Amazon Personalize now supports Kafka Sink connector to ingest real-time data with ease
Amazon Personalize has launched a new open source Amazon Personalize Kafka Sink connector that makes it easy to stream data in real-time for use in Amazon Personalize. Amazon Personalize enables developers to improve customer engagement through personalized product and content recommendations – no ML expertise required. Amazon Personalize uses data provided by customers to train custom models on their behalf. With this launch, customers can readily ingest their data from Apache Kafka clusters and call the Amazon Personalize-specific APIs to enable real-time data steaming, without the need for custom code. This makes it faster and easier to bring real-time data to Amazon Personalize for those using Apache Kafka.
Amazon Personalize has launched a new open source Amazon Personalize Kafka Sink connector that makes it easy to stream data in real-time for use in Amazon Personalize. Amazon Personalize enables developers to improve customer engagement through personalized product and content recommendations – no ML expertise required. Amazon Personalize uses data provided by customers to train custom models on their behalf. With this launch, customers can readily ingest their data from Apache Kafka clusters and call the Amazon Personalize-specific APIs to enable real-time data steaming, without the need for custom code. This makes it faster and easier to bring real-time data to Amazon Personalize for those using Apache Kafka.
Getting started with the Amazon Personalize Kafka Sink connector is easy. Simply download and package the open source plugin code, then configure the plugin directory path, and create the connector using Connect Rest API. If you are using Amazon Managed Streaming for Apache Kafka, refer to their developer guide to create a custom connector.
Amazon Personalize enables you to personalize your website, app, ads, emails, and more, using the same machine learning technology used by Amazon, without requiring any prior machine learning experience. To get started with Amazon Personalize, visit our documentation.