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One Final Commit for the Last Sprint

Setting Up Standalone Kafka with Docker Compose: Including UI, JMX Exporter, and Monitoring

Kafka Terminology Overview Before diving into deployment, it's essential to understand core Kafka concepts such as brokers, topics, partitions, producers, consumers, and replication. These are well-documented in the official Apache Kafka documentation and Confluent’s developer resources. Selecting a...

Using Kafka and Flink for Real-Time Data Processing

Implementing a Kafka Producer Below is a Java-based Kafka producer implementation that sends data to a Kafka topic on a scheduled basis: @Configuration @Slf4j public class ScheduledDataProducer extends Thread { public static final String BROKER_URL = "your_broker_ip:9092"; public static fi...

Big Data Components Installation, Configuration Files, and Service Management Commands Guide

Flume Remove conflicting JAR file: rm /opt/module/flume/lib/guava-11.0.2.jar Launch Flume monitoring: bin/flume-ng agent -n a1 -c conf/ -f job/flume-file-hdfs.conf Stop Flume monitoring: # Terminate process using ps -ef command ps aux | grep flume kill <process_id> Hadoop (Cluster) Configurati...

Understanding Kafka's Core Architecture and Performance Characteristics

Understanding Kafka's High Throughput Kafka achieves exceptional throughput through several architectural decisions: Append-only writes: Kafka messages are written sequentially to log files, eliminating the need for random disk I/O operations which are significantly slower. Zero-copy technology: Uti...

Integrating Kafka and Storm with Spring Boot

Kafka and Storm Overview If you are familiar with Kafka and Storm, you can skip this section. If not, you can refer to my previous blog posts. Environment Setup for Kafka and Storm Link: http://www.panchengming.com/2018/01/26/pancm70/ Usage of Kafka Link: http://www.panchengming.com/2018/01/28/pancm...

Configuring Kafka Consumer Retry with Maximum Attempts and Backoff Interval

Scenario When we have a functionality that must operate independently of the database—meaning that if the database goes down, data remains unaffected, and once the database is restored, data is written correctly—the client should experience no disruption. With this clear objective, let's implmeent i...

Redis, Kafka, and ZooKeeper Core Concepts and Common Interview Questions

Redis Performence and Persistence Redis achieves high read/write speeds through: In-memory storage: Data resides entirely in RAM, enabling faster access compared to disk-based systems. Single-threaded model: Eliminates context-switching and lock contention overhead, simplifying concurrency control....

Securing Apache Kafka with SASL-PLAIN Authentication and ACL Authorization

Core Security ConceptsSASL (Simple Authentication and Security Layer): Handles identity verification during client-to-server connections, ensuring credential data is handled securely.SSL/TLS: Encrypts the data transmitted over the network. Relying on SASL alone leaves the payload unencrypted after a...

Securing Apache Kafka with SASL/PLAIN Authentication and Spring Boot Client Integration

Enabling SASL/PLAIN Authentication in Kafka 2.4.0 To protect Kafka clusters exposed to untrusted networks, SASL/PLAIN authentication—paired with TLS ancryption—is implemented for secure client and inteer-broker communication. Broker-Side JAAS Configuration Create a JAAS configuration file (e.g., kaf...

Integrating Apache ZooKeeper with Apache Kafka for Distributed Coordination and Messaging

Apache ZooKeeper serves as a centralized coordination service for distributed systems, enabling reliable configuration management, naming, synchronization, and group services. It operates as a hierarchical key-value store with strong consistency guarantees and event-driven notifications. ZooKeeper c...