Develop C# class library functions using Azure Functions
Important
Support will end for the in-process model on November 10, 2026. We highly recommend that you migrate your apps to the isolated worker model for full support.
This article is an introduction to developing Azure Functions by using C# in .NET class libraries. These class libraries are used to run in-process with the Functions runtime. Your .NET functions can alternatively run _isolated from the Functions runtime, which offers several advantages. To learn more, see the isolated worker model. For a comprehensive comparison between these two models, see Differences between the in-process model and the isolated worker model.
Important
This article supports .NET class library functions that run in-process with the runtime. Your C# functions can also run out-of-process and isolated from the Functions runtime. The isolated worker process model is the only way to run non-LTS versions of .NET and .NET Framework apps in current versions of the Functions runtime. To learn more, see .NET isolated worker process functions. For a comprehensive comparison between isolated worker process and in-process .NET Functions, see Differences between in-process and isolate worker process .NET Azure Functions.
As a C# developer, you may also be interested in one of the following articles:
| Getting started | Concepts | Guided learning/samples |
|---|---|---|
Azure Functions supports C# and C# script programming languages. If you're looking for guidance on using C# in the Azure portal, see C# script (.csx) developer reference.
Supported versions
Versions of the Functions runtime support specific versions of .NET. To learn more about Functions versions, see Azure Functions runtime versions overview. Version support also depends on whether your functions run in-process or isolated worker process.
Note
To learn how to change the Functions runtime version used by your function app, see view and update the current runtime version.
The following table shows the highest level of .NET or .NET Framework that can be used with a specific version of Functions.
| Functions runtime version | Isolated worker model | In-process model4 |
|---|---|---|
| Functions 4.x1 | .NET 9.0 .NET 8.0 .NET Framework 4.82 |
.NET 8.0 |
| Functions 1.x3 | n/a | .NET Framework 4.8 |
1 .NET 6 was previously supported on both models but reached the end of official support on November 12, 2024. .NET 7 was previously supported on the isolated worker model but reached the end of official support on May 14, 2024.
2 The build process also requires the .NET SDK.
3 Support ends for version 1.x of the Azure Functions runtime on September 14, 2026. For more information, see this support announcement. For continued full support, you should migrate your apps to version 4.x.
4 Support ends for the in-process model on November 10, 2026. For more information, see this support announcement. For continued full support, you should migrate your apps to the isolated worker model.
For the latest news about Azure Functions releases, including the removal of specific older minor versions, monitor Azure App Service announcements.
Updating to target .NET 8
Apps using the in-process model can target .NET 8 by following the steps outlined in this section. However, if you choose to exercise this option, you should still begin planning your migration to the isolated worker model in advance of support ending for the in-process model on November 10, 2026.
Many apps can change the configuration of the function app in Azure without updates to code or redeployment. To run .NET 8 with the in-process model, three configurations are required:
- The application setting
FUNCTIONS_WORKER_RUNTIMEmust be set with the value "dotnet". - The application setting
FUNCTIONS_EXTENSION_VERSIONmust be set with the value "~4". - The application setting
FUNCTIONS_INPROC_NET8_ENABLEDmust be set with the value "1". - You must update the stack configuration to reference .NET 8.
Support for .NET 8 still uses version 4.x of the Functions runtime, and no change to the configured runtime version is required.
To update your local project, first make sure you are using the latest versions of local tools. Then ensure that the project references version 4.4.0 or later of Microsoft.NET.Sdk.Functions. You can then change your TargetFramework to "net8.0". You must also update local.settings.json to include both FUNCTIONS_WORKER_RUNTIME set to "dotnet" and FUNCTIONS_INPROC_NET8_ENABLED set to "1".
The following is an example of a minimal project file with these changes:
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net8.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Microsoft.NET.Sdk.Functions" Version="4.4.0" />
</ItemGroup>
<ItemGroup>
<None Update="host.json">
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</None>
<None Update="local.settings.json">
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
<CopyToPublishDirectory>Never</CopyToPublishDirectory>
</None>
</ItemGroup>
</Project>
The following is an example of a minimal local.settings.json file with these changes:
{
"IsEncrypted": false,
"Values": {
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"FUNCTIONS_INPROC_NET8_ENABLED": "1",
"FUNCTIONS_WORKER_RUNTIME": "dotnet"
}
}
If your app uses Microsoft.Azure.DurableTask.Netherite.AzureFunctions, ensure it targets version 1.5.3 or later. Due to a behavior change in .NET 8, apps with older versions of the package will throw an ambiguous constructor exception.
You might need to make other changes to your app based on the version support of its other dependencies.
Version 4.x of the Functions runtime provides equivalent functionality for .NET 6 and .NET 8. The in-process model does not include additional features or updates that integrate with new .NET 8 capabilities. For example, the runtime doesn't support keyed services. To take full advantage of the latest .NET 8 capabilities and enhancements, you must migrate to the isolated worker model.
Functions class library project
In Visual Studio, the Azure Functions project template creates a C# class library project that contains the following files:
- host.json - stores configuration settings that affect all functions in the project when running locally or in Azure.
- local.settings.json - stores app settings and connection strings that are used when running locally. This file contains secrets and isn't published to your function app in Azure. Instead, add app settings to your function app.
When you build the project, a folder structure that looks like the following example is generated in the build output directory:
<framework.version>
| - bin
| - MyFirstFunction
| | - function.json
| - MySecondFunction
| | - function.json
| - host.json
This directory is what gets deployed to your function app in Azure. The binding extensions required in version 2.x of the Functions runtime are added to the project as NuGet packages.
Important
The build process creates a function.json file for each function. This function.json file is not meant to be edited directly. You can't change binding configuration or disable the function by editing this file. To learn how to disable a function, see How to disable functions.
Methods recognized as functions
In a class library, a function is a method with a FunctionName and a trigger attribute, as shown in the following example:
public static class SimpleExample
{
[FunctionName("QueueTrigger")]
public static void Run(
[QueueTrigger("myqueue-items")] string myQueueItem,
ILogger log)
{
log.LogInformation($"C# function processed: {myQueueItem}");
}
}
The FunctionName attribute marks the method as a function entry point. The name must be unique within a project, start with a letter and only contain letters, numbers, _, and -, up to 127 characters in length. Project templates often create a method named Run, but the method name can be any valid C# method name. The above example shows a static method being used, but functions aren't required to be static.
The trigger attribute specifies the trigger type and binds input data to a method parameter. The example function is triggered by a queue message, and the queue message is passed to the method in the myQueueItem parameter.
Method signature parameters
The method signature may contain parameters other than the one used with the trigger attribute. Here are some of the other parameters that you can include:
- Input and output bindings marked as such by decorating them with attributes.
- An
ILoggerorTraceWriter(version 1.x-only) parameter for logging. - A
CancellationTokenparameter for graceful shutdown. - Binding expressions parameters to get trigger metadata.
The order of parameters in the function signature doesn't matter. For example, you can put trigger parameters before or after other bindings, and you can put the logger parameter before or after trigger or binding parameters.
Output bindings
A function can have zero or multiple output bindings defined by using output parameters.
The following example modifies the preceding one by adding an output queue binding named myQueueItemCopy. The function writes the contents of the message that triggers the function to a new message in a different queue.
public static class SimpleExampleWithOutput
{
[FunctionName("CopyQueueMessage")]
public static void Run(
[QueueTrigger("myqueue-items-source")] string myQueueItem,
[Queue("myqueue-items-destination")] out string myQueueItemCopy,
ILogger log)
{
log.LogInformation($"CopyQueueMessage function processed: {myQueueItem}");
myQueueItemCopy = myQueueItem;
}
}
Values assigned to output bindings are written when the function exits. You can use more than one output binding in a function by simply assigning values to multiple output parameters.
