// This method gets called by the runtime. Use this method to configure the HTTP request pipeline.
public void Configure(IApplicationBuilder app, IWebHostEnvironment env)
{
if (env.IsDevelopment())
{
app.UseDeveloperExceptionPage();
}
app.UseHttpsRedirection();
app.UseRouting();
app.UseAuthorization();
var appInsightsConfig = app.ApplicationServices.GetService <TelemetryConfiguration>();
TelemetryProcessorChainBuilder builder = appInsightsConfig.TelemetryProcessorChainBuilder;
// some custom telemetry processor for Application Insights that filters out synthetic traffic (e.g traffic that comes from Azure to keep the server awake).
builder.UseAdaptiveSampling(excludedTypes: "Exception");
builder.UseAdaptiveSampling(maxTelemetryItemsPerSecond: 10000);
builder.Build();
app.UseEndpoints(endpoints =>
{
endpoints.MapControllers();
});
}
public void UseAdaptiveSamplingWithSettingsParameterAndExcludedTypesThrowsArgumentNullExceptionSettingsIsNull()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
AssertEx.Throws <ArgumentNullException>(() => channelBuilder.UseAdaptiveSampling(null, null, "request"));
}
public void UseAdaptiveSamplingWithSettingsParameterThrowsArgumentNullExceptionSettingsIsNull()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
AssertEx.Throws <ArgumentNullException>(() => channelBuilder.UseAdaptiveSampling(default(SamplingPercentageEstimatorSettings), null));
}
public void UseAdaptiveSamplingAddsAdaptiveSamplingProcessorToTheChainWithCorrectExcludedTypes()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
channelBuilder.UseAdaptiveSampling("request");
channelBuilder.Build();
Assert.AreEqual("request", ((AdaptiveSamplingTelemetryProcessor)tc.TelemetryProcessorChain.FirstTelemetryProcessor).ExcludedTypes);
}
public void UseAdaptiveSamplingAddsAdaptiveSamplingProcessorToTheChain()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
channelBuilder.UseAdaptiveSampling();
channelBuilder.Build();
AssertEx.IsType <AdaptiveSamplingTelemetryProcessor>(tc.TelemetryProcessorChain.FirstTelemetryProcessor);
}
public void UseAdaptiveSamplingAddsAdaptiveSamplingProcessorToTheChainWithCorrectMaxTelemetryItemsPerSecond()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
channelBuilder.UseAdaptiveSampling(5);
channelBuilder.Build();
Assert.AreEqual(5, ((AdaptiveSamplingTelemetryProcessor)tc.TelemetryProcessorChain.FirstTelemetryProcessor).MaxTelemetryItemsPerSecond);
}
public void AllTelemetryCapturedWhenProductionRateIsLow()
{
var sentTelemetry = new List <ITelemetry>();
int itemsProduced = 0;
using (var tc = new TelemetryConfiguration()
{
TelemetryChannel = new StubTelemetryChannel()
})
{
var chainBuilder = new TelemetryProcessorChainBuilder(tc);
// set up adaptive sampling that evaluates and changes sampling % frequently
chainBuilder
.UseAdaptiveSampling(
new Channel.Implementation.SamplingPercentageEstimatorSettings()
{
EvaluationInterval = TimeSpan.FromSeconds(1),
SamplingPercentageDecreaseTimeout = TimeSpan.FromSeconds(2),
SamplingPercentageIncreaseTimeout = TimeSpan.FromSeconds(2),
},
this.TraceSamplingPercentageEvaluation)
.Use((next) => new StubTelemetryProcessor(next)
{
OnProcess = (t) => sentTelemetry.Add(t)
});
chainBuilder.Build();
const int productionFrequencyMs = 1000;
var productionTimer = new Timer(
(state) =>
{
tc.TelemetryProcessorChain.Process(new RequestTelemetry());
itemsProduced++;
},
null,
productionFrequencyMs,
productionFrequencyMs);
Thread.Sleep(25000);
// dispose timer and wait for callbacks to complete
DisposeTimer(productionTimer);
}
Assert.AreEqual(itemsProduced, sentTelemetry.Count);
}
public void AdaptiveSamplingSetsExcludedTypesOnInternalSamplingProcessor()
{
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
channelBuilder.UseAdaptiveSampling(5, "request;");
channelBuilder.Build();
var fieldInfo = typeof(AdaptiveSamplingTelemetryProcessor).GetField("samplingProcessor", BindingFlags.GetField | BindingFlags.Instance | BindingFlags.NonPublic);
SamplingTelemetryProcessor internalProcessor = (SamplingTelemetryProcessor)fieldInfo.GetValue(tc.TelemetryProcessorChain.FirstTelemetryProcessor);
