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Confluent Blog
Data Products, Data Contracts, and Change Data Capture
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...
Introducing Confluent Cloud Freight Clusters
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.
Contributing to Apache Kafka®: How to Write a KIP
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.
Using Apache Kafka Command Line Tools with Confluent Cloud
If you have been using Apache Kafka® for a while, it is likely that you have developed a degree of confidence in the command line tools that come with it. […]
Confluent Raises a $125M Series D Funding Round
I’m excited to announce that Confluent has raised a $125M Series D funding round, led by Sequoia, with participation from our other major investors, Index Ventures and Benchmark. This builds […]
Getting Your Feet Wet with Stream Processing – Part 2: Testing Your Streaming Application
Part 1 of this blog series introduced a self-paced tutorial for developers who are just getting started with stream processing. The hands-on tutorial introduced the basics of the Kafka Streams […]
Getting Your Feet Wet with Stream Processing – Part 1: Tutorial for Developing Streaming Applications
Stream processing is a data processing technology used to collect, store, and manage continuous streams of data as it’s produced or received. Stream processing (also known as event streaming or […]
Easy Ways to Generate Test Data in Kafka
If you’ve already started designing your real-time streaming applications, you may be ready to test against a real Apache Kafka® cluster. To make it easy to get started with your […]
A Developer’s Guide to the Confluent Community License
Last week we announced that we changed the license of some of the components of Confluent Platform from Apache 2.0 to the Confluent Community License. We are really grateful to […]
12 Days of Tech Tips
For the first 12 days of December, Confluent shared a daily tech tip related to managing Apache Kafka® in the cloud. These tips make it easier for you to get […]
License Changes for Confluent Platform
We’re changing the license for some of the components of Confluent Platform from Apache 2.0 to the Confluent Community License. This new license allows you to freely download, modify, and […]
Deep Dive into ksqlDB Deployment Options
The phrase time value of data has been used to demonstrate that the value of captured data diminishes by time. This means that the sooner the data is captured, analyzed […]
Kafka Summit 2019 Call for Papers, Tracks and Office Hours
It might seem a little strange, being the holiday season and still technically 2018, for me to be talking 2019 Kafka Summit events. But as you may already know, the […]
Kafka Streams and KSQL with Minimum Privileges
The principle of least privilege dictates that each user and application will have the minimal privileges required to do their job. When applied to Apache Kafka® and its Streams API, […]
3 Ways to Prepare for Disaster Recovery in Multi-Datacenter Apache Kafka Deployments
Imagine: Disaster strikes—catastrophic hardware failure, software failure, power outage, denial of service attack or some other event causes one datacenter with an Apache Kafka® cluster to completely fail. Yet Kafka […]
Streaming in the Clouds: Where to Start
Only a few years ago, when someone said they had a “cloud-first strategy,” you knew exactly who their new preferred vendor was. These days, however, the story is a lot […]
Using Apache Kafka to Drive Cutting-Edge Machine Learning
Machine learning and the Apache Kafka® ecosystem are a great combination for training and deploying analytic models at scale. I had previously discussed potential use cases and architectures for machine […]