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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 |
The extension NuGet package you install depends on the C# mode you're using in your function app:
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.
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.
To allow your functions to scale properly on the Premium plan when using Kafka triggers and bindings, you need to enable runtime scale monitoring.
In the Azure portal, in your function app, choose Configuration and on the Function runtime settings tab turn Runtime scale monitoring to On.
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 |