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Article . 2021
License: CC BY
Data sources: Datacite
ZENODO
Article . 2021
License: CC BY
Data sources: Datacite
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Advanced Logging Techniques Using Log4j and SLF4J for Debugging in Enterprise Applications

Authors: Bhargavi Tanneru;

Advanced Logging Techniques Using Log4j and SLF4J for Debugging in Enterprise Applications

Abstract

Efficient debugging and monitoring are crucial for maintaining enterprise applications. Log4j and SLF4J are widely adopted logging frameworks in Java-based applications that enhance logging capabilities and facilitate debugging. This paper explores advanced logging techniques using these frameworks, addressing key issues such as log management, performance optimization, and security considerations. The study highlights structured logging, asynchronous logging, and best practices for effective debugging in large-scale enterprise environments. Additionally, we discuss logging strategies for microservices, best practices for log retention, and integration with observability tools. The impact of these techniques on system maintainability and performance is also discussed in depth.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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