Filter and preprocess telemetry in the Application Insights SDK

You can write code to filter, modify, or enrich your telemetry before it's sent from the SDK. The processing includes data that's sent from the standard telemetry modules, such as HTTP request collection and dependency collection.

• Filtering can modify or discard telemetry before it's sent from the SDK by implementing ITelemetryProcessor. For example, you could reduce the volume of telemetry by excluding requests from robots. Unlike sampling, You have full control over what is sent or discarded, but it affects any metrics based on aggregated logs. Depending on how you discard items, you might also lose the ability to navigate between related items.

• Add or Modify properties to any telemetry sent from your app by implementing an ITelemetryInitializer. For example, you could add calculated values or version numbers by which to filter the data in the portal.

• Sampling reduces the volume of telemetry without affecting your statistics. It keeps together related data points so that you can navigate between them when you diagnose a problem. In the portal, the total counts are multiplied to compensate for the sampling.

Note

The SDK API is used to send custom events and metrics.

Prerequisites

Install the appropriate SDK for your application: ASP.NET, ASP.NET Core, Non-HTTP/Worker for .NET/.NET Core, or JavaScript.

Filtering

This technique gives you direct control over what's included or excluded from the telemetry stream. Filtering can be used to drop telemetry items from being sent to Application Insights. You can use filtering with sampling, or separately.

To filter telemetry, you write a telemetry processor and register it with TelemetryConfiguration. All telemetry goes through your processor. You can choose to drop it from the stream or give it to the next processor in the chain. Telemetry from the standard modules, such as the HTTP request collector and the dependency collector, and telemetry you tracked yourself is included. For example, you can filter out telemetry about requests from robots or successful dependency calls.

Warning

Filtering the telemetry sent from the SDK by using processors can skew the statistics that you see in the portal and make it difficult to follow related items.

Instead, consider using sampling.

.NET applications

1. Implement ITelemetryProcessor.

   Telemetry processors construct a chain of processing. When you instantiate a telemetry processor, you're given a reference to the next processor in the chain. When a telemetry data point is passed to the process method, it does its work and then calls (or doesn't call) the next telemetry processor in the chain.

   using Microsoft.ApplicationInsights.Channel;
   using Microsoft.ApplicationInsights.Extensibility;
   using Microsoft.ApplicationInsights.DataContracts;
   
   public class SuccessfulDependencyFilter : ITelemetryProcessor
   {
       private ITelemetryProcessor Next { get; set; }
   
       // next will point to the next TelemetryProcessor in the chain.
       public SuccessfulDependencyFilter(ITelemetryProcessor next)
       {
           this.Next = next;
       }
   
       public void Process(ITelemetry item)
       {
           // To filter out an item, return without calling the next processor.
           if (!OKtoSend(item)) { return; }
   
           this.Next.Process(item);
       }
   
       // Example: replace with your own criteria.
       private bool OKtoSend (ITelemetry item)
       {
           var dependency = item as DependencyTelemetry;
           if (dependency == null) return true;
   
           return dependency.Success != true;
       }
   }
   

2. Add your processor.

   ASP.NET

   Insert this snippet in ApplicationInsights.config:

   <TelemetryProcessors>
     <Add Type="WebApplication9.SuccessfulDependencyFilter, WebApplication9">
       <!-- Set public property -->
       <MyParamFromConfigFile>2-beta</MyParamFromConfigFile>
     </Add>
   </TelemetryProcessors>
   

   You can pass string values from the .config file by providing public named properties in your class.

   Warning

   Take care to match the type name and any property names in the .config file to the class and property names in the code. If the .config file references a nonexistent type or property, the SDK may silently fail to send any telemetry.

   Alternatively, you can initialize the filter in code. In a suitable initialization class, for example, AppStart in Global.asax.cs, insert your processor into the chain:

   var builder = TelemetryConfiguration.Active.DefaultTelemetrySink.TelemetryProcessorChainBuilder;
   builder.Use((next) => new SuccessfulDependencyFilter(next));
   
   // If you have more processors:
   builder.Use((next) => new AnotherProcessor(next));
   
   builder.Build();
   

   Telemetry clients created after this point use your processors.

   ASP.NET Core/Worker service

   Note

   Adding a processor by using ApplicationInsights.config or TelemetryConfiguration.Active isn't valid for ASP.NET Core applications or if you're using the Microsoft.ApplicationInsights.WorkerService SDK.

