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

The data mesh architectural paradigm shift is all about moving analytical data away from a monolithic data warehouse or data lake into a distributed architecture—allowing data to be shared for analytical purposes in real time, right at the point of origin. The idea of data mesh was introduced by Zhamak Dehghani (Director of Emerging Technologies, Thoughtworks) in 2019.  Here, she provides an intro...

Note: This episode was recorded when Cluster Linking was in preview mode. It’s now generally available as part of the Confluent Q3 ‘21 release on August 17, 2021.  Infrastructure needs to react in real time to support globally distributed events, such as cloud migration, IoT, edge data collection, and disaster recovery. To provide a seamless yet cloud-native, cross-cluster topic replication experi...

What does a ride-hailing app that offers micromobility and food delivery services have to do with data in motion? In this episode, Ruslan Gibaiev (Data Architect, Bolt) shares about Bolt’s road to adopting Apache Kafka® and ksqlDB for stream processing to replicate data from transactional databases to analytical warehouses.  Rome wasn't built overnight, nor was the adoption of Kafka and ksqlD...

Monolithic applications present challenges for organizations like Saxo Bank, including difficulties when it comes to transitioning to cloud, data efficiency, and performing data management in a regulated environment. Graham Stirling, the head of data platforms at Saxo Bank and also a self-proclaimed recovering architect on the pathway to delivery, shares his experience over the last 2.5 years as S...

ksqlDB makes it easy to read, write, process, and transform data on Apache Kafka®, the de facto event streaming platform. With simple SQL syntax, pre-built connectors, and materialized views, ksqlDB’s powerful stream processing capabilities enable you to quickly start processing real-time data at scale. But how does ksqlDB work? In this episode, Michael Drogalis (Principal Product Manager, Product...

Building a large, stateful Kafka Streams application that tracks the state of each outgoing email is crucial to marketing automation tools like Mailchimp. Joining us today in this episode, Mitch Seymour, staff engineer at Mailchimp, shares how ksqlDB and Kafka Streams handle the company’s largest source of streaming data.   Almost like a post office, except instead of sending physical parcels, Mai...

The best-informed business insights that support better decision-making begin with data collection, ahead of data processing and analytics. Enterprises nowadays are engulfed by data floods, with data sources ranging from cloud services, applications, to thousands of internal servers. The massive volume of data that organizations must process presents data ingestion challenges for many large compan...

Stream processing has become an important part of the big data landscape as a new programming paradigm to implement real-time data-driven applications. One of the biggest challenges for streaming systems is to provide correctness guarantees for data processing in a distributed environment. Guozhang Wang (Distributed Systems Engineer, Confluent) contributed to a leadership paper, along with other l...

Using large amounts of streaming data increasingly requires interactive, real-time analytics and dashboards—and this applies to any industry, including tech. CTO and Co-Founder of Rockset Dhruba Borthakur shares how his company uses Apache Kafka® to perform complex joins, search, and aggregations on streaming data with low latencies. The Kafka database integrations allow his team to make a cloud-n...

Is it possible to have automated adoption of your event-driven architectures and microservices? The answer is yes! Alianna Inzana, product leader for API testing and virtualization at SmartBear, uses this evolutionary model to make event services reusable, functional, and strategic for both in-house needs and clients. SmartBear relies on Apache Kafka® to drive its automated microservices solutions...

Coming out of university, Patrick Neff (Data Scientist, BAADER) was used to “perfect” examples of datasets. However, he soon realized that in the real world, data is often either unavailable or unstructured.  This compelled him to learn more about collecting data, analyzing it in a smart and automatic way, and exploring Apache Kafka® as a core ecosystem while at BAADER, a global provider of food p...

The most secure clusters aren’t built on the hopes that they’ll never break. They are the clusters that are broken on purpose and with a specific goal. When organizations want to avoid systematic weaknesses, chaos engineering with Apache Kafka® is the route to go.  Your system is only as reliable as its highest point of vulnerability. Patrick Brennan (Principal Architect) and Tammy Butow (Principa...

Confluent Cloud isn’t just for public access anymore. As the requirement for security across sectors increases, so does the need for virtual private cloud (VPC) connections. It is becoming more common today to come across Apache Kafka® implementations with the latest private link connectivity option.  In the past, most Confluent Cloud users were satisfied with public connectivity paths and VPC pee...

