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     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN: (Print) | 2582-7138 (Online) | Impact Factor: 9.54 | Open Access

Best Practices for Logging and Monitoring Big Data Pipelines with Grafana

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Volume: 6 | Issue: 3 | Pages: 835-836

Subject: Engineering

Country: United States

DOI: https://doi.org/10.54660/.IJMRGE.2025.6.3.835-836

License: CC BY 4.0

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Abstract

Comprehensive logging and real-time monitoring are critical for ensuring pipeline reliability, performance, and rapid troubleshooting in large-scale data engineering environments. Grafana—together with metrics stores such as Prometheus or AWS Timestream, and log backends like Grafana Loki—offers a unified platform for observability. This article surveys best practices for instrumenting big data pipelines—covering logging strategies, metrics collection (including Timestream as a long-term time-series store), alerting, and dashboard design—and illustrates how Grafana’s ecosystem enables end-to-end visibility.

How to Cite This Article

Ujjawal Nayak (2025). Best Practices for Logging and Monitoring Big Data Pipelines with Grafana . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 6(3), 835-836. DOI: https://doi.org/10.54660/.IJMRGE.2025.6.3.835-836

Publication Information

Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

Publisher: Anfo Publication House

ISSN: (Print), 2582-7138 (Online)

Frequency: Bimonthly

Language: English

Open Access: Yes - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

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