Decoding Kafka Challenges: Addressing Common Pain Points in Kafka Deployments

In the realm of distributed event streaming, Apache Kafka stands tall as a powerful and versatile platform, enabling real-time data processing, messaging, and event-driven architectures. However, deploying and managing Kafka at scale comes with challenges and pain points. Join us for a deep dive into these challenges and how Apache Pulsar addresses them.


- Exploring Common Pain Points in Kafka DeploymentsUnderstanding Multi-Tenancy Challenges

- The Repartitioning Dilemma

- Data Retention Challenges

- Messaging Queueing Challenges

- Geo-Replication Challenges

- Conclusion and Q&A

Key Takeaways:

- Understanding the complexities of Kafka deployments

- Learning how Apache Pulsar addresses common pain points

- Insights into effective strategies for Kafka deployment and management

David Kjerrumgaard
David is a Sales Engineer and former Developer Advocate for StreamNative with a focus on helping developers solve their streaming data challenges using Apache Pulsar. He has over 15 years of experience working with open source projects in the Big Data, Stream Processing, and Distributed Computing spaces. David is the author of the book Pulsar in Action.


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