Stanislav Kozlovski’s Post

Static dashboards can only show what already happened. With Apache Kafka®, you can build dashboards that surface what’s happening right now and give teams the power to act instantly. Learn how to build real-time dashboard in our latest blog 👉 https://cnfl.io/3IPxxfM

Are you making these common Kafka mistakes? After spending countless hours debugging, scaling, and optimizing Kafka pipelines, I’ve realized that many teams fall into the same traps — often unknowingly. So, I decided to put together a blog series: 🎯 "10 Common Kafka Mistakes and How to Avoid Them" From: Overusing Kafka as a database Misconfiguring retention settings Ignoring consumer lag Misusing keys (causing data skew or out-of-order processing) ... and more 🚀 This series is written for data engineers, architects, and platform teams who want to: ✅ Design more reliable pipelines ✅ Avoid painful production surprises ✅ Understand Kafka's internals with real-world examples 📖 Read the first part on Medium: 👉 [ https://lnkd.in/g9UhJc8t ] 📂 Browse the full GitHub repo (with diagrams & markdown): 👉[ https://lnkd.in/gs_uJ7Sb ] Would love your feedback! 🙌 Have you seen any of these mistakes in the wild? #ApacheKafka #DataEngineering #Streaming #TechBlog #KafkaMistakes #EventDriven #LinkedInTech #MediumBlog

Keen to master Apache Kafka and open source pipelines? Modern enterprises depend on real-time data flow to stay competitive, but managing complex pipelines with Apache Kafka can be a major challenge. Our insightful eBook, "Scaling Seamlessly with Apache Kafka," is your strategic playbook to overcome these obstacles. Inside, you'll find: ✅ Best practices for building robust and reliable pipelines ✅ Real-world use cases to achieve measurable business outcomes ✅ A roadmap for scaling Kafka to drive efficiency and innovation Equip your team with the insights to optimize operations, improve scalability, and innovate faster than the competition. Download your free copy today and chart a clear path to open source success: https://bit.ly/40k5uuv #BigData #ApacheKafka #DataStreaming #OpenSource #TechInnovation #ScalableSolutions #DataEngineering #NetAppInstaclustr

🚀 Excited to share my latest Rust-based 🦀 open-source project — Kafka2i! A terminal UI for Kafka that makes debugging and message inspection a whole lot easier. If you’ve ever struggled to fetch messages from Kafka using the standard CLI tools or kcat, you know the pain! OAuth based setup makes it even more painful. Kafka2i simplifies this: - Explore Kafka metadata easily - Fetch messages by offset or timestamp - Seamlessly handle OAuth authentication & refresh tokens If you work with Kafka, I’d love your feedback! https://lnkd.in/dDCJ3BBN #rust #ratatui #rdkafka #TUI #opensource

Ever wondered how systems like Apache Kafka handle server failures? I decided to build my own fault-tolerant distributed event streaming system from scratch in Go to find out! Key features: 1️⃣ Fault Tolerance & Log Replication using Raft Protocol: data is copied and kept in sync across multiple servers. If a server fails, the system automatically elects a new leader and continues processing messages without data loss or downtime. 2️⃣ Scaling Performance (Topic Partitioning): organizing data into topics, which are subdivided into partitions. 3️⃣ Kafka-style Rebalancing Protocol: automatically balances partitions across all consumers in a group as they join and leave. Check out the full implementation and architecture breakdown on GitHub https://lnkd.in/gVtkNZQg If you find the work interesting, give the repo a star ⭐. Appreciate! #DistributedSystem #FaultTolerance #SystemDesign #Kafka

Using Gemini Pro to build Kafka-like distributed event streaming system from scratch. Side project from Quang Hoang. Give the repo a star if you find it helpful.

Long-dormant bugs surfacing at the worst time, compatibility regressions in edge cases, and the challenge of coordinating open-source projects. Plus: compression breakthroughs, IDE integrations, and the KIPs shaping Kafka's future... all this and more in the latest Get Kafka-nated Espresso! Your biweekly concentrated shot of Apache Kafka community news. Check out the latest issue via the link in the comments. #ApacheKafka #StreamProcessing

🎉 Apache Kafka 3.8 is officially here! 🎉 This release includes 17 new KIPs, adding new features and functionality across Kafka Core, Kafka Streams, and Kafka Connect. Highlights include: - Two new Docker images, next generation of the Consumer Rebalance Protocol, the ability to set compression levels for some codecs, and an easier way to to check if a metric is measurable - The ability to set task assignors in Kafka Streams - The ability to enforce the tasks.max configuration in Kafka Connect Get the full details in the announcement blog post from the release manager Josep Prat.

Continuing our Road to GA series towards the next major releases in the Spring portfolio: Share Consumer (Kafka Queues) in Spring for Apache Kafka 4.0 Apache Kafka 4.0 introduces Share Groups as a complementary consumption model. Unlike traditional consumer groups that assign partitions, Share Groups distribute individual records across consumers. This post covers:  • How the two consumption models differ  • When to use Share Groups vs traditional consumer groups  • Getting started with @KafkaListener and programmatic configuration  • Explicit acknowledgment and concurrency support Share Groups are currently in preview in Kafka 4.1.0 and expected to reach production-ready status in Kafka 4.2.0. Spring for Apache Kafka 4.0 provides full support for Share Groups. Read the post: https://lnkd.in/gsZKbM8N

A practical demonstration of KIP-1111: Enforcing Explicit Naming for Kafka Streams Internal Topics - showcasing why explicit naming of internal resources is crucial for production-ready Kafka Streams applications. #apachekafka https://lnkd.in/dvEeSQmj