Is there a better way to manage access to resources without compromising security? New employees need access to a variety of resources within a company's tech stack. But manually granting access can be error-prone. And when employees leave, their access must be revoked, thus potentially introducing security risks if an admin misses one. In this podcast, Kris Jenkins talks to Anuj Sawani (Security Product Manager, Confluent) about the centralized identity management system he helped build to integrate with Apache Kafka® to prevent common identity management headaches and security risks.
With 12+ years of experience building cybersecurity products for enterprise companies, Anuj Sawani explains how he helped build out KIP-768 (Secured OAuth support in Kafka) that supports a unified identity mechanism that spans across cloud and on-premises (hybrid scenarios).
Confluent Cloud customers wanted a single identity to access all their services. The manual process required managing different sets of identity stores across the ecosystem. Anuj goes on to explain how Identity and Access Management (IAM) using cloud-native authentication protocols, such as OAuth or OpenID Connect, solves this problem by centralizing identity and minimizing security risks.
Anuj emphasizes that sticking with industry standards is key because it makes integrating with other systems easy. With OAuth now supported in Kafka, this means performing client upgrades, configuring identity providers, etc. to ensure the applications can leverage new capabilities. Some examples of how to do this are to use centralized identities for client/broker connections.
As Anuj continues to build and enhance features, he hopes to recommend this unified solution to other technology vendors because it makes integration much easier. The goal is to create a web of connectors that support the same standards. The future is bright, as other organizations are researching supporting OAuth and similar industry standards. Anuj is looking forward to the evolution and applying it to other use cases and scenarios.
EPISODE LINKS
Building Real-Time Data Governance at Scale with Apache Kafka ft. Tushar Thole
Handling 2 Million Apache Kafka Messages Per Second at Honeycomb
Why Data Mesh? ft. Ben Stopford
Serverless Stream Processing with Apache Kafka ft. Bill Bejeck
The Evolution of Apache Kafka: From In-House Infrastructure to Managed Cloud Service ft. Jay Kreps
What’s Next for the Streaming Audio Podcast ft. Kris Jenkins
On to the Next Chapter ft. Tim Berglund
Intro to Event Sourcing with Apache Kafka ft. Anna McDonald
Expanding Apache Kafka Multi-Tenancy for Cloud-Native Systems ft. Anna Povzner and Anastasia Vela
Apache Kafka 3.1 - Overview of Latest Features, Updates, and KIPs
Optimizing Cloud-Native Apache Kafka Performance ft. Alok Nikhil and Adithya Chandra
From Batch to Real-Time: Tips for Streaming Data Pipelines with Apache Kafka ft. Danica Fine
Real-Time Change Data Capture and Data Integration with Apache Kafka and Qlik
Modernizing Banking Architectures with Apache Kafka ft. Fotios Filacouris
Running Hundreds of Stream Processing Applications with Apache Kafka at Wise
Lessons Learned From Designing Serverless Apache Kafka ft. Prachetaa Raghavan
Using Apache Kafka as Cloud-Native Data System ft. Gwen Shapira
ksqlDB Fundamentals: How Apache Kafka, SQL, and ksqlDB Work Together ft. Simon Aubury
Explaining Stream Processing and Apache Kafka ft. Eugene Meidinger
Handling Message Errors and Dead Letter Queues in Apache Kafka ft. Jason Bell
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