diff --git a/content/en/serverless/azure_functions/_index.md b/content/en/serverless/azure_functions/_index.md
index 9a84bd3fa529d..60f1d94c62194 100644
--- a/content/en/serverless/azure_functions/_index.md
+++ b/content/en/serverless/azure_functions/_index.md
@@ -3,11 +3,11 @@ title: Install Serverless Monitoring for Azure Functions
 ---
 
 ## Overview
-This page explains how to collect traces, trace metrics, runtime metrics, and custom metrics from your Azure Functions. To collect additional metrics, install the [Datadog Azure integration][6].
+This page explains how to collect traces, trace metrics, runtime metrics, and custom metrics from your Azure Functions. To collect additional metrics, install the [Datadog Azure integration][5].
 
 ## Setup
 
-{{< programming-lang-wrapper langs="nodejs,python,java" >}}
+{{< programming-lang-wrapper langs="nodejs,python,java,dotnet" >}}
 {{< programming-lang lang="nodejs" >}}
 1. **Install dependencies**. Run the following commands:
    ```shell
@@ -15,11 +15,9 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    npm install dd-trace
    ```
 
-   To use [automatic instrumentation][1], you must use `dd-trace` v5.25+.
-
    Datadog recommends pinning the package versions and regularly upgrading to the latest versions of both `@datadog/serverless-compat` and `dd-trace` to ensure you have access to enhancements and bug fixes.
 
-2. **Start the Datadog serverless compatibility layer and initialize the Node.js tracer**. Add the following lines to your main application entry point file (for example, `app.js`):
+2. **Start the Datadog Serverless Compatibility Layer and initialize the Datadog Node.js tracer**. Add the following lines to your main application entry point file (for example, `app.js`):
 
    ```js
    require('@datadog/serverless-compat').start();
@@ -28,13 +26,11 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    const tracer = require('dd-trace').init()
    ```
 
-3. (Optional) **Enable runtime metrics**. See [Node.js Runtime Metrics][2].
+3. **Configure the Datadog Node.js tracer**
 
-4. (Optional) **Enable custom metrics**. See [Metric Submission: DogStatsD][3].
+   [Configuring the Node.js Tracing Library][1]
 
-[1]: /tracing/trace_collection/automatic_instrumentation/?tab=singlestepinstrumentation
-[2]: /tracing/metrics/runtime_metrics/nodejs/?tab=environmentvariables
-[3]: /metrics/custom_metrics/dogstatsd_metrics_submission/?code-lang=nodejs
+[1]:/tracing/trace_collection/library_config/nodejs
 {{< /programming-lang >}}
 {{< programming-lang lang="python" >}}
 1. **Install dependencies**. Run the following commands:
@@ -43,11 +39,9 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    pip install ddtrace
    ```
 
-   To use [automatic instrumentation][1], you must use `dd-trace` v2.19+.
-
    Datadog recommends using the latest versions of both `datadog-serverless-compat` and `ddtrace` to ensure you have access to enhancements and bug fixes.
 
-2. **Initialize the Datadog Python tracer and serverless compatibility layer**. Add the following lines to your main application entry point file:
+2. **Start the Datadog Serverless Compatibility Layer and initialize the Datadog Python tracer**. Add the following lines to your main application entry point file:
 
    ```python
    from datadog_serverless_compat import start
@@ -56,13 +50,11 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    start()
    ```
 
-3. (Optional) **Enable runtime metrics**. See [Python Runtime Metrics][2].
+3. **Configure the Datadog Python tracer**
 
-4. (Optional) **Enable custom metrics**. See [Metric Submission: DogStatsD][3].
+   [Configuring the Python Tracing Library][1]
 
-[1]: /tracing/trace_collection/automatic_instrumentation/?tab=singlestepinstrumentation
-[2]: /tracing/metrics/runtime_metrics/python/
-[3]: /metrics/custom_metrics/dogstatsd_metrics_submission/?code-lang=python
+[1]:/tracing/trace_collection/library_config/python
 {{< /programming-lang >}}
 {{< programming-lang lang="java" >}}
 1. **Install dependencies**. Download the Datadog JARs and deploy them with your function:
@@ -70,29 +62,103 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    wget -O dd-java-agent.jar 'https://dtdg.co/latest-java-tracer'
    wget -O dd-serverless-compat-java-agent.jar 'https://dtdg.co/latest-serverless-compat-java-agent'
    ```
-   See Datadog's [Maven Repository][4] for any specific version of the Datadog Serverless Compatibility Layer.
-
-   To use [automatic instrumentation][1], you must use `dd-java-agent` v1.48.0+.
+   See Datadog's [Maven Repository][1] for any specific version of the Datadog Serverless Compatibility Layer.
 
    Datadog recommends regularly upgrading to the latest versions of both `dd-serverless-compat-java-agent` and `dd-java-agent` to ensure you have access to enhancements and bug fixes.
 