   For apps written by using ASP.NET Core or WorkerService, adding a new telemetry processor is done by using the AddApplicationInsightsTelemetryProcessor extension method on IServiceCollection, as shown. This method is called in the ConfigureServices method of your Startup.cs class.

   public void ConfigureServices(IServiceCollection services)
   {
       // ...
       services.AddApplicationInsightsTelemetry();
       services.AddApplicationInsightsTelemetryProcessor<SuccessfulDependencyFilter>();
   
       // If you have more processors:
       services.AddApplicationInsightsTelemetryProcessor<AnotherProcessor>();
   }
   

   To register telemetry processors that need parameters in ASP.NET Core, create a custom class implementing ITelemetryProcessorFactory. Call the constructor with the desired parameters in the Create method and then use AddSingleton<ITelemetryProcessorFactory, MyTelemetryProcessorFactory>().

Example filters

Synthetic requests

Filter out bots and web tests. Although Metrics Explorer gives you the option to filter out synthetic sources, this option reduces traffic and ingestion size by filtering them at the SDK itself.

public void Process(ITelemetry item)
{
    if (!string.IsNullOrEmpty(item.Context.Operation.SyntheticSource)) {return;}
    
    // Send everything else:
    this.Next.Process(item);
}

Failed authentication

Filter out requests with a "401" response.

public void Process(ITelemetry item)
{
    var request = item as RequestTelemetry;

    if (request != null &&
    request.ResponseCode.Equals("401", StringComparison.OrdinalIgnoreCase))
    {
        // To filter out an item, return without calling the next processor.
        return;
    }

    // Send everything else
    this.Next.Process(item);
}

Filter out fast remote dependency calls

If you want to diagnose only calls that are slow, filter out the fast ones.

Note

This filtering will skew the statistics you see on the portal.

public void Process(ITelemetry item)
{
    var request = item as DependencyTelemetry;

    if (request != null && request.Duration.TotalMilliseconds < 100)
    {
        return;
    }
    this.Next.Process(item);
}

Diagnose dependency issues

This blog describes a project to diagnose dependency issues by automatically sending regular pings to dependencies.

Java applications

To learn more about telemetry processors and their implementation in Java, reference the Java telemetry processors documentation.

JavaScript web applications

You can filter telemetry from JavaScript web applications by using ITelemetryInitializer.

1. Create a telemetry initializer callback function. The callback function takes ITelemetryItem as a parameter, which is the event that's being processed. Returning false from this callback results in the telemetry item to be filtered out.

   var filteringFunction = (envelope) => {
     if (envelope.data.someField === 'tobefilteredout') {
       return false;
     }
     return true;
   };
   

2. Add your telemetry initializer callback:

   appInsights.addTelemetryInitializer(filteringFunction);
   

Add/modify properties: ITelemetryInitializer

Use telemetry initializers to enrich telemetry with additional information or to override telemetry properties set by the standard telemetry modules.

For example, Application Insights for a web package collects telemetry about HTTP requests. By default, it flags any request with a response code >=400 as failed. If instead you want to treat 400 as a success, you can provide a telemetry initializer that sets the success property.

If you provide a telemetry initializer, it's called whenever any of the Track*() methods are called. This initializer includes Track() methods called by the standard telemetry modules. By convention, these modules don't set any property that was already set by an initializer. Telemetry initializers are called before calling telemetry processors, so any enrichments done by initializers are visible to processors.

.NET applications

1. Define your initializer

   using System;
   using Microsoft.ApplicationInsights.Channel;
   using Microsoft.ApplicationInsights.DataContracts;
   using Microsoft.ApplicationInsights.Extensibility;
   
   namespace MvcWebRole.Telemetry
   {
     /*
      * Custom TelemetryInitializer that overrides the default SDK
      * behavior of treating response codes >= 400 as failed requests
      *
      */
       public class MyTelemetryInitializer : ITelemetryInitializer
       {
           public void Initialize(ITelemetry telemetry)
           {
               var requestTelemetry = telemetry as RequestTelemetry;
               // Is this a TrackRequest() ?
               if (requestTelemetry == null) return;
               int code;
               bool parsed = Int32.TryParse(requestTelemetry.ResponseCode, out code);
               if (!parsed) return;
               if (code >= 400 && code < 500)
               {
                   // If we set the Success property, the SDK won't change it:
                   requestTelemetry.Success = true;
   
