Kafka in the Cloud: Why it’s 10x better with Confluent | Find out more
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...
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.
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.
Day 1 of the event, summarized for your convenience. They say you never forget your first Kafka Summit. Mine was in New York City in 2017, and it had, what, […]
Go from zero to production on Apache Kafka® without talking to sales reps or building infrastructure Apache Kafka is the standard for event-driven applications. But it’s not without its challenges, […]
Robust data governance support through Schema Validation on write is now supported in Confluent Platform 5.4. Schema Validation enables the broker to verify that data produced to an Apache Kafka® […]
In the early days, many companies simply used Apache Kafka® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. The significant difference […]
In 2011, Marc Andressen wrote an article called Why Software is Eating the World. The central idea is that any process that can be moved into software, will be. This […]
There is a coming and a going / A parting and often no—meeting again. —Franz Kafka, 1897 Load balancing and scheduling are at the heart of every distributed system, and […]
Kafka Summit San Francisco is just one week away. Conferences can be busy affairs, so here are some tips on getting the most out of your time there. Plan Go […]
As a distributed system for collecting, storing, and processing data at scale, Apache Kafka® comes with its own deployment complexities. Luckily for on-premises scenarios, a myriad of deployment options are […]
When people ask me the very top-level question “why do people use Kafka,” I usually lead with the story in my last post, where I talked about how Apache Kafka® […]
Running a single Apache Kafka® cluster across multiple datacenters (DCs) is a common, yet somewhat taboo architecture. This architecture, referred to as a stretch cluster, provides several operational benefits and […]
For me, and I think for you, technology is cool by itself. When you first learn how consistent hashing works, it’s fun. When you finally understand log-structured merge trees, it’s […]
First, what is event sourcing? Here’s an example. Consider your bank account: viewing it online, the first thing you notice is often the current balance. How many of us drill […]
TL;DR 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 I will […]
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 […]