-2. **Start the Datadog serverless compatibility layer and initialize the Java tracer**. Add the following `-javaagent` arguments to the JVM options.:
+2. **Start the Datadog Serverless Compatibility Layer and initialize the Datadog Java tracer**. Add the following `-javaagent` arguments to the JVM options.:
 
    ```bash
    -javaagent:/path/to/dd-serverless-compat-java-agent.jar -javaagent:/path/to/dd-java-agent.jar
    ```
 
-   **Note**: the environment variable to set JVM options depends on the hosting plan (example, Consumption, Elastic Premium, Dedicated). See [Azure Functions Java developer guide][5] for more details on the appropriate environment variable for your hosting plan.
+   **Note**: the environment variable to set JVM options depends on the hosting plan (example, Consumption, Elastic Premium, Dedicated). See [Azure Functions Java developer guide][2] for more details on the appropriate environment variable for your hosting plan.
 
-3. (Optional) **Enable runtime metrics**. See [Java Runtime Metrics][2].
+3. **Configure the Datadog Java tracer**
 
-4. (Optional) **Enable custom metrics**. See [Metric Submission: DogStatsD][3].
+   [Configuring the Java Tracing Library][3]
 
-[1]: /tracing/trace_collection/automatic_instrumentation/?tab=singlestepinstrumentation
-[2]: /tracing/metrics/runtime_metrics/?tab=java#environment-variables
-[3]: /metrics/custom_metrics/dogstatsd_metrics_submission/?code-lang=java
-[4]: https://repo1.maven.org/maven2/com/datadoghq/dd-serverless-compat-java-agent/
-[5]: https://learn.microsoft.com/en-us/azure/azure-functions/functions-reference-java?tabs=bash%2Cconsumption#customize-jvm
+[1]: https://repo1.maven.org/maven2/com/datadoghq/dd-serverless-compat-java-agent/
+[2]: https://learn.microsoft.com/en-us/azure/azure-functions/functions-reference-java?tabs=bash%2Cconsumption#customize-jvm
+[3]: /tracing/trace_collection/library_config/java
+{{< /programming-lang >}}
+{{< programming-lang lang="dotnet" >}}
+1. **Install dependencies**. Run the following commands:
+   ```shell
+   dotnet package add Datadog.Azure.Functions
+   ```
+
+   Datadog recommends regularly upgrading to the latest version of `Datadog.AzureFunctions` to ensure you have access to enhancements and bug fixes.
+
+2. **Start the Datadog Serverless Compatibility Layer**.
+
+   If your Azure Function app uses the Isolated Worker model, add the following lines to your main application entry point file:
+   ```csharp
+   Datadog.Serverless.CompatibilityLayer.Start();
+   ```
+
+   If your Azure Function app uses the In-Process model, add a NuGet package reference to `Microsoft.Azure.Functions.Extensions`:
+   ```shell
+   dotnet package add Microsoft.Azure.Functions.Extensions
+   ```
+
+   And add the following `.cs` file to your application:
+   ```csharp
+   using Datadog.Serverless;
+   using Microsoft.Azure.Functions.Extensions.DependencyInjection;
+
+   [assembly: FunctionsStartup(typeof(MyFunctionApp.Startup))]
+
+   namespace MyFunctionApp
+   {
+      public class Startup : FunctionsStartup
+      {
+         public override void Configure(IFunctionsHostBuilder builder)
+         {
+               Datadog.Serverless.CompatibilityLayer.Start();
+         }
+      }
+   }
+   ```
+
+3. **Configure Automatic Instrumentation**
+
+   If your Azure Function app runs on Windows, add the following environment variables to your Function app:
+   ```
+   CORECLR_ENABLE_PROFILING=1
+
+   CORECLR_PROFILER={846F5F1C-F9AE-4B07-969E-05C26BC060D8}
+
+   CORECLR_PROFILER_PATH_64=
+   C:\home\site\wwwroot\datadog\win-x64\Datadog.Trace.ClrProfiler.Native.dll
+
+   CORECLR_PROFILER_PATH_32=
+   C:\home\site\wwwroot\datadog\win-x86\Datadog.Trace.ClrProfiler.Native.dll
+
+   DD_DOTNET_TRACER_HOME=C:\home\site\wwwroot\datadog
+
+   ```
+
+   If your Azure Function app runs on Linux, add the following environment variables to your Function app:
+   ```
+   CORECLR_ENABLE_PROFILING=1
+
+   CORECLR_PROFILER={846F5F1C-F9AE-4B07-969E-05C26BC060D8}
+
+   CORECLR_PROFILER_PATH=
+      /home/site/wwwroot/datadog/linux-x64/Datadog.Trace.ClrProfiler.Native.so
+
+   DD_DOTNET_TRACER_HOME=/home/site/wwwroot/datadog
+
+   ```
+
+4. **Configure the Datadog .NET tracer**
+
+   - [Configuring the .NET Core Tracing Library][1]
+   - [Configuring the .NET Framework Tracing Library][2]
+
+[1]:/tracing/trace_collection/library_config/dotnet-core
+[2]:/tracing/trace_collection/library_config/dotnet-framework
 {{< /programming-lang >}}
 {{< /programming-lang-wrapper >}}
 
