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In this article, we show how to integrate Apache Kafka with Elasticsearch for data ingestion and indexing. We will provide an overview of Kafka, its concept of producers and consumers, and we will create a logs index where messages will be received and indexed through Apache Kafka. The project is implemented in Python, and the code is available on GitHub.
Prerequisites
- Docker and Docker Compose: Ensure you have Docker and Docker Compose installed on your machine.
- Python 3.x: To run the Producer and Consumer scripts.
Introduction to Apache Kafka
Apache Kafka is a distributed streaming platform that enables high scalability and availability, as well as fault tolerance. In Kafka, data management occurs through the main components:
- Broker: responsible for storing and distributing messages between producers and consumers.
- Zookeeper: manages and coordinates the Kafka brokers, controlling the state of the cluster, partition leaders, and consumer information.
- Topics: channels where data is published and stored for consumption.
- Consumers and Producers: while producers send data to the topics, consumers retrieve that data.