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10 Best Practices for Log Management and AnalyticsSet a Strategy. Don't log blindly.Structure Your Log Data.Separate and Centralize your Log Data.Practice End-to-End Logging.Correlate Data Sources.Use Unique Identifiers.Add Context.Perform Real-Time Monitoring.More items...?Oct 15, 2015

Log management is the process of handling log events generated by all software applications and infrastructure on which they run.Logging has become an integral part of any DevOps team.

Log Management Software are tools that deal with a large volume of computer-generated messages. It is also known as event logs, audit trails, and audit records. These software generally deal with log collection, storage, retention, rotation, analysis, searching, and reporting.

Log management is the practice of continuously gathering, storing, processing, synthesizing and analyzing data from disparate programs and applications in order to optimize system performance, identify technical issues, better manage resources, strengthen security and improve compliance.

Logging is generally categorized into two categories: selective and clear-cutting. Selective logging is selective because loggers choose only wood that is highly valued, such as mahogany. Clear-cutting is not selective.

A Log Management System (LMS) is a software solution that gathers, sorts and stores log data and event logs from a variety of sources in one centralized location.

Log management is the collective processes and policies used to administer and facilitate the generation, transmission, analysis, storage, archiving and ultimate disposal of the large volumes of log data created within an information system.Log management software automates many of the processes involved.