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Processing a lot of data with Kafka means knowing how and when to scale horizontally and vertically. When you’ve exhausted the boundaries of scaling inside a single cluster, replication becomes critical but sometimes standard replication is not enough. New Relic once earned the dubious title of “World’s Largest Kafka Cluster”, and in our journey to break this cluster into dozens of smaller clusters, we needed to route events between clusters and topics based on headers. At the time, this meant we had to do it ourselves. Starting out, our goal was fan out (one-to-many) replication. Since then our needs have expanded to include many-to-one and many-to-many replication. In this talk we'll discuss what bottlenecks we have hit as we scaled out, and what measures we took to remove them, such as: Replicating data based on Kafka Headers Connecting to many source and destination Kafka clusters Managing the replication of Kafka topics of varying traffic The use of an intermediary Kafka cluster At the end of this talk you will understand how we have scaled replication and routing to support New Relic's ever growing data ingestion, and all the mitigations it took to get us there. ABOUT CONFLUENT Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io. #confluent #apachekafka #kafka