                   // Allow us to filter these requests in the portal:
                   requestTelemetry.Properties["Overridden400s"] = "true";
               }
               // else leave the SDK to set the Success property
           }
       }
   }
   

2. Load your initializer

   ASP.NET

   In ApplicationInsights.config:

   <ApplicationInsights>
     <TelemetryInitializers>
       <!-- Fully qualified type name, assembly name: -->
       <Add Type="MvcWebRole.Telemetry.MyTelemetryInitializer, MvcWebRole"/>
       ...
     </TelemetryInitializers>
   </ApplicationInsights>
   

   Alternatively, you can instantiate the initializer in code, for example, in Global.aspx.cs:

   protected void Application_Start()
   {
       // ...
       TelemetryConfiguration.Active.TelemetryInitializers.Add(new MyTelemetryInitializer());
   }
   

   See more of this sample.

   ASP.NET Core/Worker service

   Note

   Adding an initializer by using ApplicationInsights.config or TelemetryConfiguration.Active isn't valid for ASP.NET Core applications or if you're using the Microsoft.ApplicationInsights.WorkerService SDK.

   For apps written using ASP.NET Core or WorkerService, adding a new telemetry initializer is done by adding it to the Dependency Injection container, as shown. Accomplish this step in the Startup.ConfigureServices method.

   using Microsoft.ApplicationInsights.Extensibility;
   using CustomInitializer.Telemetry;
   public void ConfigureServices(IServiceCollection services)
   {
       services.AddSingleton<ITelemetryInitializer, MyTelemetryInitializer>();
   }
   

JavaScript telemetry initializers

Insert a JavaScript telemetry initializer, if needed. For more information on the telemetry initializers for the Application Insights JavaScript SDK, see Telemetry initializers.

JavaScript (Web) SDK Loader Script

Insert a telemetry initializer by adding the onInit callback function in the JavaScript (Web) SDK Loader Script configuration:

