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Kafka

What is a Kafka Consumer and How does it work?

Now that your data is inside your Kafka cluster, how do you get it out? In this video, Dan Weston covers the basics of Kafka Consumers: what consumers are, how they get your data flowing, and best practices for configuring consumers in a real-time data streaming system. You will also learn about offsets, consumer groups, and partition assignment.

#12 Kafka Live Stream | HTTP Sink Connector & Business Automation with Make

See the new Lenses Kafka to HTTP Sink Connector in action with Lenses.io and @itsmake. In this 30 minute session, we show you how to trigger APIs that automate your business processes: a message in Kafka calls a Make workflow, then triggering an automation in Salesforce.

What is the Listen to Yourself Pattern? | Designing Event-Driven Microservices

The Listen to Yourself pattern is implemented by having a microservice emit an event to a platform such as Apache Kafka, and then consuming its own events to perform internal updates. It can be used as a solution to the dual-write problem since it separates Kafka and database writes into different processes. However, it also provides added benefits because it allows microservices to respond quickly to requests by deferring processing to a later time.

Using Streams Replication Manager Prefixless Replication for Kafka Topic Aggregation

Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. For example, if there are separate clusters, and there are topics with the same purpose in the different clusters, then it is useful to aggregate the content into one topic.

Introducing Apache Kafka 3.7

We are proud to announce the release of Apache Kafka® 3.7.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features. For a full list of changes, be sure to check the release notes. See the Upgrading to 3.7.0 from any version 0.8.x through 3.6.x section in the documentation for the list of notable changes and detailed upgrade steps.

Apache Kafka 3.7: Official Docker Image and Improved Client Monitoring

Apache Kafka® 3.7 is here! On behalf of the Kafka community, Danica Fine highlights key release updates, with KIPs from Kafka Core, Kafka Streams, and Kafka Connect. Kafka Core: Kafka Streams: Kafka Connect: Many more KIPs are a part of this release. See the blog post for more details.