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Stream Processing
Introducing Confluent Private Cloud: Cloud-Level Agility for Your Private Infrastructure
Confluent Private Cloud (CPC) is a new software package that extends Confluent’s cloud-native innovations to your private infrastructure. CPC offers an enhanced broker with up to 10x higher throughput and a new Gateway that provides network isolation and central policy enforcement without client...
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...
New in Confluent Intelligence: A2A, Multivariate Anomaly Detection, Vector Search for Cosmos DB, Amazon S3 Vectors, and More
Explore new Confluent Intelligence features: A2A integration, multivariate anomaly detection, vector search for Cosmos DB and S3 Vectors, Private Link, and MCP support.
Introducing ksqlDB
Today marks a new release of KSQL, one so significant that we’re giving it a new name: ksqlDB. Like KSQL, ksqlDB remains freely available and community licensed, and you can […]
Using Graph Processing for Kafka Streams Visualizations
We know that Apache Kafka® is great when you’re dealing with streams, allowing you to conveniently look at streams as tables. Stream processing engines like ksqlDB furthermore give you the […]
ksqlDB UDFs and UDAFs Made Easy
One of ksqlDB’s most powerful features is allowing users to build their own ksqlDB functions for processing real-time streams of data. These functions can be invoked on individual messages (user-defined […]
Building Shared State Microservices for Distributed Systems Using Kafka Streams
The Kafka Streams API boasts a number of capabilities that make it well suited for maintaining the global state of a distributed system. At Imperva, we took advantage of Kafka […]
KSQL Training for Hands-On Learning
I’ve been using KSQL from Confluent since its first developer preview in 2017. Reading, writing, and transforming data in Apache Kafka® using KSQL is an effective way to rapidly deliver […]
Deploying Kafka Streams and KSQL with Gradle – Part 3: KSQL User-Defined Functions and Kafka Streams
Building off part 1 where we discussed an event streaming architecture that we implemented for a customer using Apache Kafka, KSQL, and Kafka Streams, and part 2 where we discussed […]
Deploying Kafka Streams and KSQL with Gradle – Part 2: Managing KSQL Implementations
In part 1, we discussed an event streaming architecture that we implemented for a customer using Apache Kafka®, KSQL from Confluent, and Kafka Streams. Now in part 2, we’ll discuss […]
Deploying Kafka Streams and KSQL with Gradle – Part 1: Overview and Motivation
Red Pill Analytics was recently engaged by a Fortune 500 e-commerce and wholesale company that is transforming the way they manage inventory. Traditionally, this company has used only a few […]
Optimizing Kafka Streams Applications
With the release of Apache Kafka® 2.1.0, Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. This framework opens the door for various optimization techniques […]
Putting Events in Their Place with Dynamic Routing
Event-driven architecture means just that: It’s all about the events. In a microservices architecture, events drive microservice actions. No event, no shoes, no service. In the most basic scenario, microservices […]
KSQL: What’s New in 5.2
KSQL enables you to write streaming applications expressed purely in SQL. There’s a ton of great new features in 5.2, many of which are a result of requests and support […]
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 […]
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 […]