Technology

Get a high-level overview of source connector tuning: What can and cannot be tuned, and tuning methodology for any and all source connectors.

Learn about Confluent Platform 7.5 and its latest key features: enhancing security with SSO for Control Center, improving developer efficacy with Confluent REST Proxy API v3, and improving disaster recovery capabilities with bidirectional Cluster Linking.

Apache Flink can be used for multiple stream processing use cases. In this post we show how developers can use Flink to build real-time applications, run analytical workloads or build real-time pipelines.

Versioned key-value state stores, introduced to Kafka Streams in 3.5, enhance stateful processing capabilities by allowing users to store multiple record versions per key, rather than only the single latest version per key as is the case for existing key-value stores today...

Learn why stream processing is such a critical component of the data streaming stack, why developers are choosing Apache Flink as their stream processing framework of choice, and how to use Flink with Kafka.

Confluent Cloud has chosen Let’s Encrypt as its Certificate Authority and leverages its automation features to spend less time managing certificates and more time building private networking features.

Learn the basics of what an Apache Kafka cluster is and how they work, from brokers to partitions, how they balance load, and how they handle replication, and leader and replica failures.

When developing streaming applications, one crucial aspect that often goes unnoticed is the default partitioning behavior of Java and non-Java producers. This disparity can result in data mismatches and inconsistencies, posing challenges for developers.

Confluent Platform 7.4 now includes SBOMs, which gives customers more transparency and control over their software deployments.

Learn when to consider expanding to multiple Apache Kafka clusters, how to manage the operations for large clusters, and tools and resources for efficient operations.

The term “event” shows up in a lot of different Apache Kafka® arenas. There’s “event-driven design,” “event sourcing,” “designing events,” and “event streaming.” What is an event, and what is the difference between the role an event has to play in each of these contexts?

We are proud to announce the release of Apache Kafka® 3.5.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features.

ChatGPT and data streaming can work together for any company. Learn a basic framework for using GPT-4 and streaming to build a real-world production application.

GitOps can work with policy-as-code systems to provide a true self-service model for managing Confluent resources. Policy-as-code is the practice of permitting or preventing actions based on rules and conditions defined in code. In the context of GitOps for Confluent, suitable policies...