Confluent Blog

I previously showed how to install and set up Apache Kafka® on Windows in minutes by using the Windows Subsystem for Linux 2 (WSL 2). From there, it’s only a

Most companies who have adopted event streaming are running multiple Apache Kafka® environments. For example, they may use different Kafka clusters for testing vs. production or for different use cases.

Persisting data in multiple regions has become crucial for modern businesses: They need their mission-critical data to be protected from accidents and disasters. They can achieve this goal by running

How do you process IoT data, change data capture (CDC) data, or streaming data from sensors, applications, and sources in real time? Apache Kafka® and Apache Spark® are widely adopted

At Zendesk, Apache Kafka® is one of our foundational services for distributing events among different internal systems. We have pods, which can be thought of as isolated cloud environments where

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

Apache Kafka® scales well. A Kafka cluster can grow to tens or hundreds of brokers and easily sustain tens of GB per second of read and write traffic. But scaling

With the release of Confluent Platform 6.0 comes a preview of Confluent Cluster Linking available to self-managed customers and in Confluent Cloud for our early access partners. Cluster Linking is

Near-real-time insights have become a de facto requirement for Azure use cases involving scalable log analytics, time series analytics, and IoT/telemetry analytics. Azure Data Explorer (also called Kusto) is the

Confluent Operator allows you to deploy and manage Confluent Platform as a cloud-native, stateful container application on Kubernetes and OpenShift. The automation provided by Kubernetes, Operator, and Helm greatly simplifies