Complete Guide to Setting Up ELK Stack with Kafka, Redis, Beats, and Spring Boot for Microservices Logging
Architecture diagram: Components Breakdown: Microservices 1, 2, and 3: These are the core applications responsible for generating logs. Logstash: Acts as a central log processor. It collects logs from the microservices, transforms them into a common format (usually JSON), and sends them to Elasticsearch. Elasticsearch: A powerful search engine that stores and indexes the logs received from Logstash. It allows for fast retrieval and analysis of log data. Kafka: A distributed streaming platform used to buffer and distribute logs from the microservices to Logstash. Kafka ensures reliability and fault tolerance in log handling. Redis: An in-memory data store used for caching, session management, and other purposes. Redis can help improve the performance and scalability of the application. Beats: A lightweight data shipper that can forward logs from the microservices to Logstash or Kafka. Beats is typically used for collecting logs from application files or other sources. Kibana: A data vis...