The binding reference articles (Storage queues, for example) explain which parameter types you can use with trigger, input, or output binding attributes.
Binding expressions example
The following code gets the name of the queue to monitor from an app setting, and it gets the queue message creation time in the insertionTime parameter.
public static class BindingExpressionsExample
{
[FunctionName("LogQueueMessage")]
public static void Run(
[QueueTrigger("%queueappsetting%")] string myQueueItem,
DateTimeOffset insertionTime,
ILogger log)
{
log.LogInformation($"Message content: {myQueueItem}");
log.LogInformation($"Created at: {insertionTime}");
}
}
Autogenerated function.json
The build process creates a function.json file in a function folder in the build folder. As noted earlier, this file isn't meant to be edited directly. You can't change binding configuration or disable the function by editing this file.
The purpose of this file is to provide information to the scale controller to use for scaling decisions on the Consumption plan. For this reason, the file only has trigger info, not input/output bindings.
The generated function.json file includes a configurationSource property that tells the runtime to use .NET attributes for bindings, rather than function.json configuration. Here's an example:
{
"generatedBy": "Microsoft.NET.Sdk.Functions-1.0.0.0",
"configurationSource": "attributes",
"bindings": [
{
"type": "queueTrigger",
"queueName": "%input-queue-name%",
"name": "myQueueItem"
}
],
"disabled": false,
"scriptFile": "..\\bin\\FunctionApp1.dll",
"entryPoint": "FunctionApp1.QueueTrigger.Run"
}
Microsoft.NET.Sdk.Functions
The function.json file generation is performed by the NuGet package Microsoft.NET.Sdk.Functions.
The following example shows the relevant parts of the .csproj files that have different target frameworks of the same Sdk package:
<PropertyGroup>
<TargetFramework>net8.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Microsoft.NET.Sdk.Functions" Version="4.5.0" />
</ItemGroup>
Important
Starting with version 4.0.6517 of the Core Tools, in-process model projects must reference version 4.5.0 or later of Microsoft.NET.Sdk.Functions. If an earlier version is used, the func start command will error.
Among the Sdk package dependencies are triggers and bindings. A 1.x project refers to 1.x triggers and bindings because those triggers and bindings target the .NET Framework, while 4.x triggers and bindings target .NET Core.
The Sdk package also depends on Newtonsoft.Json, and indirectly on WindowsAzure.Storage. These dependencies make sure that your project uses the versions of those packages that work with the Functions runtime version that the project targets. For example, Newtonsoft.Json has version 11 for .NET Framework 4.6.1, but the Functions runtime that targets .NET Framework 4.6.1 is only compatible with Newtonsoft.Json 9.0.1. So your function code in that project also has to use Newtonsoft.Json 9.0.1.
The source code for Microsoft.NET.Sdk.Functions is available in the GitHub repo azure-functions-vs-build-sdk.
Local runtime version
Visual Studio uses the Azure Functions Core Tools to run Functions projects on your local computer. The Core Tools is a command-line interface for the Functions runtime.
If you install the Core Tools using the Windows installer (MSI) package or by using npm, it doesn't affect the Core Tools version used by Visual Studio. For the Functions runtime version 1.x, Visual Studio stores Core Tools versions in %USERPROFILE%\AppData\Local\Azure.Functions.Cli and uses the latest version stored there. For Functions 4.x, the Core Tools are included in the Azure Functions and Web Jobs Tools extension. For Functions 1.x, you can see what version is being used in the console output when you run a Functions project:
[3/1/2018 9:59:53 AM] Starting Host (HostId=contoso2-1518597420, Version=2.0.11353.0, ProcessId=22020, Debug=False, Attempt=0, FunctionsExtensionVersion=)
ReadyToRun
You can compile your function app as ReadyToRun binaries. ReadyToRun is a form of ahead-of-time compilation that can improve startup performance to help reduce the impact of cold-start when running in a Consumption plan.
ReadyToRun is available in .NET 6 and later versions and requires version 4.0 of the Azure Functions runtime.
