Kafka was developed at LinkedIn in 2010. To encourage adoption, it was originally an open system; developers could easily create new data streams, add data to the pipeline, and read data as it was created. Kafka succeeded brilliantly at encouraging developers to build new data applications, improved the reliability of systems and applications, and helped LinkedIn scale its logging and data infrastructure.
Unfortunately, as Kafka usage grew at LinkedIn (and at other sites), we discovered problems with a totally open system. Developers might inadvertently cause production problems when creating new Kafka streams, engineers might change the configuration of critical systems, and employees might get access to sensitive data. As Kafka has been adopted by larger enterprises with more complex security requirements, we have had to rethink our architecture.
Jun Rao explains how the community has secured Apache Kafka, discussing the threats that Kafka Security mitigates, the changes that we made to Kafka to enable security, and the steps required to secure an existing Kafka cluster.
Jun Rao is the cofounder of Confluent, a company that provides a streaming data platform on top of Apache Kafka. Previously, Jun was a senior staff engineer at LinkedIn, where he led the development of Kafka, and a researcher at IBM’s Almaden research data center, where he conducted research on database and distributed systems. Jun is the PMC chair of Apache Kafka and a committer of Apache Cassandra.
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