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.
Shift Left: Headless Data Architecture, Part 2
Building a headless data architecture requires us to identify the work we’re already doing deep inside our data analytics plane, and shift it to the left. Learn the specifics in this blog.
Announcing the Confluent for Startups AI Accelerator Program: Empowering the First Generation of Real-Time AI Startups
The Confluent for Startups AI Accelerator Program is a 10-week virtual initiative designed to support early-stage AI startups building real-time, data-driven applications. Participants will gain early access to Confluent’s cutting-edge technology, one-on-one mentorship, marketing exposure, and...
Join the Ultimate AWS GameDay Challenge with Confluent
Imagine competing in a high-stakes, gamified environment where you're tasked with solving real-world data challenges, all while exploring AWS and Confluent services hands-on. Welcome to AWS GameDay—an experience like no other.
Shift Left: Headless Data Architecture, Part 1
A headless data architecture means no longer having to coordinate multiple copies of data, and being free to use whatever processing or query engine is most suitable for the job. This blog details how it works.
Preparing the Consumer Fetch: Kafka Producer and Consumer Internals, Part 3
In this third installment of a blog series examining Kafka Producer and Consumer Internals, we switch our attention to Kafka consumer clients, examining how consumers interact with brokers, coordinate their partitions, and send requests to read data from Kafka topics.
Confluent Cloud Is Now 100% KRaft and You Should Be Too
Confluent has helped thousands migrate to KRaft, Kafka’s new consensus protocol that replaces ZooKeeper for metadata management. Kafka users can migrate to KRaft quickly and with ease by using automated tools like Confluent for Kubernetes (CFK) and Ansible Playbooks.
APAC Data Streaming Deep Dive: Unlocking Business Agility and Innovation Across the Region
This blog post announces the launch of the APAC deep dive of the data streaming report.
Shift Left: Bad Data in Event Streams, Part 2
Event design plays a big role in your ability to fix bad data in your streams. But if you’ve wrecked a stream with bad data (i.e., it’s unavoidably contaminated), you'll need to employ a "rewind, rebuild, and retry" strategy.
Spring Into Confluent Cloud with Kotlin – Part 2: Kafka Streams
In this edition, we’ll have a look at creating Kafka Streams topologies—exploring the dependency injection and design principles with Spring Framework, while also highlighting some syntactic sugar of Kotlin that makes for more concise and legible topologies.
Enhancing Security with IAM Roles in Confluent Managed Connectors
This blog post talks about Confluent’s newest enhancement to their fully managed connectors: the ability to assume IAM roles.
Shift Left: Bad Data in Event Streams, Part 1
At a high level, bad data is data that doesn’t conform to what is expected, and it can cause serious issues and outages for all downstream data users. This blog looks at how bad data may come to be, and how we can deal with it when it comes to event streams.
Your Guide to the Apache Flink® Table API: An In-Depth Exploration
The blog post provides a comprehensive overview of the Flink Table API, demonstrating how it enables developers to express complex data processing logic using Java or Python in a user-friendly manner. It also includes practical examples and guidance, making it a valuable resource for anyone...
Allure of Data in Motion Inspires Move to Confluent’s Professional Services Team
Read our latest Confluent Champion post to learn what motivated Nadine Capelle, staff solutions architect in Professional Services, to join the world of data streaming.