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Technology
Queues for Apache Kafka® Is Here: Your Guide to Getting Started in Confluent
Confluent announces the General Availability of Queues for Kafka on Confluent Cloud and Confluent Platform with Apache Kafka 4.2. This production-ready feature brings native queue semantics to Kafka through KIP-932, enabling organizations to consolidate streaming and queuing infrastructure while...
AI Tools for Builders — Confluent's MCP Server & Agent Skills
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.
New in Confluent Intelligence: Real-Time Context Engine Upgrade, New Model Support, ML Functions, and More
Explore new Confluent Intelligence features: enhanced querying with Real-Time Context Engine, PII detection, sentiment analysis, and support for TimesFM, Anthropic, and Fireworks AI models.
The Importance of Distributed Tracing for Apache Kafka Based Applications
Apache Kafka® based applications stand out for their ability to decouple producers and consumers using an event log as an intermediate layer. One result of this is that producers and […]
Kafka Streams’ Take on Watermarks and Triggers
Back in May 2017, we laid out why we believe that Kafka Streams is better off without a concept of watermarks or triggers, and instead opts for a continuous refinement […]
SOA vs. EDA: Is Not Life Simply a Series of Events?
When should you use an API? When should you use an event? Most contemporary software architectures are some mix of these two approaches. I will attempt to articulate in layman’s […]
Kafka Connect Deep Dive – Error Handling and Dead Letter Queues
Kafka Connect is part of Apache Kafka® and is a powerful framework for building streaming pipelines between Kafka and other technologies. It can be used for streaming data into Kafka […]
Spring for Apache Kafka Deep Dive – Part 2: Apache Kafka and Spring Cloud Stream
On the heels of part 1 in this blog series, Spring for Apache Kafka – Part 1: Error Handling, Message Conversion and Transaction Support, here in part 2 we’ll focus […]
CloudBank’s Journey from Mainframe to Streaming with Confluent Cloud
Cloud is one of the key drivers for innovation. Innovative companies experiment with data to come up with something useful. It usually starts with the opening of a firehose that […]
All About the Kafka Connect Neo4j Sink Plugin
Only a little more than one month after the first release, we are happy to announce another milestone for our Kafka integration. Today, you can grab the Kafka Connect Neo4j […]
Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless
With serverless being all the rage, it brings with it a tidal change of innovation. Given that it is at a relatively early stage, developers are still trying to grok […]
Spring for Apache Kafka Deep Dive – Part 1: Error Handling, Message Conversion and Transaction Support
Following on from How to Work with Apache Kafka in Your Spring Boot Application, which shows how to get started with Spring Boot and Apache Kafka®, here we’ll dig a […]
Improving Stream Data Quality with Protobuf Schema Validation
The requirements for fast and reliable data pipelines are growing quickly at Deliveroo as the business continues to grow and innovate. We have delivered an event streaming platform which gives […]
Sysmon Security Event Processing in Real Time with KSQL and HELK
During a recent talk titled Hunters ATT&CKing with the Right Data, which I presented with my brother Jose Luis Rodriguez at ATT&CKcon, we talked about the importance of documenting and […]
Journey to Event Driven – Part 2: Programming Models for the Event-Driven Architecture
Part 1 of our series on event-driven architecture discussed why you need to embrace event-first thinking, while this article builds a rationale for different styles of event-driven architectures and compares […]
Kafka Connect Deep Dive – JDBC Source Connector
One of the most common integrations that people want to do with Apache Kafka® is getting data in from a database. That is because relational databases are a rich source […]
Machine Learning with Python, Jupyter, KSQL and TensorFlow
Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine […]