Real-Time Event Distribution with Data Mesh

Real-Time Event Distribution with Data Mesh

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 tal...

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Why Kafka Connect? ft. Robin Moffatt

Why Kafka Connect? ft. Robin Moffatt

In this episode, Tim talks to Robin Moffatt about what Kafka Connect is and why you should almost certainly use it if you're working with Apache Kafka®️. Whether you're building database offload pipel...

12 Kesä 201946min

Schema Registry Made Simple by Confluent Cloud ft. Magesh Nandakumar

Schema Registry Made Simple by Confluent Cloud ft. Magesh Nandakumar

Tim Berglund and Magesh Nandakumar (Software Engineer, Confluent) discuss why schemas matter for building systems on Apache Kafka®, and how Confluent Schema Registry helps with the problem. They talk ...

3 Kesä 201941min

Why is Stream Processing Hard? ft. Michael Drogalis

Why is Stream Processing Hard? ft. Michael Drogalis

Tim Berglund and Michael Drogalis (Product Lead for Kafka Streams and KSQL, Confluent) talk about all things stream processing: why it’s complex, how it's evolved, and what’s on the horizon to make it...

29 Touko 201945min

Testing Kafka Streams Applications with Viktor Gamov

Testing Kafka Streams Applications with Viktor Gamov

Tim Berglund is joined by Viktor Gamov (Developer Advocate, Confluent) to discuss various approaches to testing Kafka Streams applications. EPISODE LINKS KafkaEmbeddedTopologyTestDriverMocked Streams...

20 Touko 201942min

Chris Riccomini on the History of Apache Kafka and Stream Processing

Chris Riccomini on the History of Apache Kafka and Stream Processing

It’s a problem endemic to the tech world that we are always focused on what’s coming next, that we often forget to look at where we’ve been. Chris Riccomini, who was there at LinkedIn when Apache Kafk...

16 Touko 201950min

Ask Confluent #13: Machine Learning with Kai Waehner

Ask Confluent #13: Machine Learning with Kai Waehner

Gwen and Kai chat about machine learning architectures, and whether software engineers and data scientists can learn to get along. EPISODE LINKS Blogs on deploying machine learning workloads: Machine...

8 Touko 201933min

Diving into Exactly Once Semantics with Guozhang Wang

Diving into Exactly Once Semantics with Guozhang Wang

It has been said that in distributed messaging, there are two hard problems: 2) exactly once delivery, 1) guaranteed order of messages and 2) exactly once delivery. Apache Kafka® has offered exactly o...

22 Huhti 201947min

Ask Confluent #12: In Search of the Lost Offsets

Ask Confluent #12: In Search of the Lost Offsets

Stanislav Kozlovski joins us to discuss common pitfalls when using Kafka consumers and a new KIP that promises to make consumer restarts much smoother. EPISODE LINKS KIP-345: Static consumer membersh...

17 Huhti 201922min

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