public static IServiceCollection AddWavefrontDirectIngestion(this IServiceCollection services, IConfiguration configuration)
{
var waveFrontDirectIngestionConfiguration =
configuration.GetSection(WavefrontDirectIngestionOptions.WavefrontDirectIngestion)
.Get <WavefrontDirectIngestionOptions>();
var applicationTags =
new ApplicationTags.Builder(waveFrontDirectIngestionConfiguration.Application, waveFrontDirectIngestionConfiguration.Service)
.Cluster(waveFrontDirectIngestionConfiguration.Cluster)
.Shard(waveFrontDirectIngestionConfiguration.Shard)
.Build();
var wfDirectIngestionClientBuilder = new WavefrontDirectIngestionClient.Builder(waveFrontDirectIngestionConfiguration.Hostname, waveFrontDirectIngestionConfiguration.Token);
wfDirectIngestionClientBuilder.MaxQueueSize(waveFrontDirectIngestionConfiguration.MaxQueueSize);
wfDirectIngestionClientBuilder.BatchSize(waveFrontDirectIngestionConfiguration.BatchSize);
wfDirectIngestionClientBuilder.FlushIntervalSeconds(waveFrontDirectIngestionConfiguration.FlushIntervalSeconds);
var wavefrontSender = wfDirectIngestionClientBuilder.Build();
var wfAspNetCoreReporter = new WavefrontAspNetCoreReporter.Builder(applicationTags)
.WithSource(waveFrontDirectIngestionConfiguration.Source)
.ReportingIntervalSeconds(waveFrontDirectIngestionConfiguration.ReportingIntervalSeconds)
.Build(wavefrontSender);
var wavefrontSpanReporter = new WavefrontSpanReporter.Builder()
.Build(wavefrontSender);
ITracer tracer = new WavefrontTracer.Builder(wavefrontSpanReporter, applicationTags).Build();
services.AddWavefrontForMvc(wfAspNetCoreReporter, tracer);
return(services);
}
private static void startWavefrontReportingViaDirectInjestion()
{
IWavefrontSender wavefrontDirectIngestionClient =
new WavefrontDirectIngestionClient.Builder(wavefrontServer, token).Build();
IMetricsRoot metrics = new MetricsBuilder()
.Configuration.Configure(options =>
{
options.DefaultContextLabel = "service";
options.GlobalTags = new GlobalMetricTags(new Dictionary <string, string>
{
{ "dc", "us-west-2" },
{ "env", "staging" }
});
})
.Report.ToWavefront(options =>
{
options.WavefrontSender = wavefrontDirectIngestionClient;
options.Source = "app-1.company.com";
})
.Build();
CounterOptions evictions = new CounterOptions
{
Name = "cache-evictions"
};
metrics.Measure.Counter.Increment(evictions);
var scheduler = new AppMetricsTaskScheduler(TimeSpan.FromSeconds(5), async() =>
{
await Task.WhenAll(metrics.ReportRunner.RunAllAsync());
});
scheduler.Start();
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)] HttpRequest req,
ILogger log)
{
//Begin code instrumentation - reference https://github.com/wavefrontHQ/wavefront-opentracing-sdk-csharp
//The application, service, cluster, and shard variables are all metadata to be added to each span created.
string application = "VMworld2020Demo";
string service = "GlobalDataAggregator";
string cluster = "Azure";
string shard = "networknerd4";
//The URL and token are for direct ingestion of metrics, traces, and spans (no proxy in use here).
//The API token can be found inside the Tanzu Observability (Wavefront) web UI and is unique to your environment. Click the gear icon in the upper right, click your e-mail address, and then select API Access.
string wfURL = "https://vmware.wavefront.com";
string token = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx";
// Create ApplicationTags - for tracing purposes
ApplicationTags applicationTags = new ApplicationTags.Builder(application, service).Cluster(cluster).Shard(shard).Build();
//Configure a MetricsBuilder object - for custom metrics sent via the Metrics SDK
var MyMetricsBuilder = new MetricsBuilder();
//Initialize WavefrontDirectIngestionClient
WavefrontDirectIngestionClient.Builder wfDirectIngestionClientBuilder = new WavefrontDirectIngestionClient.Builder(wfURL, token);
// Create an IWavefrontSender instance for sending data via direct ingestion.
IWavefrontSender wavefrontSender = wfDirectIngestionClientBuilder.Build();
//Configure MeetricsBuilder to Report to Wavefront with proper sender object and source tag specified. In this case my source is the function name.
MyMetricsBuilder.Report.ToWavefront(
options =>
{
options.WavefrontSender = wavefrontSender;
options.Source = "TruckGlobalDataAggregator";
});
//Build IMetrics instance
var MyMetrics = MyMetricsBuilder.Build();
//These are arrays for key value pairs to add as metric tags. You can add some or many here as you instrument your code.
string[] keys = new string[3] {
"FunctionApp", "Cloud", "Region"
};
string[] values = new string[3] {
"networknerd4", "Azure", "Central-US"
};
// Configure and instantiate a DeltaCounter using DeltaCounterOptions.Builder. The metric name is azure.function.execution.deltacounter.
var myDeltaCounter = new DeltaCounterOptions.Builder("azure.function.execution.deltacounter").MeasurementUnit(Unit.Calls).Tags(new MetricTags(keys, values)).Build();
// Increment the counter by 1
MyMetrics.Measure.Counter.Increment(myDeltaCounter);
//Force reporting all custom metrics
await Task.WhenAll(MyMetrics.ReportRunner.RunAllAsync());
//Create a WavefrontSpanReporter for reporting trace data that originates on <sourceName>. The source is the function name in this case.
