Apache Kafka bindings for Azure Functions overview

The Kafka extension for Azure Functions lets you write values out to Apache Kafka topics by using an output binding. You can also use a trigger to invoke your functions in response to messages in Kafka topics.

Important

Kafka bindings are only available for Functions on the Elastic Premium Plan and Dedicated (App Service) plan. They are only supported on version 3.x and later version of the Functions runtime.

Action	Type
Run a function based on a new Kafka event.	Trigger
Write to the Kafka event stream.	Output binding

Install extension

The extension NuGet package you install depends on the C# mode you're using in your function app:

Isolated worker model

Functions execute in an isolated C# worker process. To learn more, see Guide for running C# Azure Functions in an isolated worker process.

Add the extension to your project by installing this NuGet package.

In-process model

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.

Functions execute in the same process as the Functions host. To learn more, see Develop C# class library functions using Azure Functions.

Add the extension to your project by installing this NuGet package.

Install bundle

The Kafka extension is part of an extension bundle, which is specified in your host.json project file. When you create a project that targets Functions version 3.x or later, you should already have this bundle installed. To learn more, see extension bundle.

Enable runtime scaling

To allow your functions to scale properly on the Premium plan when using Kafka triggers and bindings, you need to enable runtime scale monitoring.

Azure portal

In the Azure portal, in your function app, choose Configuration and on the Function runtime settings tab turn Runtime scale monitoring to On.

Azure CLI

Use the following Azure CLI command to enable runtime scale monitoring:

az resource update -g <RESOURCE_GROUP> -n <FUNCTION_APP_NAME>/config/web --set properties.functionsRuntimeScaleMonitoringEnabled=1 --resource-type Microsoft.Web/sites

host.json settings

This section describes the configuration settings available for this binding in versions 3.x and higher. Settings in the host.json file apply to all functions in a function app instance. For more information about function app configuration settings in versions 3.x and later versions, see the host.json reference for Azure Functions.

{
    "version": "2.0",
    "extensions": {
        "kafka": {
            "maxBatchSize": 64,
            "SubscriberIntervalInSeconds": 1,
            "ExecutorChannelCapacity": 1,
            "ChannelFullRetryIntervalInMs": 50
        }
    }
}

Property	Default	Type	Description
ChannelFullRetryIntervalInMs	50	Trigger	Defines the subscriber retry interval, in milliseconds, used when attempting to add items to an at-capacity channel.
ExecutorChannelCapacity	1	Both	Defines the channel message capacity. Once capacity is reached, the Kafka subscriber pauses until the function catches up.
MaxBatchSize	64	Trigger	Maximum batch size when calling a Kafka triggered function.
SubscriberIntervalInSeconds	1	Trigger	Defines the minimum frequency incoming messages are executed, per function in seconds. Only when the message volume is less than MaxBatchSize / SubscriberIntervalInSeconds

The following properties, which are inherited from the Apache Kafka C/C++ client library, are also supported in the kafka section of host.json, for either triggers or both output bindings and triggers:

Property	Applies to	librdkafka equivalent
AutoCommitIntervalMs	Trigger	auto.commit.interval.ms
AutoOffsetReset	Trigger	auto.offset.reset
FetchMaxBytes	Trigger	fetch.max.bytes
LibkafkaDebug	Both	debug
MaxPartitionFetchBytes	Trigger	max.partition.fetch.bytes
MaxPollIntervalMs	Trigger	max.poll.interval.ms
MetadataMaxAgeMs	Both	metadata.max.age.ms
QueuedMinMessages	Trigger	queued.min.messages
QueuedMaxMessagesKbytes	Trigger	queued.max.messages.kbytes
ReconnectBackoffMs	Trigger	reconnect.backoff.max.ms
ReconnectBackoffMaxMs	Trigger	reconnect.backoff.max.ms
SessionTimeoutMs	Trigger	session.timeout.ms
SocketKeepaliveEnable	Both	socket.keepalive.enable
StatisticsIntervalMs	Trigger	statistics.interval.ms

Next steps

• Run a function from an Apache Kafka event stream