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Alibaba Cloud EventHouse is now in public preview! 🚀 With EventHouse, EventBridge now completes the serverless event ecosystem: EventBus EventStreaming EventHouse. 👉 Public preview: int.alibabacloud.com/m/10004… 👉 Blog: int.alibabacloud.com/m/10004…

Apache Kafka faces a critical OAUTHBEARER bypass (CVE-2026-33557) and sensitive logging leaks. Secure your data pipelines—patch to v4.1.2 or v4.2.0 today. #ApacheKafka #CyberSecurity #InfoSec #JWT #DataSecurity #ZeroTrust #EventStreaming securityonline.info/apache-k…

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ChimeraMQ - Üç Başlı Canavar Uyanıyor Kafka RabbitMQ Pulsar = tek Go binary. 🦁 Queue Engine → RabbitMQ'yu replace eder 🐐 Stream Engine → Kafka'yı replace eder 🐍 Protocol Engine → AMQP MQTT WebSocket HTTP hepsi tek portta Özellikler: - Zero external dependency (sadece Go stdlib) - Unified Mode: aynı topic hem queue hem stream - Tiered Storage: Hot (mmap) → Warm (LSM-Tree) → Cold (zstd) - Built-in Schema Registry, WASM transforms, Stream Processing - Embedded Raft Gossip clustering 25MB binary. <1 saniye cold start. 1M msg/sec. github.com/chimeramq/chimera chimeramq.com #ChimeraMQ #Go #Golang #MessageQueue #EventStreaming #Kafka #RabbitMQ #NOFORKANYMORE #OpenSource

Is 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. softwaremill.com/compaction-… #ApacheKafka #DataEngineering #DistributedSystems #EventStreaming #Observability

Apache Kafka 4.2.0 is here – and it’s a big one. The headliner? Queues for Kafka (KIP-932) is officially GA. This means you can finally use Kafka for classic "competing consumer" queuing patterns without the rigid constraints of partition assignments. But there is much more: #ApacheKafka #Kafka42 #EventStreaming #DataEngineering #DistributedSystems

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Kafka isn’t a “queue.” It’s a distributed commit log that turns your microservices into a real-time system.⚡️ Producers write events → partitions give parallelism → offsets give replay → replicas give fault tolerance. That’s why Kafka powers payments, logs, analytics, and streaming at scale. #Kafka #DistributedSystems #BackendEngineering #EventStreaming #SystemDesign

One bad Kafka message can block a partition, explode lag, and kill throughput. Poison message ≠ retry forever. Retry ->DLQ -> fix -> replay. Keep the stream moving. 🚀 #Kafka #DLQ #EventStreaming #Kafka #EventStreaming #ApacheKafka #DLQ #PoisonPill #Microservices #EventDriven #DataEngineering #Streaming #DevOps

Check out my first trip to the lightboard, as I unpack "Queues for @apachekafka" #apachekafka #eventstreaming

Kafka vs RabbitMQ 🚀📬 Kafka: High-throughput, partitioned logs, designed for streaming & event-driven systems. Pull-based, keeps message history for replay. RabbitMQ: Traditional message broker, supports complex routing, push-based, ideal for low-latency task queues.Both help apps communicate asynchronously, but Kafka streams data; RabbitMQ queues tasks. Choose based on your use case! #Kafka #RabbitMQ #EventStreaming #Messaging

Discover the 4 core architectural decisions that make Apache Kafka process 2 million messages per second on commodity hardware. 🚀 What You'll Learn: Sequential disk writes vs random access performance impact Zero-copy optimization and kernel-level data transfer Batch processing and compression strategies that reduce network overhead Distributed partitioning for parallel processing scalability Page cache utilization for memory-efficient operations ⚡ Real-World Performance: Kafka achieves 2 million writes per second on three cheap machines, powering data pipelines at Netflix, LinkedIn, and Uber. Unlike traditional systems, Kafka writes everything to disk sequentially and consumers fetch data in order, making disk access always sequential instead of random. 🔧 Technical Deep Dive: Zero-copy principal: kernel moves data to sockets without application intervention OS pagecache optimization for standardized binary format throughout producer → broker → consumer flow Efficient batching format with compression support 📊 Why This Matters: Understanding these performance mechanisms helps you make informed trade-offs between latency, throughput, and resource utilization in distributed systems. Critical for architects designing high-scale event streaming platforms. #ApacheKafka #SystemDesign #EventStreaming #SoftwareArchitecture #Performance Secondary: #DataEngineering #DistributedSystems #TechTutorial #SoftwareEngineering #CloudArchitecture #StreamProcessing #MessageQueue #ScalableSystems #TechInsights #PerformanceOptimization Trending: #TechEducation #SoftwareDevelopment #BackendEngineering #CloudComputing #DataPipelines

📚️ New blog! Pulsar Newbie Guide for Kafka Engineers (Part 5) → Retention, TTL & Compaction. Learn how Pulsar handles storage differently from Kafka & how to manage backlogs latest state per key. Read here 👉 hubs.ly/Q03GJx7Z0 Stay tuned — Parts 6–10 of the series are coming soon! 🔥 #ApachePulsar #Kafka #DataStreaming #EventStreaming

🚀 Kafka vs AutoMQ: The Future of Event Streaming ✍️ By Abhishek Kumar | #FirstCrazyDeveloper 💡 Read my blog with real-world examples (Amazon, Spotify, Uber). firstcrazydeveloper.in/2025/… #Kafka #AutoMQ #EventStreaming #CloudNative #BigData #FirstCrazyDeveloper

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Kafka does real-time streaming but wasn't built as a database. Using it for long-term storage results in high costs and really complex querying. Kurrent adds the event-native database layer Kafka needs. 🔧 #eventstreaming #streaming kurrent.io/use-cases/superch…

🔥Tomorrow!
Join us to see how @Iterable uses #ApachePulsar to power real queues & agentic AI at scale. ✅ Queue-based workflows ✅ Pulsar vs Kafka, RabbitMQ, SQS
 ✅ Real-world AI use cases 🗓️ July 24 | 9AM PT
 🎟️ Register: hubs.ly/Q03yttWK0 #ApachePulsar #RealTimeData #AgenticAI #EventStreaming #StreamNative #Iterable