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  1. DZone
  2. Data Engineering
  3. Big Data
  4. Architectures for Distributed, Hybrid, Edge, and Global Apache Kafka

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Architectures for Distributed, Hybrid, Edge, and Global Apache Kafka

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Architectures for Distributed, Hybrid, Edge, and Global Apache Kafka

Learn about several scenarios that may require multi-cluster solutions and see real-world examples with their specific requirements and trade-offs.

This article was provided by and does not represent the editorial content of DZone.

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Kai Wähner user avatar
Kai Wähner
DZone Core CORE ·
Mar. 19, 20 ·
Free Resource
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Multi-cluster and cross-data center deployments of Apache Kafka have become the norm rather than an exception. Learn about several scenarios that may require multi-cluster solutions and see real-world examples with their specific requirements and trade-offs, including disaster recovery, aggregation for analytics, cloud migration, mission-critical stretched deployments and global Kafka.

kafka

Key Takeaways for Multi Data Center Kafka Architectures

  • In many scenarios, one Kafka cluster is not enough. Understand different architectures and alternatives for multi-cluster deployments.
  • Zero data loss and high availability are two key requirements. Understand how to realize this, including trade-offs.
  • Learn about features and limitations of Kafka for multi-cluster deployments- Global Kafka and mission-critical multi-cluster deployments with zero data loss and high availability became the normal, not an exception.
  • Learn about architectures like stretched cluster, hybrid integration and fully-managed serverless Kafka in the cloud (using Confluent Cloud), and tools like MirrorMaker 2, Confluent Replicator, Multi-Region Clusters (MRP), Global Kafka, and more.

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Architecture patterns for distributed, hybrid, edge and global Apache Kafka deployments from Kai Wähner.

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