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

How do the principles of chaotic, agile operations in the military apply to software development and event-driven systems? As a former Royal Marine, Ben Ford (Founder and CEO, Commando Development) is also a software developer, with many years of experience building event streaming architectures across financial services and startups. He shares principles that the military employs in chaotic condi...

Imagine you can process and analyze real-time event streams for intelligence to mitigate cyber threats or keep soldiers constantly alerted to risks and precautions they should take based on events. In this episode, Jeffrey Needham (Senior Solutions Engineer, Advanced Technology Group, Confluent) shares use cases on how Apache Kafka® can be used for real-time signal processing to mitigate risk befo...

How is Apache Kafka® relevant to blockchain technology and cryptocurrency? Fotios Filacouris (Staff Solutions Engineer, Confluent) has been working with Kafka for close to five years, primarily designing architectural solutions for financial services, he also has expertise in the blockchain. In this episode, he joins Kris to discuss how blockchain and Kafka are complementary, and he also highlight...

To ensure safe and efficient deployment of Apache Kafka® clusters across multiple cloud providers, Confluent rolled out a large scale cluster management solution. Rashmi Prabhu (Staff Software Engineer & Eng Manager, Fleet Management Platform, Confluent) and her team have been building the Fleet Management Platform for Confluent Cloud. In this episode, she delves into what Fleet Management is,...

What are some of the common mistakes that you have seen with Apache Kafka® record production and consumption? Nikoleta Verbeck (Principal Solutions Architect at Professional Services, Confluent) has a role that specifically tasks her with performance tuning as well as troubleshooting Kafka installations of all kinds. Based on her field experience, she put together a comprehensive list of common is...

A well-written abstract is your ticket to conferences, but how do you write an excellent synopsis that will get accepted? As an experienced conference speaker, Robin Moffatt (Principal Developer Advocate, Confluent) often writes presentations that help the developer community to understand Apache Kafka® and its ecosystem. He is also the Program Committee Chair for Kafka Summit and Current 2022 : T...

What is a developer advocate and how do you become one? In this episode, we have seasoned developer advocates, Kris Jenkins (Senior Developer Advocate, Confluent) and Danica Fine (Senior Developer Advocate, Confluent) answer the question by diving into how they got into the world of developer relations, what they enjoyed the most about their roles, and how you can become one. Developer advocacy is...

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. Adam begins by noting that while data mesh is a type of modern data archit...

Stream processing can be hard or easy depending on the approach you take, and the tools you choose. This sentiment is at the heart of the discussion with Matthias J. Sax (Apache Kafka® PMC member; Software Engineer, ksqlDB and Kafka Streams, Confluent) and Jeff Bean (Sr. Technical Marketing Manager, Confluent). With immense collective experience in Kafka, ksqlDB, Kafka Streams, and Apache Flink®,...

Apache Kafka® isn’t just for day jobs according to Danica Fine (Senior Developer Advocate, Confluent). It can be used to make life easier at home, too! Building out a practical Apache Kafka® data pipeline is not always complicated—it can be simple and fun. For Danica, the idea of building a Kafka-based data pipeline sprouted with the need to monitor the water level of her plants at home. In this e...

Apache Kafka® 3.2 delivers new  KIPs in three different areas of the Kafka ecosystem: Kafka Core, Kafka Streams, and Kafka Connect. On behalf of the Kafka community, Danica Fine (Senior Developer Advocate, Confluent), shares release highlights. More than half of the KIPs in the new release concern Kafka Core. KIP-704 addresses unclean leader elections by allowing for further communication between...

How much can Apache Kafka® scale horizontally, and how can you automatically balance, or rebalance data to ensure optimal performance? You may require the flexibility to scale or shrink your Kafka clusters based on demand. With experience engineering cluster elasticity and capacity management features for cloud-native Kafka, Ajit Yagaty (Confluent Cloud Control Plane Engineering) and Aashish Kohli...

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...

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 build...

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...

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'...

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 te...

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 st...

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 acco...

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 Kafk...

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...

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 observabil...

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 mov...

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 wi...

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 d...