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Showing content from https://learn.microsoft.com/en-us/azure/azure-functions/scripts/../functions-bindings-kafka below:

Apache Kafka bindings for Azure Functions

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.

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:

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.

In the Azure portal, in your function app, select Configuration.
On the Function runtime settings tab, for Runtime Scale Monitoring, select On.

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

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