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Custom Container with Kafka extension

You can use the Kafka extension with a custom container. If you don't know about the custom container, you can refer to Create a function on Linux using a custom container.

This sample is for java. However, you can pick any languages. You can follow the step of the Create a function on Linux using a custom container with additional steps only for the Kafka extensions.

Kafka extension additional steps

  1. Install the Kafka extension
  2. Set the LD_LIBRARY_PATH

For the 1. and 2., the step is included on the Dockerfile.

Quick Start

Build, Test, Publish the Docker container

Refer to the Dockerfile. The Dockerfile execute these steps.

NOTE: You need to use azure-functions-java-library 1.4.0+ and azure-functions-maven-plugin 1.6.0+.

  • mvn clean package
  • Install Kafka Extension
  • LD_LIBRARY_PATH as an environment variables

Build

$ docker build --tag {YOUR_DOCKERHUB_NAME}/azurefunctionsimage:v1.0.0 .

Test

This sample is configured for Connecting to Confluent Cloud in Azure. If you want to get simple configuration, refer to the Java sample or Connecting to Confluent Cloud in Azure

If you want to run locally, you need to pass the credentials for the Confluent Cloud. In this sample, I use an Azure Storage Account. Please refer to Create an Azure Storage account.

You can see the log with sending the Kafka event. For the Confluence Cloud, you can use ccloud utility. Otherwise, you can use kafkacat to send the event.

$ docker run -p 8080:80 -it -e "BrokerList={YOUR_CONFLUENT_CLOUD_NAME}.eastus.azure.confluent.cloud:9092" -e ConfluentCloudUsername={YOUR_CONFLUENT_CLOUD_USERNAME} -e ConfluentCloudPassword={YOUR_CONFLUENT_CLOUD_PASSWORD} -e AzureWebJobsStorage="{YOUR_STORAGE_ACCOUNT_CONNECTION_STRING}" -e FUNCTIONS_WORKER_RUNTIME=java tsuyoshiushio/azurefunctionsimage:v1.0.0

Push the container

$ docker login
$ docker push docker push tsuyoshiushio/azurefunctionsimage:v1.0.0

Create and Configure Linux Premium Function App

Create a Linux based Premium Function. Follow the step of Create supporting Azure resources for your function and Create and configure a function app on Azure with the image.

These steps create a Premium Function App and set the container image on the Function APp.

Configure the Kafka credentials

Configure the Kafka credentials to the function app.

$ az functionapp config appsettings set --name <app_name> --resource-group <source_group_name> --settings "BrokerList={YOUR_CONFLUENT_CLOUD_NAME}.eastus.azure.confluent.cloud:9092 ConfluentCloudUsername={YOUR_CONFLUENT_CLOUD_USERNAME} ConfluentCloudPassword={YOUR_CONFLUENT_CLOUD_PASSWORD}

NOTE: You don't need LD_LIBRARY_PATH for this scenario. It is already configured on the Dockerfile.