Assert.AreEqual("request;", internalProcessor.ExcludedTypes);
}
public void UseAdaptiveSamplingAddsAdaptiveSamplingProcessorToTheChainWithCorrectSettings()
{
SamplingPercentageEstimatorSettings settings = new SamplingPercentageEstimatorSettings
{
MaxSamplingPercentage = 13
};
AdaptiveSamplingPercentageEvaluatedCallback callback = (second, percentage, samplingPercentage, changed, estimatorSettings) => { };
var tc = new TelemetryConfiguration {
TelemetryChannel = new StubTelemetryChannel()
};
var channelBuilder = new TelemetryProcessorChainBuilder(tc);
channelBuilder.UseAdaptiveSampling(settings, callback);
channelBuilder.Build();
Assert.AreEqual(13, ((AdaptiveSamplingTelemetryProcessor)tc.TelemetryProcessorChain.FirstTelemetryProcessor).MaxSamplingPercentage);
}
public void SamplingPercentageAdjustsAccordingToConstantHighProductionRate()
{
var sentTelemetry = new List <ITelemetry>();
int itemsProduced = 0;
using (var tc = new TelemetryConfiguration()
{
TelemetryChannel = new StubTelemetryChannel()
})
{
var chainBuilder = new TelemetryProcessorChainBuilder(tc);
// set up adaptive sampling that evaluates and changes sampling % frequently
chainBuilder
.UseAdaptiveSampling(
new Channel.Implementation.SamplingPercentageEstimatorSettings()
{
EvaluationInterval = TimeSpan.FromSeconds(1),
SamplingPercentageDecreaseTimeout = TimeSpan.FromSeconds(2),
SamplingPercentageIncreaseTimeout = TimeSpan.FromSeconds(2),
},
this.TraceSamplingPercentageEvaluation)
.Use((next) => new StubTelemetryProcessor(next)
{
OnProcess = (t) => sentTelemetry.Add(t)
});
chainBuilder.Build();
const int productionFrequencyMs = 100;
var productionTimer = new Timer(
(state) =>
{
for (int i = 0; i < 2; i++)
{
tc.TelemetryProcessorChain.Process(new RequestTelemetry());
itemsProduced++;
}
},
null,
0,
productionFrequencyMs);
Thread.Sleep(25000);
// dispose timer and wait for callbacks to complete
DisposeTimer(productionTimer);
}
// number of items produced should be close to target of 5/second
int targetItemCount = 25 * 5;
// tolrance +-
int tolerance = targetItemCount / 2;
Trace.WriteLine(string.Format("'Ideal' telemetry item count: {0}", targetItemCount));
Trace.WriteLine(string.Format(
"Expected range: from {0} to {1}",
targetItemCount - tolerance,
targetItemCount + tolerance));
Trace.WriteLine(string.Format(
"Actual telemetry item count: {0} ({1:##.##}% of ideal)",
sentTelemetry.Count,
100.0 * sentTelemetry.Count / targetItemCount));
Assert.IsTrue(sentTelemetry.Count > targetItemCount - tolerance);
Assert.IsTrue(sentTelemetry.Count < targetItemCount + tolerance);
}
public void SamplingPercentageAdjustsForSpikyProductionRate()
{
var sentTelemetry = new List <ITelemetry>();
int itemsProduced = 0;
using (var tc = new TelemetryConfiguration()
{
TelemetryChannel = new StubTelemetryChannel()
})
{
var chainBuilder = new TelemetryProcessorChainBuilder(tc);
// set up adaptive sampling that evaluates and changes sampling % frequently
chainBuilder
.UseAdaptiveSampling(
new SamplingPercentageEstimatorSettings()
{
InitialSamplingPercentage = 5.0,
EvaluationInterval = TimeSpan.FromSeconds(1),
SamplingPercentageDecreaseTimeout = TimeSpan.FromSeconds(2),
SamplingPercentageIncreaseTimeout = TimeSpan.FromSeconds(10),
},
this.TraceSamplingPercentageEvaluation)
.Use((next) => new StubTelemetryProcessor(next)
{
OnProcess = (t) => sentTelemetry.Add(t)
});
chainBuilder.Build();
const int regularProductionFrequencyMs = 100;
const int spikeProductionFrequencyMs = 3000;
using (var regularProductionTimer = new Timer(
(state) =>
{
for (int i = 0; i < 2; i++)
{
tc.TelemetryProcessorChain.Process(new RequestTelemetry());
Interlocked.Increment(ref itemsProduced);
}
},
null,
0,
regularProductionFrequencyMs))
using (var spikeProductionTimer = new Timer(
(state) =>
{
for (int i = 0; i < 200; i++)
{
tc.TelemetryProcessorChain.Process(new RequestTelemetry());
Interlocked.Increment(ref itemsProduced);
}
},
null,
0,
spikeProductionFrequencyMs))
{
Thread.Sleep(30000);
}
}
// number of items produced should be close to target of 5/second
