Tags: Multi-Datacenter Replication

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 […]

Organizations today are moving their data and their data processing workloads to the cloud, and often into multiple clouds. Hybrid cloud solutions, cloud-native application architectures, and event streaming systems—especially in […]

Single-cluster deployments of Apache Kafka® are rare. Most medium to large deployments employ more than one Kafka cluster, and even the smallest use cases include development, testing, and production clusters. […]

Enterprises run modern data systems and services across multiple cloud providers, private clouds and on-prem multi-datacenter deployments. Instead of having many point-to-point connections between sites, the Confluent Platform provides an […]

Part 1 of this blog series introduced a self-paced tutorial for developers who are just getting started with stream processing. The hands-on tutorial introduced the basics of the Kafka Streams […]

Imagine: Disaster strikes—catastrophic hardware failure, software failure, power outage, denial of service attack or some other event causes one datacenter with an Apache Kafka® cluster to completely fail. Yet Kafka […]

Datacenter downtime and data loss can result in businesses losing a vast amount of revenue or entirely halting operations. To minimize the downtime and data loss resulting from a disaster, […]

One of the most common pain points we hear is around managing the flow and placement of data between datacenters. Almost every Apache Kafka user eventually ends up with clusters […]

Today, we are excited to announce the release of Confluent 3.1, the only stream processing platform built entirely on Apache Kafka. At Confluent, our vision is to not only ship […]