@@ -105,50 +171,24 @@ This page explains how to collect traces, trace metrics, runtime metrics, and cu
    | `DD_API_KEY` | Your [Datadog API key][1]. |
    | `DD_SITE` | Your [Datadog site][2]. For example, {{< region-param key=dd_site code="true" >}}. |
 
-7. **Configure Unified Service Tagging**. You can collect metrics from your Azure Functions by installing the [Datadog Azure integration][6]. To correlate these metrics with your traces, first set the `env`, `service`, and `version` tags on your resource in Azure. Then, configure the following environment variables. You can add custom tags as `DD_TAGS`.
+7. **Configure Unified Service Tagging**. You can collect metrics from your Azure Functions by installing the [Datadog Azure integration][5]. To correlate these metrics with your traces, first set the `env`, `service`, and `version` tags on your resource in Azure. Then, configure the following environment variables.
 
    | Name | Value |
    | ---- | ----- |
-   | `DD_ENV` | How you want to tag your env for [Unified Service Tagging][9]. For example, `prod`. |
-   | `DD_SERVICE` | How you want to tag your service for [Unified Service Tagging][9].  |
-   | `DD_VERSION` | How you want to tag your version for [Unified Service Tagging][9]. |
-   | `DD_TAGS` | Your comma-separated custom tags. For example, `key1:value1,key2:value2`.  |
+   | `DD_ENV` | How you want to tag your env for [Unified Service Tagging][7]. For example, `prod`. |
+   | `DD_SERVICE` | How you want to tag your service for [Unified Service Tagging][7].  |
+   | `DD_VERSION` | How you want to tag your version for [Unified Service Tagging][7]. |
 
 ## What's next?
 
-- You can view your Azure Functions traces in [Trace Explorer][4]. Search for the service name you set in the `DD_SERVICE` environment variable to see your traces.
-- You can use the [Serverless > Azure Functions][5] page to see your traces enriched with telemetry collected by the [Datadog Azure integration][6].
-
-### Enable/disable trace metrics
-
-[Trace metrics][3] are enabled by default. To configure trace metrics, use the following environment variable:
-
-{{< programming-lang-wrapper langs="nodejs,python,java" >}}
-{{< programming-lang lang="nodejs" >}}
-`DD_TRACE_STATS_COMPUTATION_ENABLED`
-: Enables (`true`) or disables (`false`) trace metrics. Defaults to `true`.
-
-  **Values**: `true`, `false`
-{{< /programming-lang >}}
-{{< programming-lang lang="python" >}}
-`DD_TRACE_STATS_COMPUTATION_ENABLED`
-: Enables (`true`) or disables (`false`) trace metrics. Defaults to `true`.
-
-  **Values**: `true`, `false`
-{{< /programming-lang >}}
-{{< programming-lang lang="java" >}}
-`DD_TRACE_TRACER_METRICS_ENABLED`
-: Enables (`true`) or disables (`false`) trace metrics. Defaults to `true`.
-
-  **Values**: `true`, `false`
-{{< /programming-lang >}}
-{{< /programming-lang-wrapper >}}
+- You can view your Azure Functions traces in [Trace Explorer][3]. Search for the service name you set in the `DD_SERVICE` environment variable to see your traces.
+- You can use the [Serverless > Azure Functions][4] page to see your traces enriched with telemetry collected by the [Datadog Azure integration][5].
 
 ## Troubleshooting
 
 ### Enable debug logs
 
-You can collect [debug logs][7] for troubleshooting. To configure debug logs, use the following environment variables:
+You can collect [debug logs][6] for troubleshooting. To configure debug logs, use the following environment variables:
 
 `DD_TRACE_DEBUG`
 : Enables (`true`) or disables (`false`) debug logging for the Datadog Tracing Library. Defaults to `false`.
@@ -160,17 +200,10 @@ You can collect [debug logs][7] for troubleshooting. To configure debug logs, us
 
   **Values**: `trace`, `debug`, `info`, `warn`, `error`, `critical`, `off`
 
-### Linux Consumption plans and GitHub Actions
-
-To use a GitHub Action to deploy to a Linux Consumption function, you must configure your workflow to use an Azure Service Principal for RBAC. See [Using Azure Service Principal for RBAC as Deployment Credential][8].
-
-
 [1]: /account_management/api-app-keys/#add-an-api-key-or-client-token
 [2]: /getting_started/site
-[3]: /tracing/metrics/metrics_namespace/
-[4]: https://app.datadoghq.com/apm/traces
-[5]: https://app.datadoghq.com/functions?cloud=azure&entity_view=function
-[6]: /integrations/azure/
-[7]: /tracing/troubleshooting/tracer_debug_logs/#enable-debug-mode
-[8]: https://github.com/Azure/functions-action?tab=readme-ov-file#using-azure-service-principal-for-rbac-as-deployment-credential
-[9]: /getting_started/tagging/unified_service_tagging/
\ No newline at end of file
+[3]: https://app.datadoghq.com/apm/traces
+[4]: https://app.datadoghq.com/functions?cloud=azure&entity_view=function
+[5]: /integrations/azure/
+[6]: /tracing/troubleshooting/tracer_debug_logs/#enable-debug-mode
+[7]: /getting_started/tagging/unified_service_tagging/