To compile your project as ReadyToRun, update your project file by adding the <PublishReadyToRun> and <RuntimeIdentifier> elements. The following is the configuration for publishing to a Windows 32-bit function app.
<PropertyGroup>
<TargetFramework>net8.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<PublishReadyToRun>true</PublishReadyToRun>
<RuntimeIdentifier>win-x86</RuntimeIdentifier>
</PropertyGroup>
Important
Starting in .NET 6, support for Composite ReadyToRun compilation has been added. Check out ReadyToRun Cross platform and architecture restrictions.
You can also build your app with ReadyToRun from the command line. For more information, see the -p:PublishReadyToRun=true option in dotnet publish.
Supported types for bindings
Each binding has its own supported types; for instance, a blob trigger attribute can be applied to a string parameter, a POCO parameter, a CloudBlockBlob parameter, or any of several other supported types. The binding reference article for blob bindings lists all supported parameter types. For more information, see Triggers and bindings and the binding reference docs for each binding type.
Tip
If you plan to use the HTTP or WebHook bindings, plan to avoid port exhaustion that can be caused by improper instantiation of HttpClient. For more information, see How to manage connections in Azure Functions.
Binding to method return value
You can use a method return value for an output binding, by applying the attribute to the method return value. For examples, see Triggers and bindings.
Use the return value only if a successful function execution always results in a return value to pass to the output binding. Otherwise, use ICollector or IAsyncCollector, as shown in the following section.
Writing multiple output values
To write multiple values to an output binding, or if a successful function invocation might not result in anything to pass to the output binding, use the ICollector or IAsyncCollector types. These types are write-only collections that are written to the output binding when the method completes.
This example writes multiple queue messages into the same queue using ICollector:
public static class ICollectorExample
{
[FunctionName("CopyQueueMessageICollector")]
public static void Run(
[QueueTrigger("myqueue-items-source-3")] string myQueueItem,
[Queue("myqueue-items-destination")] ICollector<string> myDestinationQueue,
ILogger log)
{
log.LogInformation($"C# function processed: {myQueueItem}");
myDestinationQueue.Add($"Copy 1: {myQueueItem}");
myDestinationQueue.Add($"Copy 2: {myQueueItem}");
}
}
Async
To make a function asynchronous, use the async keyword and return a Task object.
public static class AsyncExample
{
[FunctionName("BlobCopy")]
public static async Task RunAsync(
[BlobTrigger("sample-images/{blobName}")] Stream blobInput,
[Blob("sample-images-copies/{blobName}", FileAccess.Write)] Stream blobOutput,
CancellationToken token,
ILogger log)
{
log.LogInformation($"BlobCopy function processed.");
await blobInput.CopyToAsync(blobOutput, 4096, token);
}
}
You can't use out parameters in async functions. For output bindings, use the function return value or a collector object instead.
Cancellation tokens
A function can accept a CancellationToken parameter, which enables the operating system to notify your code when the function is about to be terminated. You can use this notification to make sure the function doesn't terminate unexpectedly in a way that leaves data in an inconsistent state.
Consider the case when you have a function that processes messages in batches. The following Azure Service Bus-triggered function processes an array of ServiceBusReceivedMessage objects, which represents a batch of incoming messages to be processed by a specific function invocation:
using Azure.Messaging.ServiceBus;
using System.Threading;
namespace ServiceBusCancellationToken
{
public static class servicebus
{
[FunctionName("servicebus")]
public static void Run([ServiceBusTrigger("csharpguitar", Connection = "SB_CONN")]
ServiceBusReceivedMessage[] messages, CancellationToken cancellationToken, ILogger log)
{
try
{
foreach (var message in messages)
{
if (cancellationToken.IsCancellationRequested)
{
log.LogInformation("A cancellation token was received. Taking precautionary actions.");
//Take precautions like noting how far along you are with processing the batch
log.LogInformation("Precautionary activities --complete--.");
break;
}
else
{
//business logic as usual
log.LogInformation($"Message: {message} was processed.");
}
}
}
catch (Exception ex)
{
log.LogInformation($"Something unexpected happened: {ex.Message}");
}
}
}
}
Logging
In your function code, you can write output to logs that appear as traces in Application Insights. The recommended way to write to the logs is to include a parameter of type ILogger, which is typically named log. Version 1.x of the Functions runtime used TraceWriter, which also writes to Application Insights, but doesn't support structured logging. Don't use Console.Write to write your logs, since this data isn't captured by Application Insights.
