Igor De SouzaKafka vs Flink vs Spark Streaming: What Nobody Tells You Before You Pick One
HackerNoonApache Kafka has gotten rather long in the tooth, is Apache Iggy the successor? https://hackernoon.com/what-the-heck-is-apache-iggy #apachekafka
From Batch to Real‑Time: Mastering Event‑Driven Architectures with Apache Kafka
From Batch to Real‑Time: Mastering Event‑Driven Architectures with Apache Kafka
Introduction For decades, enterprises have relied on batch jobs to move, transform, and analyze data. Nightly ETL pipelines, scheduled reports, and periodic data warehouses have been the backbone of decision‑making. Yet the business landscape is changing: customers expect instant feedback, fraud detection must happen in milliseconds, and Internet‑of‑Things (IoT) devices generate a continuous flood of events. Enter event‑driven architecture (EDA)—a paradigm where systems react to streams of immutable events as they happen. At the heart of modern EDA is Apache Kafka, a distributed log that can ingest billions of events per day, guarantee ordering per partition, and provide durable storage for as long as you need.
Visual Guide to Apache Kafka Diskless Topics & Cloud Costs
https://www.instaclustr.com/blog/visual-guide-to-apache-kafka-diskless-topics-cloud-costs/
Visual Guide to Apache Kafka Diskless Topics & Cloud Costs
A visual guide to Apache Kafka® Diskless Topics: Finding Zen in the cloud I’ve been tracking the progress of Apache Kafka “Diskless Topics” for a while now. It’s a topic that sparks curiosity—mostly because the name itself sounds like an oxymoron. How can a topic be diskless? Where does the data go? With the recent......
Happy #piday !!!
Estimating Pi with Kafka Streams
https://fredrikmeyer.net/2024/05/06/estimating-pi-kafka.html
Announcing Inkless clusters: Cloud Kafka done right
https://aiven.io/blog/announcing-inkless-clusters-cloud-kafka-done-right
SoftwareMillIs your Kafka lag dashboard lying? Learn how log compaction and retention silently manipulate reported timestamps to understate consumer delays and how to identify these inaccuracies and ensure your monitoring reflects actual system performance.
https://softwaremill.com/compaction-and-retention-edge-cases-that-make-your-kafkas-lag-metrics-inaccurate/
#ApacheKafka #DataEngineering #DistributedSystems #EventStreaming #Observability
KPipe: A Modern, High-Performance Kafka Consumer in Java — Powered by Java 25 Features
https://open.substack.com/pub/topicigor/p/kpipe-a-modern-high-performance-kafka
Event-Driven Architecture in Java and Kafka
A nice walk through in an application using Reactive Java with MongoDB.
https://foojay.io/today/event-driven-architecture-in-java-and-kafka/
Event-Driven Architecture in Java and Kafka
Reactive Java is well suited to modern streaming, event driven applications. In this article, we'll walk through an example of such an application using Reactive Java with MongoDB. Specifically, we're going to cover:Why Reactive Java was introduced and how it differs from more traditional Java programming.Details of some of the key elements of Reactive Java - Mono, Flux and flatMap.A walk through of a sample application, comparing a Reactive version of the code using the Reactive Streams MongoDB driver, with a more traditional version of the code using the synchronous MongoDB driver.
How KIP-881 and KIP-392 reduce Inter-AZ Networking Costs in Classic Kafka
https://getkafkanated.substack.com/p/how-kip-881-and-kip-392-reduce-inter
