• GuidesJava Profile Picture

    Java Guides @GuidesJava

    12 months ago

    Apache Kafka has become the de facto standard for building real-time data pipelines and streaming applications. As a distributed event streaming platform, it has revolutionized  how companies handle data flows. Let's dive into what makes Kafka tick. Key Concepts: 1. Topics: • Think of these as categories or feed names • Messages are published to topics • Can have multiple partitions for parallelism 2. Partitions: • Ordered, immutable sequence of records • Each record assigned a sequential ID (offset) • Enables massive scalability 3. Producers: • Publish messages to topics • Can choose which partition to send messages to 4. Consumers: • Subscribe to topics and process the messages • Track their position (offset) in each partition 5. Brokers: • Kafka servers that store and manage topics • A cluster typically has multiple brokers for fault tolerance 6. KRaft: • Manages the Kafka cluster • Tracks broker health, topic configuration, and more How It All Connects: 1. Message Flow: Producer → Broker → Consumer 2. Partition Leadership: • Each partition has one leader broker and multiple replicas • Writes go to the leader, replicas stay in sync 3. Consumer Groups: • Multiple consumers can work together • Each partition is read by only one consumer in a group 4. Offset Management: • Consumers commit their offset after processing • Enables restart from last position if a consumer fails 5. Retention: • Messages can be retained for a configured time or size • Enables replay and catch-up scenarios Key Features: • High Throughput: Can handle millions of messages per second • Fault Tolerance: Replication ensures data safety • Scalability: Easy to scale out by adding more brokers • Low Latency: Sub-10 ms latency in production environments • Durability: Data persisted to disk, surviving broker failures Use Cases: • Event Sourcing • Log Aggregation • Stream Processing • Metrics Collection • Activity Tracking Kafka's architecture enables decoupling of data streams and systems. This makes it invaluable for building real-time data pipelines and streaming applications. Pro Tip: When designing Kafka-based systems, carefully consider your partitioning strategy. It's crucial for performance and scalability. Credit: Brij kishore Pandey

    1 82 341 15K 305
    Download Gif
  • itsraghz Profile Picture

    Raghavan @ Saravanan @itsraghz

    12 months ago

    @GuidesJava @SaveToNotion #tweet #kafka

    0 0 0 198 0
  • Download Image
    • Privacy
    • Term and Conditions
    • About
    • Contact Us
    • TwStalker is not affiliated with X™. All Rights Reserved. 2024 www.instalker.org

    twitter web viewer x profile viewer bayigram.com instagram takipçi satın al instagram takipçi hilesi twitter takipçi satın al tiktok takipçi satın al tiktok beğeni satın al tiktok izlenme satın al beğeni satın al instagram beğeni satın al youtube abone satın al youtube izlenme satın al sosyalgram takipçi satın al instagram ücretsiz takipçi twitter takipçi satın al tiktok takipçi satın al tiktok beğeni satın al tiktok izlenme satın al beğeni satın al instagram beğeni satın al youtube abone satın al youtube izlenme satın al metin2 metin2 wiki metin2 ep metin2 dragon coins metin2 forum metin2 board popigram instagram takipçi satın al takipçi hilesi twitter takipçi satın al tiktok takipçi satın al tiktok beğeni satın al tiktok izlenme satın al beğeni satın al instagram beğeni satın al youtube abone satın al youtube izlenme satın al buyfans buy instagram followers buy instagram likes buy instagram views buy tiktok followers buy tiktok likes buy tiktok views buy twitter followers buy telegram members Buy Youtube Subscribers Buy Youtube Views Buy Youtube Likes forstalk postegro web postegro x profile viewer