<script type="text/javascript">
!(function (cfg){function e(){cfg.onInit&&cfg.onInit(n)}var x,w,D,t,E,n,C=window,O=document,b=C.location,q="script",I="ingestionendpoint",L="disableExceptionTracking",j="ai.device.";"instrumentationKey"[x="toLowerCase"](),w="crossOrigin",D="POST",t="appInsightsSDK",E=cfg.name||"appInsights",(cfg.name||C[t])&&(C[t]=E),n=C[E]||function(g){var f=!1,m=!1,h={initialize:!0,queue:[],sv:"8",version:2,config:g};function v(e,t){var n={},i="Browser";function a(e){e=""+e;return 1===e.length?"0"+e:e}return n[j+"id"]=i[x](),n[j+"type"]=i,n["ai.operation.name"]=b&&b.pathname||"_unknown_",n["ai.internal.sdkVersion"]="javascript:snippet_"+(h.sv||h.version),{time:(i=new Date).getUTCFullYear()+"-"+a(1+i.getUTCMonth())+"-"+a(i.getUTCDate())+"T"+a(i.getUTCHours())+":"+a(i.getUTCMinutes())+":"+a(i.getUTCSeconds())+"."+(i.getUTCMilliseconds()/1e3).toFixed(3).slice(2,5)+"Z",iKey:e,name:"Microsoft.ApplicationInsights."+e.replace(/-/g,"")+"."+t,sampleRate:100,tags:n,data:{baseData:{ver:2}},ver:undefined,seq:"1",aiDataContract:undefined}}var n,i,t,a,y=-1,T=0,S=["js.monitor.azure.com","js.cdn.applicationinsights.io","js.cdn.monitor.azure.com","js0.cdn.applicationinsights.io","js0.cdn.monitor.azure.com","js2.cdn.applicationinsights.io","js2.cdn.monitor.azure.com","az416426.vo.msecnd.net"],o=g.url||cfg.src,r=function(){return s(o,null)};function s(d,t){if((n=navigator)&&(~(n=(n.userAgent||"").toLowerCase()).indexOf("msie")||~n.indexOf("trident/"))&&~d.indexOf("ai.3")&&(d=d.replace(/(\/)(ai\.3\.)([^\d]*)$/,function(e,t,n){return t+"ai.2"+n})),!1!==cfg.cr)for(var e=0;e<S.length;e++)if(0<d.indexOf(S[e])){y=e;break}var n,i=function(e){var a,t,n,i,o,r,s,c,u,l;h.queue=[],m||(0<=y&&T+1<S.length?(a=(y+T+1)%S.length,p(d.replace(/^(.*\/\/)([\w\.]*)(\/.*)$/,function(e,t,n,i){return t+S[a]+i})),T+=1):(f=m=!0,s=d,!0!==cfg.dle&&(c=(t=function(){var e,t={},n=g.connectionString;if(n)for(var i=n.split(";"),a=0;a<i.length;a++){var o=i[a].split("=");2===o.length&&(t[o[0][x]()]=o[1])}return t[I]||(e=(n=t.endpointsuffix)?t.location:null,t[I]="https://"+(e?e+".":"")+"dc."+(n||"services.visualstudio.com")),t}()).instrumentationkey||g.instrumentationKey||"",t=(t=(t=t[I])&&"/"===t.slice(-1)?t.slice(0,-1):t)?t+"/v2/track":g.endpointUrl,t=g.userOverrideEndpointUrl||t,(n=[]).push((i="SDK LOAD Failure: Failed to load Application Insights SDK script (See stack for details)",o=s,u=t,(l=(r=v(c,"Exception")).data).baseType="ExceptionData",l.baseData.exceptions=[{typeName:"SDKLoadFailed",message:i.replace(/\./g,"-"),hasFullStack:!1,stack:i+"\nSnippet failed to load ["+o+"] -- Telemetry is disabled\nHelp Link: https://go.microsoft.com/fwlink/?linkid=2128109\nHost: "+(b&&b.pathname||"_unknown_")+"\nEndpoint: "+u,parsedStack:[]}],r)),n.push((l=s,i=t,(u=(o=v(c,"Message")).data).baseType="MessageData",(r=u.baseData).message='AI (Internal): 99 message:"'+("SDK LOAD Failure: Failed to load Application Insights SDK script (See stack for details) ("+l+")").replace(/\"/g,"")+'"',r.properties={endpoint:i},o)),s=n,c=t,JSON&&((u=C.fetch)&&!cfg.useXhr?u(c,{method:D,body:JSON.stringify(s),mode:"cors"}):XMLHttpRequest&&((l=new XMLHttpRequest).open(D,c),l.setRequestHeader("Content-type","application/json"),l.send(JSON.stringify(s)))))))},a=function(e,t){m||setTimeout(function(){!t&&h.core||i()},500),f=!1},p=function(e){var n=O.createElement(q),e=(n.src=e,t&&(n.integrity=t),n.setAttribute("data-ai-name",E),cfg[w]);return!e&&""!==e||"undefined"==n[w]||(n[w]=e),n.onload=a,n.onerror=i,n.onreadystatechange=function(e,t){"loaded"!==n.readyState&&"complete"!==n.readyState||a(0,t)},cfg.ld&&cfg.ld<0?O.getElementsByTagName("head")[0].appendChild(n):setTimeout(function(){O.getElementsByTagName(q)[0].parentNode.appendChild(n)},cfg.ld||0),n};p(d)}cfg.sri&&(n=o.match(/^((http[s]?:\/\/.*\/)\w+(\.\d+){1,5})\.(([\w]+\.){0,2}js)$/))&&6===n.length?(d="".concat(n[1],".integrity.json"),i="@".concat(n[4]),l=window.fetch,t=function(e){if(!e.ext||!e.ext[i]||!e.ext[i].file)throw Error("Error Loading JSON response");var t=e.ext[i].integrity||null;s(o=n[2]+e.ext[i].file,t)},l&&!cfg.useXhr?l(d,{method:"GET",mode:"cors"}).then(function(e){return e.json()["catch"](function(){return{}})}).then(t)["catch"](r):XMLHttpRequest&&((a=new XMLHttpRequest).open("GET",d),a.onreadystatechange=function(){if(a.readyState===XMLHttpRequest.DONE)if(200===a.status)try{t(JSON.parse(a.responseText))}catch(e){r()}else r()},a.send())):o&&r();try{h.cookie=O.cookie}catch(k){}function e(e){for(;e.length;)!function(t){h[t]=function(){var e=arguments;f||h.queue.push(function(){h[t].apply(h,e)})}}(e.pop())}var c,u,l="track",d="TrackPage",p="TrackEvent",l=(e([l+"Event",l+"PageView",l+"Exception",l+"Trace",l+"DependencyData",l+"Metric",l+"PageViewPerformance","start"+d,"stop"+d,"start"+p,"stop"+p,"addTelemetryInitializer","setAuthenticatedUserContext","clearAuthenticatedUserContext","flush"]),h.SeverityLevel={Verbose:0,Information:1,Warning:2,Error:3,Critical:4},(g.extensionConfig||{}).ApplicationInsightsAnalytics||{});return!0!==g[L]&&!0!==l[L]&&(e(["_"+(c="onerror")]),u=C[c],C[c]=function(e,t,n,i,a){var o=u&&u(e,t,n,i,a);return!0!==o&&h["_"+c]({message:e,url:t,lineNumber:n,columnNumber:i,error:a,evt:C.event}),o},g.autoExceptionInstrumented=!0),h}(cfg.cfg),(C[E]=n).queue&&0===n.queue.length?(n.queue.push(e),n.trackPageView({})):e();})({
src: "https://js.monitor.azure.com/scripts/b/ai.3.gbl.min.js",
crossOrigin: "anonymous", // When supplied this will add the provided value as the cross origin attribute on the script tag
onInit: function (sdk) {
    sdk.addTelemetryInitializer(function (envelope) {
    envelope.data = envelope.data || {};
    envelope.data.someField = 'This item passed through my telemetry initializer';
    });
}, // Once the application insights instance has loaded and initialized this method will be called
// sri: false, // Custom optional value to specify whether fetching the snippet from integrity file and do integrity check
cfg: { // Application Insights Configuration
    connectionString: "YOUR_CONNECTION_STRING"
}});
</script>