IReporter wfSpanReporter = new WavefrontSpanReporter.Builder()
.WithSource("TruckGlobalDataAggregator").Build(wavefrontSender);
//Create CompositeReporter and ConsoleReporter objects for more OpenTracing metrics
IReporter consoleReporter = new ConsoleReporter("TruckGlobalDataAggregator");
IReporter compositeReporter = new CompositeReporter(wfSpanReporter, consoleReporter);
//Create the WavefrontTracer.
WavefrontTracer MyTracer = new WavefrontTracer.Builder(wfSpanReporter, applicationTags).Build();
//The variable MyDictionary is needed to extract span context in case a call is made from another function / outside this function.
IDictionary <string, string> MyDictionary = new Dictionary <string, string>();
foreach (var entry in req.Headers)
{
MyDictionary.TryAdd(entry.Key, entry.Value);
}
//Attempt to pull span fontext from HTTP headers passed into this function to continue a span across environments. The proper context will be loaded into the variable
//ctx if so. The second line of code loads all metadata from the span context.
ITextMap carrier = new TextMapExtractAdapter(MyDictionary);
OpenTracing.ISpanContext ctx = MyTracer.Extract(BuiltinFormats.HttpHeaders, carrier);
OpenTracing.IScope receivingScope = MyTracer.BuildSpan("TruckGlobalDataAggregator.Execute").AsChildOf(ctx).StartActive(true);
//Start building a new span called TruckGlobalDataAggregator.Execute if there was no context passed into headers.
if (MyTracer.ActiveSpan != null)
{
MyTracer.BuildSpan("TruckGlobalDataAggregator.Execute").StartActive();
}
log.LogInformation("C# HTTP trigger function processed a request.");
string name = req.Query["name"];
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
dynamic data = JsonConvert.DeserializeObject(requestBody);
name = name ?? data?.name;
//Add function execution delays based on input - for personal testing only.
if (string.Equals(name, "0.5"))
{
await Task.Delay(500);
}
if (string.Equals(name, "1"))
{
await Task.Delay(1000);
}
if (string.Equals(name, "1.5"))
{
await Task.Delay(1500);
}
if (string.Equals(name, "2"))
{
await Task.Delay(2000);
}
string responseMessage = string.IsNullOrEmpty(name)
? "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response."
: $"Hello, {name}. This HTTP triggered function executed successfully.";
//Finish the span
MyTracer.ActiveSpan.Finish();
//Close the tracer before application exit
MyTracer.Close();
return(new OkObjectResult(responseMessage));
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)] HttpRequest req,
ILogger log)
{
//Begin code instrumentation - reference https://github.com/wavefrontHQ/wavefront-appmetrics-sdk-csharp
//The URL and token are for direct ingestion of metrics (no proxy in use here).
//The API token can be found inside the Tanzu Observability (Wavefront) web UI and is unique to your environment. Click the gear icon in the upper right, click your e-mail address, and then select API Access.
string wfURL = "https://vmware.wavefront.com";
string token = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx";
//Configure a MetricsBuilder object
var MyMetricsBuilder = new MetricsBuilder();
//Initialize WavefrontDirectIngestionClient
WavefrontDirectIngestionClient.Builder wfDirectIngestionClientBuilder = new WavefrontDirectIngestionClient.Builder(wfURL, token);
// Create an IWavefrontSender instance for sending data via direct ingestion.
IWavefrontSender wavefrontSender = wfDirectIngestionClientBuilder.Build();
//Configure MeetricsBuilder to Report to Wavefront with proper sender object and source tag specified. In this case my source is the function name.
MyMetricsBuilder.Report.ToWavefront(
options =>
{
options.WavefrontSender = wavefrontSender;
options.Source = "TruckWorkflowAnalytics";
});
//Build IMetrics instance
var MyMetrics = MyMetricsBuilder.Build();
//These are arrays for key value pairs to add as metric tags. You can add some or many here as you instrument your code.
string[] keys = new string[3] {
"FunctionApp", "Cloud", "Region"
};
string[] values = new string[3] {
"networknerd5", "Azure", "Central-US"
};
// Configure and instantiate a DeltaCounter using DeltaCounterOptions.Builder. The metric name is azure.function.execution.deltacounter.
var myDeltaCounter = new DeltaCounterOptions.Builder("azure.function.execution.deltacounter").MeasurementUnit(Unit.Calls).Tags(new MetricTags(keys, values)).Build();
// Increment the delta counter by 1
MyMetrics.Measure.Counter.Increment(myDeltaCounter);
//Force reporting all metrics
//end of code instrumentation for metrics
await Task.WhenAll(MyMetrics.ReportRunner.RunAllAsync());
//Begin default template code from the HTTP trigger function template as part of the Azure Functions Extension for C#.
log.LogInformation("C# HTTP trigger function processed a request.");
string name = req.Query["name"];
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
dynamic data = JsonConvert.DeserializeObject(requestBody);
name = name ?? data?.name;
//Add function execution delays based on input (for my own testing only).
if (string.Equals(name, "0.5"))
{
await Task.Delay(500);
}
if (string.Equals(name, "1"))
{
await Task.Delay(1000);
}
if (string.Equals(name, "1.5"))
{
await Task.Delay(1500);
}
if (string.Equals(name, "2"))
{
await Task.Delay(2000);
}
string responseMessage = string.IsNullOrEmpty(name)
? "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response."
: $"Hello, {name}. This HTTP triggered function executed successfully.";
return(new OkObjectResult(responseMessage));
}
