Join our hosts and guests from the community as they discuss the latest Apache Kafka®️ news, use cases, and trends spanning the topics of data streaming, microservices, modern IT architectures, and the cloud.
Migrating Apache Kafka® clusters can be challenging, especially when moving large amounts of data while minimizing downtime. Michael Dunn (Solutions Architect, Confluent) has worked in the data space for many years, designing and managing systems to support high-volume applications. He has helped many organizations strategize, design, and implement successful Kafka cluster migrations between different environments. In this episode, Michael shares some tips about Kafka cluster migration with Kris, including the pros and cons of the different tools he recommends.
dbt is known as being part of the Modern Data Stack for ELT processes. Being in the MDS, dbt Labs believes in having the best of breed for every part of the stack. Oftentimes folks are using an EL tool like Fivetran to pull data from the database into the warehouse, then using dbt to manage the transformations in the warehouse. Analysts can then build dashboards on top of that data, or execute tests. It’s possible for an analyst to adapt this process for use with a microservice application using Apache Kafka and the same method to pull batch data out of each and every database; however, in this episode, Amy Chen (Partner Engineering Manager, dbt Labs) tells Kris about a better way forward for analysts willing to adopt the streaming mindset.
What can online gaming teach us about making large-scale event management more collaborative in real-time? In this episode, Ben Gamble (Developer Relations Manager, Aiven) talks with Kris about integrating gaming concepts with Apache Kafka. Using Kafka’s state management stream processing, Ben has built systems that can handle real-time event processing at a massive scale, including interesting approaches to conflict resolution and collaboration.
Are bad customer experiences really just data integration problems? Can real-time data streaming and machine learning be democratized in order to deliver a better customer experience? Airy, an open-source data-streaming platform, uses Apache Kafka to help business teams deliver better results to their customers. In this episode, Airy CEO and co-founder Steffen Hoellinger explains how his company is expanding the reach of stream-processing tools and ideas beyond the world of programmers.
The past year saw new trends emerge in the world of data streaming technologies, as well as some unexpected and novel use cases for Apache Kafka. New reflections on the future of stream processing and when companies should adopt microservice architecture inspired several talks at this year’s industry conferences. In this episode, Kris is joined by his colleagues Danica Fine, Senior Developer Advocate, and Robin Moffatt, Principal Developer Advocate, for an end-of-year roundtable on this year’s developments and what they want to see in the year to come.
If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.
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