Engineering Scalable Log Aggregation and High-Cardinality Incident Dashboards for Distributed Microservice Architectures

Authors: Anupam Ojha

DOI: https://doi.org/10.37082/IJIRMPS.v9.i3.233028

Short DOI: https://doi.org/hbtwcz

Country: United States

Full-text Research PDF File:   View   |   Download

Abstract: The transition from monolithic architectures to distributed microservices has introduced a "visibility tax," where the overhead of understanding system behavior often exceeds the complexity of the features being built. Traditional centralized logging mechanisms frequently collapse under the volume of high-cardinality telemetry generated by short-lived containers. This paper proposes a robust framework for log search and incident response based on a tiered-indexing strategy and metadata-driven correlation. Drawing from over a decade of experience in high availability backend engineering, I detail a system design that leverages asynchronous ingestion via Kafka and enrichment filters in Java to bridge the gap between raw text logs and actionable operational intelligence. Experimental validation demonstrates that the proposed architecture reduces Mean Time to Resolution (MTTR) by 42% while maintaining a 30% lower storage footprint compared to standard ELK implementations.

Keywords: Microservices, Observability, Log Aggregation, Distributed Tracing, Site Reliability Engineering (SRE), Java Backend, Scalability, Incident Response.

Paper Id: 233028

Published On: 2021-05-07

Published In: Volume 9, Issue 3, May-June 2021

Share this