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Abstract: LinkedIn is building massive and complex data pipelines based on its Pub/Sub system, Kafka. Kafka uses topics to categorize data. The number of topics can grow organically depending on business needs, but Kafka itself doesn't have a mechanism to detect and delete unused topics.
Review streaming technologies like Event Hubs, Brooklin, TopicGC services & others.
Discuss how LinkedIn cleans up unused metadata for its Pub/Sub system & how TopicGC service can reduce Kafka pressure performance by at least 20%.
Upskill yourself and explore topics like Event Streaming with Kafka using Azure Event Hubs, Change Data Capture with Flink SQL and Brooklin & more.
Upgrade yourself & network with top industry players like Kasun Indrasiri, Microsoft; Shanthoosh Venkataraman & Hao Geng from LinkedIn.
Founded in 2003, LinkedIn connects the world's professionals to make them more productive and successful.
Great place to network and connect with the Kafka Community.
Such a knowledgeable speaker should be given better equipment and microphone.
Founded in 2003 LinkedIn connects the world s professionals to make them more productive and successful With more than 850 million members worldwide including executives from every Fortune 500 company LinkedIn is the world s largest professional netw
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