Nouveau dans Confluent Cloud : rendre les données et les pipelines accessibles pour un streaming prêt pour l’IA | En savoir plus
Learn how to migrate to Confluent Cloud in hours using Confluent’s open source Kafka Copy Paste tool. Get an in-depth introduction to the KCP tool and a walk-through of the four steps of migrating from MSK to Confluent Cloud using the tool.
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.
Explore new AI features and AI tools: support for IBM Granite Time Series models and TimesFM models (EA), enhanced Real-Time Context Engine experience, new Agent Skills, Confluent Copilot
This is the eighth and final month of Project Metamorphosis: an initiative that brings the best characteristics of modern cloud-native data systems to the Apache Kafka® ecosystem, served from Confluent […]
Due to the distributed architecture of Apache Kafka®, the operational burden of managing it can quickly become a limiting factor on adoption and developer agility. For this reason, it is […]
As a clothing retailer with more than 1.5 million customers worldwide, Boden is always looking to capitalise on business moments to drive sales. For example, when the Duchess of Cambridge […]
Building data pipelines isn’t always straightforward. The gap between the shiny “hello world” examples of demos and the gritty reality of messy data and imperfect formats is sometimes all too […]
Software engineering memes are in vogue, and nothing is more fashionable than joking about how complicated distributed systems can be. Despite the ribbing, many people adopt them. Why? Distributed systems […]
This blog post presents the use cases and architectures of REST APIs and Confluent REST Proxy, and explores a new management API and improved integrations into Confluent Server and Confluent […]
It’s almost KubeCon! Let’s talk about the state of cloud-native Apache Kafka® and other distributed systems on Kubernetes. Over the last decade, our industry has seen the rise of container […]
Asynchronous boundaries. Frameworks. Configuring frameworks. Apache Kafka®. All of these share one thing in common: complexity in testing. Now imagine them combined—it gets much harder. This is the final blog […]
Have you ever had to write a program that needed to handle any data payload that could be thrown at you? If so, did you always have to update the […]
The rise of the cloud introduced a focus on rapid iteration and agility that is founded on specialization. If you are an application developer, you know your applications better than […]
Event modeling has always been a pain point in organizations. From figuring out the standard format of your schemas, processing said data models effectively, and finally testing before you deploy […]
Note: Please see the blog post Introducing Cluster RBAC, Audit Logs, and BYOK for Enterprise-Grade Security for the latest updates.
“Persistent” queries have historically formed the basis of ksqlDB applications, which continuously transform, enrich, aggregate, materialize, and join your Apache Kafka® data using a familiar SQL interface. ksqlDB continuously executes […]
A fundamental challenge with today’s “data explosion” is finding the best answer to the question, “So where do I put my data?” while avoiding the longer-term problem of data warehouses, […]