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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

technology how to

All Episodes

34:41

Streaming Analytics on 50M Events Per Day with...

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

2022/05/05

What are useful practices for migrating a system to Apache Kafka® and Confluent Cloud, and why use Confluent to modernize your architecture?Dima Kalashnikov (Technical Lead, Picnic Technologies) is part of a small analytics platform team at Picnic, an online-only, European grocery store that processes around 45 million customer events and five million internal events daily. An underlying goal at Picnic is to try and make decisions as data-driven as possible, so Dima's team collects events on

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2:03

Build a Data Streaming App with Apache Kafka and JS -...

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

2022/05/03

Coding is inherently enjoyable and experimental. With the goal of bringing fun into programming, Kris Jenkins (Senior Developer Advocate, Confluent) hosts a new series of hands-on workshops—Coding in Motion, to teach you how to use Apache Kafka® and data streaming technologies for real-life use cases. In the first episode, Sound & Vision, Kris walks you through the end-to-end process of building a real-time, full-stack data streaming application from scratch using Kafka and

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48:54

Optimizing Apache Kafka's Internals with Its...

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

2022/04/28

You already know Apache Kafka® is a distributed event streaming system for setting your data in motion, but how does its internal architecture work? No one can explain Kafka’s internal architecture better than Jun Rao, one of its original creators and Co-Founder of Confluent. Jun has an in-depth understanding of Kafka that few others can claim—and he shares that with us in this episode, and in his new Kafka Internals course on Confluent Developer. One of Jun's goals in publishing the Kafka

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51:09

Using Event-Driven Design with Apache Kafka Streaming...

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

2022/04/21

What is event modeling and how does it differ from standard data modeling?In this episode of Streaming Audio, Bobby Calderwood, founder of Evident Systems and creator of oNote observes that at the dawn of the computer age, due to the fact that memory and computing power were expensive, people began to move away from time-and-narrative-oriented record-keeping systems (in the manner of a ship's log or a financial ledger) to systems based on aggregation. Such data-model systems, still dominant

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38:25

Monitoring Extreme-Scale Apache Kafka Using eBPF at...

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

2022/04/13

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 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.Monitoring New Relic's large Kafka installation

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10:01

Confluent Platform 7.1: New Features + Updates

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

2022/04/12

Confluent Platform 7.1 expands upon its already innovative features, adding improvements in key areas that benefit data consistency, allow for increased speed and scale, and enhance resilience and reliability.Previously, the Confluent Platform 7.0 release introduced Cluster Linking, which enables you to bridge on-premises and cloud clusters, among other configurations. Maintaining data quality standards across multiple environments can be challenging though. To assist with this problem, CP 7.1 adds

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70:56

Scaling an Apache Kafka Based Architecture at...

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

2022/04/07

Scaling Apache Kafka® can be tricky, let alone scaling a team. When he was first hired, Domenico Fioravanti of Therapie Clinic was given the challenging task of assembling a sizable tech team from scratch, while simultaneously building a scalable and decoupled architecture from the ground up. In addition, he wanted to deliver value to the company from day one. One way that Domenico ultimately accomplished these goals was by focusing on managed solutions in order to avoid large investments in

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23:13

Bridging Frontend and Backend with GraphQL and Apache...

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

2022/03/29

What is GraphQL? And how can you combine GraphQL with Apache Kafka® to query data in real time?With over 10 years of experience as a backend engineer, Gerard Klijs is a Confluent Community Catalyst, a contributor to several GraphQL libraries, and also a creator and maintainer of a Rust library to use Confluent Schema Registry with Java client. In this episode, he explains why you want to use Kafka with GraphQL and how they work together to bridge the gap between backend and frontend to make data

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42:58

Building Real-Time Data Governance at Scale with...

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

2022/03/22

Data availability, usability, integrity, and security are words that we sometimes hear a lot. But what do they actually look like when put into practice? That’s where data governance comes in. This becomes especially tricky when working with real-time data architectures.Tushar Thole (Senior Manager, Engineering, Trust & Security, Confluent) focuses on delivering features for software-defined storage, software-defined networking (SD-WAN), security, and cloud-native domains. In this episode, he

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41:36

Handling 2 Million Apache Kafka Messages Per Second...

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

2022/03/15

How many messages can Apache Kafka® process per second? At Honeycomb, it's easily over one million messages. In this episode, get a taste of how Honeycomb uses Kafka on massive scale. Liz Fong-Jones (Principal Developer Advocate, Honeycomb) explains how Honeycomb manages Kafka-based telemetry ingestion pipelines and scales Kafka clusters. And what is Honeycomb? Honeycomb is an observability platform that helps you visualize, analyze, and improve cloud application quality and performance

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44:42

Why Data Mesh? ft. Ben Stopford

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

2022/03/10

With experience in data infrastructure and distributed data technologies, author of the book “Designing Event-Driven Systems” Ben Stopford (Lead Technologist, Office of the CTO, Confluent) explains the data mesh paradigm, differences between traditional data warehouses and microservices, as well as how you can get started with data mesh. Unlike standard data architecture, data mesh is about moving data away from a monolithic data warehouse into distributed data systems. Doing so will allow data to

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42:23

Serverless Stream Processing with Apache Kafka ft....

