Logging Levels Explained For Beginners
Logging is essential for software development and troubleshooting because it captures and records information about an application’s behavior and events. Commonly there are five levels in logging. To productively handle the log data, we use different logging levels to classify and prioritize.
- DEBUG
The lowest and most elaborated level of logging is DEBUG, in which developers provide precise information those are typically used during development or we can say the developer can trace the flow of the program using debugging. Generally, these debug-level messages are trivial and can be safely disabled while the software is going for production.
2. INFO
Generally, basic working information about an application’s normal behavior is labeled in INFO, these are used to convey important milestones and significant events of the program. These messages are typically enabled when software is in the production environment to keep a check on the application’s condition.
3. WARN(WARNING)
WARN/WARNING messages hints that there are potential issues or situations which may cause problems in the near future. Non-fatal errors, unexpected conditions, and exceptional scenarios can be highlighted in this level of logging.
4. ERROR
Critical issues or errors which might impact the functionality of software are kept in the ERROR logging level. Even though they may not cause the software to terminate, problems that are logged should still be addressed promptly. ERROR logs are often generated when an exception or failure occurs in a software application.
5. FATAL / CRITICAL
The highest and most severe logging level is FATAL, which indicates information about catastrophic errors that cause the application to terminate or become completely a failure. These logs are essential for quickly identifying and resolving critical issues.
Above are the major Logging level and choosing the right logging level depends on the purpose of your software.
To make the most of your logging strategy, consider the following best practices:
i. Use clear, concise, and descriptive log messages that include relevant contextual information, timestamps, and any additional data that might be helpful during analysis.
ii. Implement log monitoring and alerting mechanisms to proactively identify and respond to critical issues. Set up log analysis tools or services that can detect anomalies, trigger alerts, and help you troubleshoot problems quickly.
iii. Use log filtering and aggregation tools to focus on the most important log messages, and to centralize log data from various sources. This will make it easier to analyze and detect patterns.
At last, Logging levels are important for capturing and organizing log data effectively. By understanding the purpose and characteristics of each logging level, developers can implement a logging strategy that helps to troubleshoot applications, analyze performance, and detect errors. Choosing the right logging level and following best practices can significantly improve your ability to diagnose and resolve issues in a timely manner, leading to more stable and reliable software systems.