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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.

Data Products, Data Contracts, and Change Data Capture

Change data capture (CDC) has long been one of the most popular, reliable, and quickest ways to connect your database tables into data streams. It is a powerful pattern and one of the most common and easiest ways to bootstrap data into Apache Kafka®. But it comes with a relatively significant drawback—it exposes your database’s internal data model to the downstream world.

What is the Event Sourcing Pattern? | Designing Event-Driven Microservices

Event Sourcing is a pattern of storing an object's state as a series of events. Each time the object is updated a new event is written to an append-only log. When the object is loaded from the database, the events are replayed in order, reapplying the necessary changes. The benefit of this approach is that it stores a full history of the object. This can be valuable for debugging, auditing, building new models, and a variety of other situations. It is also a technique that can be used to solve the dual-write problem when working with event-driven architectures.

New with Confluent Platform: Seamless Migration Off ZooKeeper, Arm64 Support, and More

With the increasing importance of real-time data in modern businesses, companies are leveraging distributed streaming platforms to process and analyze data streams in real time. Many companies are also transitioning to the cloud, which is often a gradual process that takes several years and involves incremental stages. During this transition, many companies adopt hybrid cloud architectures, either temporarily or permanently.

How to Use Confluent for Kubernetes to Manage Resources Outside of Kubernetes

Apache Kafka® cluster administrators often need to solve problems like how to onboard new teams, manage resources like topics or connectors, and maintain permission control over these resources. In this post, we will demonstrate how to use Confluent for Kubernetes (CfK) to enable GitOps with a CI/CD pipeline and delegate resource creation to groups of people without distributing admin permission passwords to other people in the organization.

What is the Transactional Outbox Pattern? | Designing Event-Driven Microservices

The transactional outbox pattern leverages database transactions to update a microservice's state and an outbox table. Events in the outbox will be sent to an external messaging platform such as Apache Kafka. This technique is used to overcome the dual-write problem which occurs when you have to write data to two separate systems such as a database and Apache Kafka. The database transactions can be used to ensure atomic writes between the two tables. From there, a separate process can consume the outbox and update the external system as required.