Apache Kafka is well-positioned to support different use cases including unified batch and stream processing, ML training with historic data or recomputing results with streaming data when application logic changes. These use cases often require storing data for several weeks, months, or even years. Data is retained in the Kafka cluster as long as required by configuring the retention policy. However, retaining data in a Kafka cluster can become expensive because storage and compute are tightly coupled in a cluster. In this session, we will discuss how you can use MSK tiered storage which brings a virtually unlimited and low-cost storage tier for Amazon MSK.
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