Google Cloud End to End Data Engineering Projects - 1.2 Billion Records Per Hour High Performance Kafka and Spark - End to End Data Engineering Project

PART 2: https://youtu.be/I2K6uCpxL8E Ever wondered how to process 1 billion records per hour seamlessly? In this video, we break down the architecture and tools to make it happen: ✅ Apache Kafka: The backbone of real-time data streaming. ✅ Apache Spark: Lightning-fast processing for massive data pipelines. ✅ ELK Stack: Gain visibility with Elasticsearch, Logstash, and Kibana. ✅ Grafana & Prometheus: Real-time monitoring and performance insights. ✅ Kafka Schema Registry & Control Center: Streamlined management and schema validation. 🎯 What You'll Learn: ✅ How to design a robust architecture for high-throughput data pipelines. ✅ Insights into Python vs. Java Kafka Producers: Which one performs better? ✅ Real-time logging, monitoring, and debugging strategies. 🔥 Why This Matters: If you're in data engineering or want to level up your skills, this video showcases everything you need to build, monitor, and scale an ultra-high-performance streaming platform. Timestamps: 0:00 Introduction 2:31 High Level Architecture Whiteboard 12:55 Data Storage Estimation with workings! 29:33 Clean Architecture 30:39 System Architecture 36:27 System Architecture Setup and Coding 58:21 Python Producer 😩 1:29:27 Java Producer (yay! 😁) 1:33:17 300,000 records per second! 1:36:21 Apache Spark Consumer 2:03:50 Spark Job Optimisation and Statistics 2:15:26 Cluster Health issues 2:15:38 Part 1 Outro 👀 Don't just watch, build it! 🚧 👍 Like, Comment, & Subscribe for more cutting-edge data engineering content! Resources: Full Source Code: https://buymeacoffee.com/yusuf.ganiyu/1-2-billion-records-per-hour-high-performance-kafka-spark-end-end-data Kafka Documentation: https://kafka.apache.org/documentation/ Apache Spark Documentation: https://spark.apache.org/documentation.html #ApacheKafka, #ApacheSpark, #DataEngineering, #BigData, #RealTimeProcessing, #ELKStack, #Grafana, #Prometheus, #KafkaStreams, #BigDataAnalytics, #DataPipeline, #StreamingData, #KafkaMonitoring, #SparkStreaming, #DataArchitecture, #HighPerformanceComputing