Multi-Cloud Streaming Data Integration with Confluent and Krake

What this post added

This post details the integration of Confluent Platform with Krake, an open-source multi-cluster workload scheduler, to enable flexible workload placement and improve data processing efficiency in multi-cloud and decentralized datacenter environments. It explains how Confluent Platform provides a global, distributed event streaming fabric as the data plane, while Krake orchestrates applications as the application plane. The post discusses overcoming limitations of traditional cloud computing (legal, technical, energy) through a decentralized approach and highlights the synergy of combining Confluent's global capabilities (Multi-Region Clusters, Cluster Linking) with Krake's scheduling for optimized energy utilization, cost savings, and data sovereignty. It also defines customer-bound and resource-bound workloads in the context of cloud-native applications and distributed streaming.