Using Logstash for Real-Time Log Analysis in Cloud-Based Applications

Abstract

Real-time log analysis is crucial for monitoring, troubleshooting, and optimizing cloud-based applications. Logstash, a component of the Elastic Stack, plays a significant role in collecting, processing, and forwarding logs to various storage and analysis systems. This paper explores the architecture, implementation, and benefits of using Logstash for real-time log analysis in cloud environments. We discuss challenges, best practices, and integrations with other tools such as Elasticsearch and Kibana for effective log visualization. Additionally, we examine Logstash's scalability, flexibility, and ability to handle large volumes of data in dynamic cloud environments. By leveraging Logstash, organizations can improve system reliability, enhance security monitoring, and optimize operational efficiency. The study also addresses the impact of Logstash on modern DevOps workflows and how it contributes to proactive system management in distributed architectures.