ILogger
In your function definition, include an ILogger parameter, which supports structured logging.
With an ILogger object, you call Log<level> extension methods on ILogger to create logs. The following code writes Information logs with category Function.<YOUR_FUNCTION_NAME>.User.:
public static async Task<HttpResponseMessage> Run(HttpRequestMessage req, ILogger logger)
{
logger.LogInformation("Request for item with key={itemKey}.", id);
To learn more about how Functions implements ILogger, see Collecting telemetry data. Categories prefixed with Function assume you're using an ILogger instance. If you choose to instead use an ILogger<T>, the category name may instead be based on T.
Structured logging
The order of placeholders, not their names, determines which parameters are used in the log message. Suppose you have the following code:
string partitionKey = "partitionKey";
string rowKey = "rowKey";
logger.LogInformation("partitionKey={partitionKey}, rowKey={rowKey}", partitionKey, rowKey);
If you keep the same message string and reverse the order of the parameters, the resulting message text would have the values in the wrong places.
Placeholders are handled this way so that you can do structured logging. Application Insights stores the parameter name-value pairs and the message string. The result is that the message arguments become fields that you can query on.
If your logger method call looks like the previous example, you can query the field customDimensions.prop__rowKey. The prop__ prefix is added to ensure there are no collisions between fields the runtime adds and fields your function code adds.
You can also query on the original message string by referencing the field customDimensions.prop__{OriginalFormat}.
Here's a sample JSON representation of customDimensions data:
{
"customDimensions": {
"prop__{OriginalFormat}":"C# Queue trigger function processed: {message}",
"Category":"Function",
"LogLevel":"Information",
"prop__message":"c9519cbf-b1e6-4b9b-bf24-cb7d10b1bb89"
}
}
Log custom telemetry
There's a Functions-specific version of the Application Insights SDK that you can use to send custom telemetry data from your functions to Application Insights: Microsoft.Azure.WebJobs.Logging.ApplicationInsights. Use the following command from the command prompt to install this package:
dotnet add package Microsoft.Azure.WebJobs.Logging.ApplicationInsights --version <VERSION>
In this command, replace <VERSION> with a version of this package that supports your installed version of Microsoft.Azure.WebJobs.
The following C# examples uses the custom telemetry API. The example is for a .NET class library, but the Application Insights code is the same for C# script.
Version 2.x and later versions of the runtime use newer features in Application Insights to automatically correlate telemetry with the current operation. There's no need to manually set the operation Id, ParentId, or Name fields.
using System;
using System.Threading.Tasks;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.AspNetCore.Http;
using Microsoft.Extensions.Logging;
using Microsoft.ApplicationInsights;
using Microsoft.ApplicationInsights.DataContracts;
using Microsoft.ApplicationInsights.Extensibility;
using System.Linq;
namespace functionapp0915
{
public class HttpTrigger2
{
private readonly TelemetryClient telemetryClient;
/// Using dependency injection will guarantee that you use the same configuration for telemetry collected automatically and manually.
public HttpTrigger2(TelemetryConfiguration telemetryConfiguration)
{
this.telemetryClient = new TelemetryClient(telemetryConfiguration);
}
[FunctionName("HttpTrigger2")]
public Task<IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = null)]
HttpRequest req, ExecutionContext context, ILogger log)
{
log.LogInformation("C# HTTP trigger function processed a request.");
DateTime start = DateTime.UtcNow;
// Parse query parameter
string name = req.Query
.FirstOrDefault(q => string.Compare(q.Key, "name", true) == 0)
.Value;
// Write an event to the customEvents table.