npm package

import { ApplicationInsights } from '@microsoft/applicationinsights-web'

const appInsights = new ApplicationInsights({ config: {
  connectionString: 'YOUR_CONNECTION_STRING'
  /* ...Other Configuration Options... */
} });
appInsights.loadAppInsights();
// To insert a telemetry initializer, uncomment the following code.
/** var telemetryInitializer = (envelope) => {   envelope.data = envelope.data || {}; envelope.data.someField = 'This item passed through my telemetry initializer'; 
 };
appInsights.addTelemetryInitializer(telemetryInitializer); **/ 
appInsights.trackPageView();

For a summary of the noncustom properties available on the telemetry item, see Application Insights Export Data Model.

You can add as many initializers as you like. They're called in the order that they're added.

OpenCensus Python telemetry processors

Telemetry processors in OpenCensus Python are simply callback functions called to process telemetry before they're exported. The callback function must accept an envelope data type as its parameter. To filter out telemetry from being exported, make sure the callback function returns False. You can see the schema for Azure Monitor data types in the envelopes on GitHub.

Note

You can modify cloud_RoleName by changing the ai.cloud.role attribute in the tags field.

def callback_function(envelope):
    envelope.tags['ai.cloud.role'] = 'new_role_name'

# Example for log exporter
import logging

from opencensus.ext.azure.log_exporter import AzureLogHandler

logger = logging.getLogger(__name__)

# Callback function to append '_hello' to each log message telemetry
def callback_function(envelope):
    envelope.data.baseData.message += '_hello'
    return True

handler = AzureLogHandler(connection_string='InstrumentationKey=<your-instrumentation_key-here>')
handler.add_telemetry_processor(callback_function)
logger.addHandler(handler)
logger.warning('Hello, World!')

