There is multiple reasons. All types are logging messages support not only string msg. We can use parametrized variables for logging Support advance filter for logging like (Data, Markers, Regular Expression) Support Plugin Architecture (We just use the dependency and Layout configuration with minimal config, and this will start to work) Integration support with application server Could enable.
IBM Log Analysis with LogDNA is well suited if you are using other IBM cloud product ecosystems. It's very mature and supports HIPAA-compliant configurations if you need to store PI/PHI data. We particularly use it for audit requirements but understand the limitation with the retention period is for 30 days only. Also you need to configure if your IBM cloud service doesn't have any log collection or report tool. Log collection agents are widely supported for most of infrastructure in cloud.
The ability to customize logging levels and manage log files is superior to other products we have looked at; due to this we selected to go with log4j.
If you use other IBM product ecosystems, IBM Log Analysis with LogDNA is the obvious choice, as it supports seamless integration and better access control with IBM cloud access group setups. IBM Log Analysis with LogDNA was flexible and has wide support for various infrastructure implementations and is also controlled by the same IAM access setup. It can be configured for any IBM cloud services or platform logs or for infrastructure by installing the agent.
Most of IBM cloud services support easier integration for log analysis.
We are able to achieve compliance with various audit log reports, which improves governance and control over various cloud resources we have.
Also IBM Log Analysis with LogDNA helps in troubleshooting and analysis for application logs in real time. This helps with improved issue resolution timings.
