Setting Up Kafka with Debezium for CDC from MySQL and PostgreSQL to BigQuery on GKE

The objective of this project is to set up a Kafka ecosystem on Google Kubernetes Engine (GKE) to facilitate Change Data Capture (CDC) from MySQL and PostgreSQL databases. The captured data will be pushed to Kafka topics, and from there, it will be ingested into Google BigQuery for analytics and reporting purposes. Components Kafka: A distributed streaming platform for building real-time data pipelines and streaming applications. Kafka Connect: A tool for scalably and reliably streaming data between Apache Kafka and other systems. Debezium: A CDC tool that captures row-level changes in databases and streams them to Kafka topics. GKE: Google Kubernetes Engine, a managed Kubernetes service that simplifies deploying, managing, and scaling containerized applications. Setup Steps 1. Create GKE Cluster Cluster Name: my-kafka-cluster Number of Nodes: 6 Zone: us-central1-a 2. Deploy Kafka and Kafka Connect Namespace: kafka Use Strimzi Operator to deploy and manage the Kafka cluster. Deploy Kafka Connect with necessary configurations. 3. Install Debezium Connectors Install Debezium MySQL and PostgreSQL connectors on Kafka Connect. 4. Configure MySQL and PostgreSQL for CDC Ensure MySQL and PostgreSQL databases are configured to allow Debezium to capture changes. 5. Setup Kafka Topics Create Kafka topics to receive the CDC data from MySQL and PostgreSQL. 6. Configure Kafka Connect to Push Data to BigQuery Use the Kafka Connect BigQuery sink connector to push data from Kafka topics to Google BigQuery.