Stefan Kecskes

Never stop learning, because life never stops teaching

KRaft: The Kafka Raft

Kafka’s new KRaft architecture replaces ZooKeeper with a built-in Raft-based metadata quorum, making the platform simpler, faster, and self-managing. In this post I explain how metadata now lives inside Kafka itself, why the change was needed, and how KIP-833 enables smooth migration from ZooKeeper to KRaft.

Kafka Connectors: More than just configs

An in-depth look at Kafka Connectors, focusing on their architecture, transformation features, schema management, error handling, and scalability. Includes practical configuration examples and lessons learned from real-world deployments.

Delta Lake Evolution and Migrations

In the world of data management, we often talk about schema migrations. But what exactly is schema migrations, and why it is so crucial to have a proper plan for data management? I will show you naive approach, explore some traditional solutions. We will see Delta Lake in action, but also how we can do schema migrations with our own way.

Data Modeling

Often, we leave the intricate details of data structures and performance to the DB Admin team, assuming that upscaling servers will solve everything. I used to think data modeling was just a fancy term for database design with only one right way to do it. Let’s talk about the crucial differences between transactional and analytical data modeling, each with its own tools and techniques

Using Volumes in Kubernetes

Volumes in Kubernetes are used to store data used by our applications. So that concept is very similar to volumes in docker containers. But there are some subtle differences, as always in life; nothing can be simple. :) There are many types of volumes in Kubernetes, and in this post, we will group them by properties and see some of the most common types.