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PODCAST

Confluent Developer ft. Tim Berglund, Adi Polak & Viktor Gamov

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 interviews with our community of software developers (actual human beings - not AI) talking about some of the most interesting challenges they’ve faced in their careers. We aim to explore the conditions that gave rise to each person’s technical hurdles, as well as how their experiences transformed their

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All Episodes

45:45

Why is Stream Processing Hard? ft. Michael Drogalis

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/05/29

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 simpler.

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42:33

Testing Kafka Streams Applications with Viktor Gamov

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/05/20

Tim Berglund is joined by Viktor Gamov (Developer Advocate, Confluent) to discuss various approaches to testing Kafka Streams applications.EPISODE LINKSKafkaEmbeddedTopologyTestDriverMocked Streams (Scala)MockafkaTest containersKafka containers

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50:59

Chris Riccomini on the History of Apache Kafka and...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/05/16

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 Kafka® was born, tells us how Kafka and the stream processing framework Samza came about, and also what he’s doing these days at WePay—building systems that use Kafka as a primary datastore.EPISODE LINKSWhen It Absolutely, Positively, Has to be There: Reliability Guarantees in KafkaSo, You Want to Build a

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33:15

Ask Confluent #13: Machine Learning with Kai Waehner

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/05/08

Gwen and Kai chat about machine learning architectures, and whether software engineers and data scientists can learn to get along.EPISODE LINKSBlogs on deploying machine learning workloads: Machine Learning with Python, Jupyter, KSQL and TensorFlowHow to Build and Deploy Scalable Machine Learning in Production with Apache KafkaUsing Apache Kafka to Drive Cutting-Edge Machine LearningKIP-392: Allow consumers to fetch from closest replica Watch the video version of this podcast

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47:53

Diving into Exactly Once Semantics with Guozhang Wang

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/04/22

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

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22:04

Ask Confluent #12: In Search of the Lost Offsets

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/04/17

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 LINKSKIP-345: Static consumer membership KIP-211: Documents the current behavior of offset expirationWatch the video version of this podcast

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58:15

Ben Stopford on Microservices and Event Streaming

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/04/08

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

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46:47

Magnus Edenhill on librdkafka 1.0

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/04/03

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 LINKSlibrdkafka v1.0.0 release notes

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14:28

Ask Confluent #11: More Services, More Metrics, More Fun

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/03/26

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 LINKSThe Java property that will refresh DNS cache frequently: java.security.Security.setProperty(“networkaddress.cache.ttl” , “60");Improvements to DNS lookups in Confluent Platform 5.1.2 (Apache Kafka 2.1.1):KAFKA-7755KAFKA-7890More reasons to upgrade to Confluent Platform 5.1.2Monitoring clients with old

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36:56

It’s Time for Streaming to Have a Maturity Model ft....

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/03/18

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

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41:45

Containerized Apache Kafka On Kubernetes with Viktor...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/03/11

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

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19:27

Catch Your Bus with KSQL: A Stream Processing Recipe...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/03/04

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

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45:56

KTable Update Suppression (and a Bunch About KTables)...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/02/27

When you are dealing with streaming data, it might seem like tables are things that dwell in the far-off land of relational databases, outside of Apache Kafka and your event streaming system. But then the Kafka Streams API gives us the KTable abstraction, which lets us create tabular views of data in Kafka topics. Apache Kafka 2.1 featured an interesting change to the table API—commonly known to the world as KIP-328—that gives you better control over how updates to tables are emitted into

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20:42

Splitting and Routing Events with KSQL ft. Pascal...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/02/25

Tim Berglund chats with System Engineer Pascal Vantrepote about a KSQL recipe he created based on a real-life customer use case in the financial services industry. They also discuss the advantages of KSQL, such as its expressiveness and ease of deployment in places where you’re not already writing a Java application.EPISODE LINKSAbout KSQL Stream Processing CookbookKSQL Recipe: Data Routing Joined with a KTableFor more, you can check out ksqlDB, the successor to KSQL.

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21:29

Ask Confluent #10: Cooperative Rebalances for Kafka...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/02/20

Want to know how Kafka Connect distributes tasks to workers? Always thought Connect rebalances could be improved? In this episode of Ask Confluent, Gwen Shapira speaks with Konstantine Karantasis, software engineer at Confluent, about the latest improvements to Kafka Connect and how to run the Confluent CLI on Windows.EPISODE LINKSImproved rebalancing for Kafka ConnectImproved rebalancing for Kafka StreamsThe "what would Kafka do?" scenario from Mark PapadakisThe future of retail at

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41:00

The Future of Serverless and Streaming with Neil Avery

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/02/14

Neil Avery explores the intersection between FaaS and event streaming applications before taking a quick detour back in time to understand how we've gotten to this point in event-driven applications. He'll explain the pros and cons of FaaS, and cover how in its current state cold starts and latency concerns need to be part of the bigger picture when building streaming applications. Finally, Neil shares five rules that will help you understand how FaaS fits with the event streaming

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28:57

Using Terraform and Confluent Cloud with Ricardo...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/01/23

Tim Berglund hosts Developer Advocate Ricardo Ferreira to discuss the concept of infrastructure as code, as well as the differences between Terraform, Ansible, Puppet and Chef. They also chat about why Terraform is such a big deal, some of the challenges involved with learning it and how Confluent leverages Terraform to achieve multi-cloud support for Confluent Cloud and tools for Confluent Platform.EPISODE LINKSTerraformTools for Confluent Cloud ClustersFully managed Apache Kafka as a service! Try

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15:11

Ask Confluent #9: With and Without ZooKeeper

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2019/01/08

Gwen asks: What happens when garbage collection causes Kafka to pause? And how do we run a Schema Registry cluster? We’ll find out in this episode of Ask Confluent.In "Ask Confluent," Gwen Shapira (Software Engineer, Confluent) and guests respond to a handful of questions and comments from Twitter, YouTube and elsewhere.EPISODE LINKSZooKeeper connection timeout configuration: zookeeper.connection.timeout.ms, as we said, this defaults to 6,000Schema Registry failover instructionsWatch the

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22:09

Ask Confluent #8: Guozhang Wang on Kafka Streams...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2018/12/18

Gwen is joined in studio by special guest Guozhang Wang, Kafka Streams pioneer and engineering lead at Confluent. He’ll talk to us about standby tasks and how one deserializes message headers. In "Ask Confluent," Gwen Shapira (Data Architect, Confluent) and guests respond to a handful of questions and comments from Twitter, YouTube and elsewhere.EPISODE LINKSDocumentation of standby tasks, including configsEvents with different schema in same topicHow to populate a database from Kafka and

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23:51

Ask Confluent #7: Kafka Consumers and Streams...

Confluent Developer ft. Tim Berglund, Adi Polak &... ·

2018/12/03

Gwen is joined in studio by special guest Matthias J. Sax, a software engineer at Confluent. He’ll talk to us about Kafka consumers and Kafka Streams failover. In "Ask Confluent," Gwen Shapira (Data Architect, Confluent) and guests respond to a handful of questions and comments from Twitter, YouTube and elsewhere.EPISODE LINKSWatch the video version of this podcast

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