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

2022/03/03

What is serverless?Having worked as a software engineer for over 15 years and as a regular contributor to Kafka Streams, Bill Bejeck (Integration Architect, Confluent) is an Apache Kafka® committer and author of “Kafka Streams in Action.” In today’s episode, he explains what serverless and the architectural concepts behind it are. To clarify, serverless doesn’t mean you can run an application without a server—there are still servers in the architecture, but they are abstracted away from your

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46:32

The Evolution of Apache Kafka: From In-House...

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

2022/02/24

When it comes to Apache Kafka®, there’s no one better to tell the story than Jay Kreps (Co-Founder and CEO, Confluent), one of the original creators of Kafka. In this episode, he talks about the evolution of Kafka from in-house infrastructure to a managed cloud service and discusses what’s next for infrastructure engineers who used to self-manage the workload. Kafka started out at LinkedIn as a distributed stream processing framework and was core to their central data pipeline. At the time, the

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2:39

What’s Next for the Streaming Audio Podcast ft. Kris...

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

2022/02/16

Meet your new host of the Streaming Audio podcast: Kris Jenkins (Senior Developer Advocate, Confluent)! In this preview, Kris shares a few highlights from forthcoming episodes to look forward to, spanning topics from data mesh, cloud-native technologies, and serverless Apache Kafka®, to data modeling. As a developer advocate, Kris is endlessly fascinated about software design, functional programming, real-time systems, and electronic music. He is a veteran software developer and engineer, with a

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6:45

On to the Next Chapter ft. Tim Berglund

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

2022/02/03

After nearly 200 podcast episodes of Streaming Audio, Tim Berglund bids farewell in his last episode as host of the show. Tim reflects on the many great memories with guests who have appeared on the segment—and each for its own reasons. He has covered a wide variety of topics, ranging from Apache Kafka® fundamentals, microservices, event stream processing, use cases, to cloud-native Kafka, data mesh, and more. As Tim mentions, the Streaming Audio podcast will continue on to explore all things about

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30:14

Intro to Event Sourcing with Apache Kafka ft. Anna...

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

2022/02/01

What is event sourcing and how does it work?Event sourcing is often used interchangeably with event-driven architecture and event stream processing. However, Anna McDonald (Principal Customer Success Technical Architect, Confluent) explains it's a specific category of its own—an event streaming pattern. Anna is passionate about event-driven architectures and event patterns. She’s a tour de force in the Apache Kafka® community and is the presenter of the Event Sourcing and Event Storage with

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31:01

Expanding Apache Kafka Multi-Tenancy for Cloud-Native...

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

2022/01/27

In an effort to make Apache Kafka® cloud native, Anna Povzener (Principal Engineer, Confluent) and Anastasia Vela (Software Engineer I, Confluent) have been working to expand multi-tenancy to cloud-native systems with automated capacity planning and scaling in Confluent Cloud. They explain how cloud-native data systems are different from legacy databases and share the technical requirements needed to create multi-tenancy for managed Kafka as a service. As a distributed system, Kafka is designed to

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4:43

Apache Kafka 3.1 - Overview of Latest Features,...

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

2022/01/24

Apache Kafka® 3.1 is here with exciting new features and improvements! On behalf of the Kafka community, Danica Fine (Senior Developer Advocate, Confluent) shares release highlights that you won’t want to miss, including foreign-key joins in Kafka Streams and improvements that will provide consistency for Kafka latency metrics. KAFKA-13439 deprecates the eager protocol, which has been the default since Kafka 2.4—it’s advised to upgrade your applications to the cooperative protocol as the eager

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30:40

Optimizing Cloud-Native Apache Kafka Performance ft....

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

2022/01/20

Maximizing cloud Apache Kafka® performance isn’t just about running data processes on cloud instances. There is a lot of engineering work required to set and maintain a high-performance standard for speed and availability. Alok Nikhil (Senior Software Engineer, Confluent) and Adithya Chandra (Staff Software Engineer II, Confluent) share about their efforts on how to optimize Kafka on Confluent Cloud and the three guiding principles that they follow whether you are self-managing Kafka or working on

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29:50

From Batch to Real-Time: Tips for Streaming Data...

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

2022/01/13

Implementing an event-driven data pipeline can be challenging, but doing so within the context of a legacy architecture is even more complex. Having spent three years building a streaming data infrastructure and being on the first team at a financial organization to implement Apache Kafka® event-driven data pipelines, Danica Fine (Senior Developer Advocate, Confluent) shares about the development process and how ksqlDB and Kafka Connect became instrumental to the implementation.By moving away from

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