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.
What’s the next big thing in the future of streaming data? In this episode, Greg DeMichillie (VP of Product and Solutions Marketing, Confluent) talks to Kris about the future of stream processing in environments where the value of data lies in their ability to intercept and interpret data.
Data democratization allows everyone in an organization to have access to the data they need, and the necessary tools needed to use this data effectively. In short, data democratization enables better business decisions. In this episode, Rama Ryali, a Senior IT and Data Executive, chats with Kris Jenkins about the importance of data democratization in modern systems.
Inheriting software in the banking sector can be challenging. Perhaps the only thing harder is inheriting software built by a committee of banks. How do you keep it running, while improving it, refactoring it, and planning a bigger future for it? In this episode, Jean-Francois Garet (Technical Architect, Symphony) shares his experience at Symphony as he helps it evolve from an inherited, monolithic, single-tenant architecture to an event mesh for seamless event-streaming microservices. He talks about the journey they’ve taken so far, and the foundations they’ve laid for a modern data mesh.
Data mesh isn’t software you can download and install, so how do you build a data mesh? In this episode, Adam Bellemare (Staff Technologist, Office of the CTO, Confluent) discusses his data mesh proof of concept and how it can help you conceptualize the ways in which implementing a data mesh could benefit your organization.
New Relic runs one of the larger Apache Kafka installations in the world, ingesting circa 125 petabytes a month, or approximately three billion data points per minute. Anton Rodriguez is the chief architect of the system, responsible for hundreds of clusters and thousands of clients, some of them implemented in non-standard technologies. In addition to the large volume of servers, he works with many teams, which must all work together when issues arise.
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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