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Change data capture is a popular method to connect database tables to data streams, but it comes with drawbacks. The next evolution of the CDC pattern, first-class data products, provide resilient pipelines that support both real-time and batch processing while isolating upstream systems...
Learn how the latest innovations in Kora enable us to introduce new Confluent Cloud Freight clusters, which can save you up to 90% at GBps+ scale. Confluent Cloud Freight clusters are now available in Early Access.
Learn how to contribute to open source Apache Kafka by writing Kafka Improvement Proposals (KIPs) that solve problems and add features! Read on for real examples.
Learn what windowing is in Kafka Streams and get comfortable with the differences between the main types.
Apache Kafka 3.4 includes early access to ZooKeeper to KRaft migrations, enabling existing Kafka clusters to migrate to KRaft mode and gain scalability and resiliency benefits. Additionally, 3.4 includes several updates to Kafka Core, Streams, Connect, and more.
Announcing the latest updates to Confluent’s cloud-native data streaming platform, centralized identity management, enhanced RBAC, Client Quotas, and more.
Confluent is pleased to announce that the Confluent CLI—the leading command-line tool for managing enterprise Kafka deployments and modern data flow—is now source available under the Confluent Community License.
Building data streaming applications, and growing them beyond a single team is challenging. Data silos develop easily and can be difficult to solve. The tools provided by Confluent’s Stream Governance platform can help break down those walls and make your data accessible to those who need it.
Change data capture (CDC) converts all the changes that occur inside your database into events and publishes them to an event stream. You can then use these events to power analytics, drive operational use cases, hydrate databases, and more. The pattern is enjoying wider adoption than ever before.
In this post, we introduce how to use .NET Kafka clients along with the Task Parallel Library to build a robust, high-throughput event streaming application...
Learn what a Kafka consumer group ID is and how assigning one to Kafka consumers during configuration helps with detecting new data, work sharing, and data recovery.
Self-managing connectors come with major time and resource challenges and taking on unnecessary risks of downtime that shift your team’s focus away from working on more strategic projects and innovations...
If you’ve used Kafka for any amount of time you’ve likely heard about connections; the most common place that they come up is in regard to clients. Sure, producer and consumer clients connect to the cluster to do their jobs, but it doesn’t stop there. Nearly all interactions across a cluster...
Setting up proactive, synthetic monitoring is critical for complex, distributed systems like Apache Kafka®, especially when deployed on Kubernetes and where the end-user experience is concerned, and is paramount for healthy real-time data pipelines...
This Thanksgiving-themed blog post walks through a brand new stream processing use case recipe for analyzing survey responses in real-time and gives ideas for how to spice it up and make the recipe your own!
The call for papers for Kafka Summit London 2023 has opened, and we’re looking to hear about your experiences using and working with Kafka. Every great technical talk starts with an experience. If you’re stuck looking for ideas on what to talk about, write what you know...
Confluent Cloud hosts Apache Kafka®, Kafka Connect, ksqlDB, and more. Here’s how we re-architected the system for a new deployment platform with zero downtime...