var evt = new EventTelemetry("Function called");
evt.Context.User.Id = name;
this.telemetryClient.TrackEvent(evt);
// Generate a custom metric, in this case let's use ContentLength.
this.telemetryClient.GetMetric("contentLength").TrackValue(req.ContentLength);
// Log a custom dependency in the dependencies table.
var dependency = new DependencyTelemetry
{
Name = "GET api/planets/1/",
Target = "swapi.co",
Data = "https://swapi.co/api/planets/1/",
Timestamp = start,
Duration = DateTime.UtcNow - start,
Success = true
};
dependency.Context.User.Id = name;
this.telemetryClient.TrackDependency(dependency);
return Task.FromResult<IActionResult>(new OkResult());
}
}
}
In this example, the custom metric data gets aggregated by the host before being sent to the customMetrics table. To learn more, see the GetMetric documentation in Application Insights.
When running locally, you must add the APPINSIGHTS_INSTRUMENTATIONKEY setting, with the Application Insights key, to the local.settings.json file.
Don't call TrackRequest or StartOperation<RequestTelemetry> because you'll see duplicate requests for a function invocation. The Functions runtime automatically tracks requests.
Don't set telemetryClient.Context.Operation.Id. This global setting causes incorrect correlation when many functions are running simultaneously. Instead, create a new telemetry instance (DependencyTelemetry, EventTelemetry) and modify its Context property. Then pass in the telemetry instance to the corresponding Track method on TelemetryClient (TrackDependency(), TrackEvent(), TrackMetric()). This method ensures that the telemetry has the correct correlation details for the current function invocation.
Testing functions
The following articles show how to run an in-process C# class library function locally for testing purposes:
Environment variables
To get an environment variable or an app setting value, use System.Environment.GetEnvironmentVariable, as shown in the following code example:
public static class EnvironmentVariablesExample
{
[FunctionName("GetEnvironmentVariables")]
public static void Run([TimerTrigger("0 */5 * * * *")]TimerInfo myTimer, ILogger log)
{
log.LogInformation($"C# Timer trigger function executed at: {DateTime.Now}");
log.LogInformation(GetEnvironmentVariable("AzureWebJobsStorage"));
log.LogInformation(GetEnvironmentVariable("WEBSITE_SITE_NAME"));
}
private static string GetEnvironmentVariable(string name)
{
return name + ": " +
System.Environment.GetEnvironmentVariable(name, EnvironmentVariableTarget.Process);
}
}
App settings can be read from environment variables both when developing locally and when running in Azure. When developing locally, app settings come from the Values collection in the local.settings.json file. In both environments, local and Azure, GetEnvironmentVariable("<app setting name>") retrieves the value of the named app setting. For instance, when you're running locally, "My Site Name" would be returned if your local.settings.json file contains { "Values": { "WEBSITE_SITE_NAME": "My Site Name" } }.
The System.Configuration.ConfigurationManager.AppSettings property is an alternative API for getting app setting values, but we recommend that you use GetEnvironmentVariable as shown here.
Binding at runtime
In C# and other .NET languages, you can use an imperative binding pattern, as opposed to the declarative bindings in attributes. Imperative binding is useful when binding parameters need to be computed at runtime rather than design time. With this pattern, you can bind to supported input and output bindings on-the-fly in your function code.
Define an imperative binding as follows:
Do not include an attribute in the function signature for your desired imperative bindings.
Pass in an input parameter
Binder binderorIBinder binder.Use the following C# pattern to perform the data binding.
using (var output = await binder.BindAsync<T>(new BindingTypeAttribute(...))) { ... }BindingTypeAttributeis the .NET attribute that defines your binding, andTis an input or output type that's supported by that binding type.Tcan't be anoutparameter type (such asout JObject). For example, the Mobile Apps table output binding supports six output types, but you can only use ICollector<T> or IAsyncCollector<T> with imperative binding.