# Example for trace exporter
import requests

from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace import config_integration
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer

config_integration.trace_integrations(['requests'])

# Callback function to add os_type: linux to span properties
def callback_function(envelope):
    envelope.data.baseData.properties['os_type'] = 'linux'
    return True

exporter = AzureExporter(
    connection_string='InstrumentationKey=<your-instrumentation-key-here>'
)
exporter.add_telemetry_processor(callback_function)
tracer = Tracer(exporter=exporter, sampler=ProbabilitySampler(1.0))
with tracer.span(name='parent'):
response = requests.get(url='https://www.wikipedia.org/wiki/Rabbit')

# Example for metrics exporter
import time

from opencensus.ext.azure import metrics_exporter
from opencensus.stats import aggregation as aggregation_module
from opencensus.stats import measure as measure_module
from opencensus.stats import stats as stats_module
from opencensus.stats import view as view_module
from opencensus.tags import tag_map as tag_map_module

stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder

CARROTS_MEASURE = measure_module.MeasureInt("carrots",
                                            "number of carrots",
                                            "carrots")
CARROTS_VIEW = view_module.View("carrots_view",
                                "number of carrots",
                                [],
                                CARROTS_MEASURE,
                                aggregation_module.CountAggregation())

# Callback function to only export the metric if value is greater than 0
def callback_function(envelope):
    return envelope.data.baseData.metrics[0].value > 0

def main():
    # Enable metrics
    # Set the interval in seconds in which you want to send metrics
    exporter = metrics_exporter.new_metrics_exporter(connection_string='InstrumentationKey=<your-instrumentation-key-here>')
    exporter.add_telemetry_processor(callback_function)
    view_manager.register_exporter(exporter)

    view_manager.register_view(CARROTS_VIEW)
    mmap = stats_recorder.new_measurement_map()
    tmap = tag_map_module.TagMap()

    mmap.measure_int_put(CARROTS_MEASURE, 1000)
    mmap.record(tmap)
    # Default export interval is every 15.0s
    # Your application should run for at least this amount
    # of time so the exporter will meet this interval
    # Sleep can fulfill this
    time.sleep(60)

    print("Done recording metrics")

if __name__ == "__main__":
    main()

You can add as many processors as you like. They're called in the order that they're added. If one processor throws an exception, it doesn't impact the following processors.

Example TelemetryInitializers

Add a custom property

The following sample initializer adds a custom property to every tracked telemetry.

public void Initialize(ITelemetry item)
{
    var itemProperties = item as ISupportProperties;
    if(itemProperties != null && !itemProperties.Properties.ContainsKey("customProp"))
    {
        itemProperties.Properties["customProp"] = "customValue";
    }
}

Add a cloud role name

The following sample initializer sets the cloud role name to every tracked telemetry.

public void Initialize(ITelemetry telemetry)
{
    if (string.IsNullOrEmpty(telemetry.Context.Cloud.RoleName))
    {
        telemetry.Context.Cloud.RoleName = "MyCloudRoleName";
    }
}

Control the client IP address used for geolocation mappings

The following sample initializer sets the client IP, which is used for geolocation mapping, instead of the client socket IP address, during telemetry ingestion.

public void Initialize(ITelemetry telemetry)
{
    var request = telemetry as RequestTelemetry;
    if (request == null) return true;
    request.Context.Location.Ip = "{client ip address}"; // Could utilize System.Web.HttpContext.Current.Request.UserHostAddress;   
    return true;
}

ITelemetryProcessor and ITelemetryInitializer

What's the difference between telemetry processors and telemetry initializers?

• There are some overlaps in what you can do with them. Both can be used to add or modify properties of telemetry, although we recommend that you use initializers for that purpose.
• Telemetry initializers always run before telemetry processors.
• Telemetry initializers may be called more than once. By convention, they don't set any property that was already set.
• Telemetry processors allow you to completely replace or discard a telemetry item.
• All registered telemetry initializers are called for every telemetry item. For telemetry processors, SDK guarantees calling the first telemetry processor. Whether the rest of the processors are called or not is decided by the preceding telemetry processors.
• Use telemetry initializers to enrich telemetry with more properties or override an existing one. Use a telemetry processor to filter out telemetry.

Note

JavaScript only has telemetry initializers which can filter out events by using ITelemetryInitializer

Troubleshoot ApplicationInsights.config

• Confirm that the fully qualified type name and assembly name are correct.
• Confirm that the applicationinsights.config file is in your output directory and contains any recent changes.

Azure Monitor Telemetry Data Types Reference

• ASP.NET Core SDK
• ASP.NET SDK
• Node.js SDK
• Java SDK (via config)
• Python SDK
• JavaScript SDK

Reference docs

• API overview
• ASP.NET reference

SDK code

• ASP.NET Core SDK
• ASP.NET SDK
• JavaScript SDK

Next steps

• Search events and logs
• sampling