
Sign up to save your podcasts
Or


Gwen and Kai chat about machine learning architectures, and whether software engineers and data scientists can learn to get along.
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
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 once processing since version 0.11, which allows properly configured producers and consumers to make the guarantee that each message will be processed exactly one time.
In this episode, Kafka Streams engineer Guozhang Wang walks through the implementation of transactional messaging in Kafka in some detail, including the idempotent producer API, the transaction coordinator responsible for managing the transaction log and consumer configurations. It’s a complex topic, but he takes us through it carefully and completely.
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
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
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
Microservices are pretty ubiquitous these days. Really “SOA done right,” they reimagine the services pattern in the context of the world we live in today, nearly two decades since the first big service-oriented systems hit production. But what have we learned in this time? There are plenty of war stories. System designers have explored different architectural patterns—REST, events and databases of all types.
In this podcast, Tim Berglund and Ben Stopford explore the event-driven paradigm and how it relates to the microservice architectures we build today. Ben dives deep into coupling, evolution and challenges of our increasingly data-oriented culture. He also talks about the future, where data are events and events are data, and touches on real-time architectures that retain the decoupling properties needed to be pluggable, and to evolve. Powerful stuff.
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
After several years of development, librdkafka has finally reached 1.0! It remains API compatible with older versions of the library, so you won’t need to make any changes to your application. There are, however, several important new features like the idempotent producer, sparse broker connections, support for the vaunted KIP-62 and a complete makeover for the C#/.NET client.
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
Do metrics for detecting clients from old versions actually exist? Or is Gwen making features up? This and more useful advice is coming up on today's episode of Ask Confluent.
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
Nick Dearden explains the five stages of streaming maturity. They are not denial, anger, bargaining, depression and acceptance—that’s the Kübler-Ross model, and it’s for bad things. This one is for awesome things, and takes you from the first streaming project you ever build all the way to a state where an entire organization is transformed to think in terms of real-time, event-driven systems. If you have ever found yourself trying to get streaming technology adopted, this episode is for you!
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
Kubernetes provides all the building blocks needed to run stateful workloads, but creating a truly enterprise-grade Apache Kafka® platform that can be used in production is not always intuitive. In this episode, Tim Berglund and Viktor Gamov address some of the challenges and pitfalls of managing Kafka on Kubernetes at scale. They also share lessons learned from the development of the Confluent Operator for Kubernetes, and answer questions like:
-What is Kubernetes?
-What are stateful workloads?
-Why are they hard?
-Will Confluent Operator make it easier?
EPISODE LINKS
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
We all know that feeling of waiting when your ride is running late. Leslie Kurt shares about how you can use KSQL to calculate the difference between the expected arrival time and real-time updates of a bus as it executes its route. Listen as Leslie walks you through fundamental concepts like KTables, Kafka Streams, persistent queries and Confluent MQTT Proxy, as well as other use cases that involve a similar mechanism of capturing Unix timestamps and performing a stream processing operation on these timestamps.
EPISODE LINKS
For more, you can check out ksqlDB, the successor to KSQL.
SEASON 2
Hosted by Tim Berglund, Adi Polak and Viktor Gamov
Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed
Music by Coastal Kites
Artwork by Phil Vo
From the publisher's feed
Hi, we’re Tim Berglund, Adi Polak, and Viktor Gamov and we’re excited to bring you the Confluent Developer podcast (formerly “Streaming Audio.”) Our hand-crafted weekly episodes feature in-depth…
Whether you’re a seasoned open source data streaming engineer, or just someone who’s interested in learning more about Apache Kafka®, Apache Flink® and real-time data, we hope you’ll appreciate the stories, the discussion, and our effort to bring you a high-quality show worth your time.

273 Listeners

286 Listeners

623 Listeners

144 Listeners

111,799 Listeners