Single attribute example
The following example code creates a Storage blob output binding with blob path that's defined at run time, then writes a string to the blob.
public static class IBinderExample
{
[FunctionName("CreateBlobUsingBinder")]
public static void Run(
[QueueTrigger("myqueue-items-source-4")] string myQueueItem,
IBinder binder,
ILogger log)
{
log.LogInformation($"CreateBlobUsingBinder function processed: {myQueueItem}");
using (var writer = binder.Bind<TextWriter>(new BlobAttribute(
$"samples-output/{myQueueItem}", FileAccess.Write)))
{
writer.Write("Hello World!");
};
}
}
BlobAttribute defines the Storage blob input or output binding, and TextWriter is a supported output binding type.
Multiple attributes example
The preceding example gets the app setting for the function app's main Storage account connection string (which is AzureWebJobsStorage). You can specify a custom app setting to use for the Storage account by adding the
StorageAccountAttribute
and passing the attribute array into BindAsync<T>(). Use a Binder parameter, not IBinder. For example:
public static class IBinderExampleMultipleAttributes
{
[FunctionName("CreateBlobInDifferentStorageAccount")]
public async static Task RunAsync(
[QueueTrigger("myqueue-items-source-binder2")] string myQueueItem,
Binder binder,
ILogger log)
{
log.LogInformation($"CreateBlobInDifferentStorageAccount function processed: {myQueueItem}");
var attributes = new Attribute[]
{
new BlobAttribute($"samples-output/{myQueueItem}", FileAccess.Write),
new StorageAccountAttribute("MyStorageAccount")
};
using (var writer = await binder.BindAsync<TextWriter>(attributes))
{
await writer.WriteAsync("Hello World!!");
}
}
}
Triggers and bindings
This table shows the bindings that are supported in the major versions of the Azure Functions runtime:
| Type | 1.x1 | 2.x and higher2 | Trigger | Input | Output |
|---|---|---|---|---|---|
| Blob storage | ✔ | ✔ | ✔ | ✔ | ✔ |
| Azure Cosmos DB | ✔ | ✔ | ✔ | ✔ | ✔ |
| Azure Data Explorer | ✔ | ✔ | ✔ | ||
| Azure SQL | ✔ | ✔ | ✔ | ✔ | |
| Dapr4 | ✔ | ✔ | ✔ | ✔ | |
| Event Grid | ✔ | ✔ | ✔ | ✔ | |
| Event Hubs | ✔ | ✔ | ✔ | ✔ | |
| HTTP & webhooks | ✔ | ✔ | ✔ | ✔ | |
| IoT Hub | ✔ | ✔ | ✔ | ||
| Kafka3 | ✔ | ✔ | ✔ | ||
| Mobile Apps | ✔ | ✔ | ✔ | ||
| Notification Hubs | ✔ | ✔ | |||
| Queue storage | ✔ | ✔ | ✔ | ✔ | |
| Redis | ✔ | ✔ | |||
| RabbitMQ3 | ✔ | ✔ | ✔ | ||
| SendGrid | ✔ | ✔ | ✔ | ||
| Service Bus | ✔ | ✔ | ✔ | ✔ | |
| SignalR | ✔ | ✔ | ✔ | ✔ | |
| Table storage | ✔ | ✔ | ✔ | ✔ | |
| Timer | ✔ | ✔ | ✔ | ||
| Twilio | ✔ | ✔ | ✔ |
Notes:
- Support will end for version 1.x of the Azure Functions runtime on September 14, 2026. We highly recommend that you migrate your apps to version 4.x for full support.
- Starting with the version 2.x runtime, all bindings except HTTP and Timer must be registered. See Register binding extensions.
- Triggers aren't supported in the Consumption plan. Requires runtime-driven triggers.
- Supported in Kubernetes, IoT Edge, and other self-hosted modes only.