer.shutdown()
