Optimize Costs & Scale Streaming Applications with Virtually Unlimited Storage from AWS Services

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 you will learn how AWS streaming data services can power your streaming applications that can scale to virtually unlimited storage with Tiered Storage. Discover how AWS services collaborate to address diverse event driven architectures, Change Data Capture (CDC) applications and real-time analytics use cases. Unleash the potential of AWS’ cost efficient storage tiering for long term data retention, agile decision-making and proactive data strategies.

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