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We will describe the architecture of a personalization platform that captures customer profiles and behavioral data. A Cassandra cluster is used as an intermediate storage backend to replicate updates to profile records and timeline events across multiple data-centers. A caching tier serves up the user data and provides a real-time execution environment where predictive models can calculate propensities or update category histograms, etc.. We delve into metrics that are used to track replication performance and data freshness. We also discuss applications and features like user badges that are powered by this new P13N platform.