Introducing Streamhouse: the open data architecture for AI | Learn More
New industry initiative establishes an open category for data architectures that power real-time applications and AI agents
Learn how to migrate to Confluent Cloud in hours using Confluent’s open source Kafka Copy Paste tool. Get an in-depth introduction to the KCP tool and a walk-through of the four steps of migrating from MSK to Confluent Cloud using the tool.
Confluent's AI developer tools are now GA: an open-source local MCP server, a managed MCP server, and Agent Skills. Together they give AI coding assistants direct access to your streaming platform — the tools to act on it and the domain knowledge to build correctly.
Pandora began adoption of Apache Kafka® in 2016 to orient its infrastructure around real-time stream processing analytics. As a data-driven company, we have a several thousand node Hadoop clusters with hundreds of Hive tables critical to Pandora’s operational and reporting success...
Note: The blog post Ensure Data Quality and Data Evolvability with a Secured Schema Registry contains more recent information. If you use Apache Kafka to integrate and decouple different data […]
Big news this month! First and foremost, Confluent Platform 3.2.0 with Apache Kafka® 0.10.2.0 was released! Read about the new features, check out all 200 bug fixes and performance improvements […]
We’re excited to announce the release of Confluent 3.2, our enterprise streaming platform built on Apache Kafka. At Confluent, our vision is to provide a comprehensive, enterprise-ready streaming platform that […]
At the end of 2016 we conducted a survey of the Apache Kafka® community regarding their use of Kafka clients (the producers and consumers used with Kafka) and their priorities […]
As always, we bring you news, updates and recommended content from the hectic world of Apache Kafka® and stream processing. Sometimes it seems that in Apache Kafka every improvement is […]
Last November, we released Confluent 3.1, with new connectors, clients, and Enterprise features. Today, we’re pleased to announce Confluent 3.1.2, a patch release which incorporates the latest stable version of […]
Seems that many engineers have “Learn Kafka” on their new year resolution list. This isn’t very surprising. Apache Kafka is a popular technology with many use-cases. Armed with basic Kafka […]
Happy 2017! Wishing you a wonderful year full of fast and scalable data streams. Many things have happened since we last shared the state of Apache Kafka® and the streams […]
If you were to stumble upon the whole microservices thing, without any prior context, you’d be forgiven for thinking it a little strange. Taking an application and splitting it into fragments, […]
One of the most common pain points we hear is around managing the flow and placement of data between datacenters. Almost every Apache Kafka user eventually ends up with clusters […]
This month saw the proposal of a few KIPs which will have a big impact on Apache Kafka’s semantics as well as Kafka’s operability. KIP-95 : Incremental Batch Processing for […]
This year, we were pleased to host the inaugural Kafka Summit, the first global summit for the Apache Kafka community. Kafka Summit 2016 contributed valuable content to help Kafka users […]
Confluent and Microsoft are pleased to announce the successful integration of Confluent Platform into Microsoft’s Azure Marketplace. Users can now rapidly deploy a complete Confluent Platform cluster with the click […]