Apache Log4j vs. IBM Log Analysis with LogDNA

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.

Incentivized

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.

Incentivized

• Integration with java.
• Configure logging levels.
• Customize logging contents.

Incentivized

• Easier integration with other IBM cloud resources
• Flexible access control setup using RBAC
• Supports other infrastructure as well, like Kubernetes and VMs

Incentivized

• Fixed the vulnerability which is reported which affect many big brand.
• There should be security check to check all vulnerability.

Incentivized

• Ability to create KPI charts and metrics dashboards out of the box

Incentivized

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.

Incentivized

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.

Incentivized

• Good logging tools we can integrate with minimal resource consumption.
• Ease of understanding.
• Plugin play component Architecture.
• Advance filter support can be used to filter all types of logs and events, which can be further analyzed.

Incentivized

• 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.

Incentivized