Based on Apache Kafka® 2.8, Confluent Platform 6.2 introduces Health+, which offers intelligent alerting, cloud-based monitoring tools, and accelerated support so that you can get notified of potential issues before they manifest as critical problems that lead to downtime and business disruption. Health+ provides ongoing, real-time analysis of performance and cluster metadata for your Confluent Pl...

Collecting internal, operational telemetry from Confluent Cloud services and thousands of clusters is no small feat. Stakeholders need to rely on the same data to make operational decisions. Whether it be metrics from clusters in Confluent Cloud or traces from our internal service, they all provide valuable insights not only to engineering teams but also to customers for their own operations and f...

Focused on optimizing Apache Kafka® performance with maximized efficiency, Confluent’s Product Infrastructure team has been actively exploring opportunities for scaling out Kafka clusters. They are able to run Kafka workloads with half the typical memory usage while saving infrastructure costs, which they have tested and now safely rolled out across Confluent Cloud.  After spending seven years at...

When compiling database reports using a variety of data from different systems, obtaining the right data when you need it in real time can be difficult. With cloud connectivity and distributed data pipelines, Pat Helland (Principal Architect, Salesforce) explains how to make educated partial answers when you need to use the Apache Kafka® platform. After all, you can’t get guarantees across a dista...

Jason Gustafson and Colin McCabe, Apache Kafka® developers, discuss the project to remove ZooKeeper—now known as the KRaft (Kafka on Raft) project. A previous episode of Streaming Audio featured both developers on the podcast before the release of Apache Kafka 2.8. Now they’re back to share their progress. The KRraft code has been merged (and continues to be merged) in phases. Both developers talk...

What is the internet of things (IoT), and how does it relate to event streaming and Apache Kafka®? The deployment of Kafka outside the datacenter creates many new possibilities for processing data in motion and building new business cases. In this episode, Kai Waehner, field CTO and global technology advisor at Confluent, discusses the intersection of edge data infrastructure, IoT, and cloud servi...

Imagine if you could create a better world for future generations simply by delivering marine ingenuity.  Van Oord is a Dutch family-owned company that has served as an international marine contractor for over 150 years, focusing on dredging, land infrastructure in the Netherlands, and offshore wind and oil & gas infrastructure. Real-time insights into costs spent, the progress of projects, an...

At Klarna, Lead Engineer Tommy Brunn is building a runtime platform for developers. But outside of his professional role, he is also one of the authors of the JavaScript client for Apache Kafka® called KafkaJS, which has grown from being a niche open source project to the most downloaded Kafka client for Node.js since 2018. Using Kafka in Node.js has previously meant relying on community-contribut...

Apache Kafka 2.8 is out! This release includes early access to the long-anticipated ZooKeeper removal encapsulated in KIP-500, as well as other key updates, including the addition of a Describe Cluster API, support for mutual TLS authentication on SASL_SSL listeners, exposed task configurations in the Kafka Connect REST API, the removal of a properties argument for the TopologyTestDriver, the intr...

When building solutions for customers in Microsoft Azure, it is not uncommon to come across customers who are deeply entrenched in the Apache Kafka® ecosystem and want to continue expanding within it. Thus, figuring out how to connect Azure first-party services to this ecosystem is of the utmost importance. Ryan CrawCour is a Microsoft engineer who has been working on all things data and analytics...

If you’ve heard the term “clusters,” then you might know it refers to Confluent components and features that we run in all three major cloud providers today, including an event streaming platform based on Apache Kafka®, ksqlDB, Kafka Connect, the Kafka API, databalancers, and Kafka API services. Rashmi Prabhu, a software engineer on the Control Plane team at Confluent, has the opportunity to help...

As most developers and architects know, data always needs to be accessible no matter what happens outside of the system. This week, Tim Berglund virtually sits down with Anna McDonald (Principal Customer Success Technical Architect, Confluent) to discuss how Automatic Observer Promotion (AOP) can help solve the Apache Kafka® 2.5 datacenter dilemma as a feature now available in Confluent Platform 6...