int targetItemCount = 30 * 5;
int tolerance = targetItemCount / 2;
Trace.WriteLine(string.Format("'Ideal' telemetry item count: {0}", targetItemCount));
Trace.WriteLine(string.Format(
"Expected range: from {0} to {1}",
targetItemCount - tolerance,
targetItemCount + tolerance));
Trace.WriteLine(string.Format(
"Actual telemetry item count: {0} ({1:##.##}% of ideal)",
sentTelemetry.Count,
100.0 * sentTelemetry.Count / targetItemCount));
Assert.IsTrue(sentTelemetry.Count > targetItemCount - tolerance);
Assert.IsTrue(sentTelemetry.Count < targetItemCount + tolerance);
}
public (int proactivelySampledInAndSentCount, double sentCount) ProactiveSamplingTest(
int proactivelySampledInRatePerSec,
int beforeSamplingRatePerSec,
double targetAfterSamplingRatePerSec,
double precision,
int testDurationInSec)
{
// we'll ignore telemetry reported during first few percentage evaluations
int warmUpInSec = 12;
// we'll produce proactively sampled in items and also 'normal' items with the same rate
// but allow only proactively sampled in + a bit more
// number of items produced should be close to target
int targetItemCount = (int)(testDurationInSec * targetAfterSamplingRatePerSec);
var sentTelemetry = new List <ITelemetry>();
using (var tc = new TelemetryConfiguration()
{
TelemetryChannel = new StubTelemetryChannel()
})
{
var chainBuilder = new TelemetryProcessorChainBuilder(tc);
// set up adaptive sampling that evaluates and changes sampling % frequently
chainBuilder
.UseAdaptiveSampling(
new Channel.Implementation.SamplingPercentageEstimatorSettings()
{
// help algo get to stabilize earlier
InitialSamplingPercentage = targetAfterSamplingRatePerSec / (double)beforeSamplingRatePerSec * 100,
MaxTelemetryItemsPerSecond = targetAfterSamplingRatePerSec,
EvaluationInterval = TimeSpan.FromSeconds(2),
SamplingPercentageDecreaseTimeout = TimeSpan.FromSeconds(4),
SamplingPercentageIncreaseTimeout = TimeSpan.FromSeconds(4),
},
this.TraceSamplingPercentageEvaluation)
.Use((next) => new StubTelemetryProcessor(next)
{
OnProcess = (t) => sentTelemetry.Add(t)
});
chainBuilder.Build();
var sw = Stopwatch.StartNew();
var productionTimer = new Timer(
(state) =>
{
var requests = new RequestTelemetry[beforeSamplingRatePerSec];
for (int i = 0; i < beforeSamplingRatePerSec; i++)
{
requests[i] = new RequestTelemetry()
{
ProactiveSamplingDecision = i < proactivelySampledInRatePerSec ? SamplingDecision.SampledIn : SamplingDecision.None
};
requests[i].Context.Operation.Id = ActivityTraceId.CreateRandom().ToHexString();
}
foreach (var request in requests)
{
if (((Stopwatch)state).Elapsed.TotalSeconds < warmUpInSec)
{
// let's ignore telemetry from first few rate evaluations - it does not make sense
request.Properties["ignore"] = "true";
}
tc.TelemetryProcessorChain.Process(request);
}
},
sw,
0,
1000);
Thread.Sleep(TimeSpan.FromSeconds(testDurationInSec + warmUpInSec));
// dispose timer and wait for callbacks to complete
DisposeTimer(productionTimer);
}
var notIgnoredSent = sentTelemetry.Where(i => i is ISupportProperties propItem && !propItem.Properties.ContainsKey("ignore")).ToArray();
var proactivelySampledInAndSentCount = notIgnoredSent.Count(i =>
i is ISupportAdvancedSampling advSamplingItem &&
advSamplingItem.ProactiveSamplingDecision == SamplingDecision.SampledIn);
// check that normal sampling requirements still apply (we generated as much items as expected)
Trace.WriteLine($"'Ideal' telemetry item count: {targetItemCount}");
Trace.WriteLine($"Expected range: from {targetItemCount - precision * targetItemCount} to {targetItemCount + precision * targetItemCount}");
Trace.WriteLine(
$"Actual telemetry item count: {notIgnoredSent.Length} ({100.0 * notIgnoredSent.Length / targetItemCount:##.##}% of ideal)");
Trace.WriteLine(
$"Actual proactive sampled in and sent: {proactivelySampledInAndSentCount}");
Assert.IsTrue(notIgnoredSent.Length / (double)targetItemCount > 1 - precision);
Assert.IsTrue(notIgnoredSent.Length / (double)targetItemCount < 1 + precision);
return(proactivelySampledInAndSentCount, notIgnoredSent.Length);
}