Logging Best Practices

Logging is an essential aspect of application development, monitoring, and troubleshooting. Effective logging helps teams identify issues quickly, understand application behavior, and track performance metrics.

Let’s cover logging best practices you may encounter inside your Bullhorn software to ensure your application logs are both informative and actionable.

Include Sufficient Context in Logs

Logs should provide enough context to understand the event without needing to reproduce the issue. This includes information such as:

Timestamps: Include precise timestamps to track when events occurred.
Error Messages: Provide clear, concise error messages with detailed explanations.
Request/Transaction IDs: Use unique identifiers for user requests or transactions to trace logs across multiple systems.
User Context: Log user information where relevant (e.g., user ID, roles), especially when debugging user-specific issues.
Stack Traces: When logging errors, include the stack trace for better debugging, but ensure they are sanitized to avoid exposing sensitive internal details.

Avoid logging sensitive information such as passwords, credit card numbers, or API keys. If sensitive information must be logged, ensure it is redacted or hashed.
Ensure logs are standardized, allowing for easy parsing and analysis.

Avoid Over-Logging

While it’s important to include relevant information, excessive logging can lead to performance issues, storage bloat, increased storage cost and difficulty in identifying meaningful events.

Log events that provide value for monitoring, debugging, or auditing.
Regularly review and prune your log entries to ensure they remain relevant and avoid unnecessary verbosity.
Use log rotation to manage log file size and archiving.

Debug Logs & Their Impact

DEBUG logs are valuable during development and troubleshooting, as they provide detailed insights into the internal workings of the application. However, when DEBUG-level logging is left enabled in production, it can quickly lead to problems:

Log File Growth: DEBUG logs are typically very verbose, including detailed information about function calls, variables, system states, and stack traces. This can result in rapid log file growth, consuming large amounts of storage space.
Performance Degradation: Writing extensive DEBUG-level logs introduces additional I/O operations, which can negatively impact application performance, especially in high-throughput systems. This can lead to slower response times and increased latency.
Storage Costs: Storing unnecessary DEBUG logs for long periods increases storage costs, especially when logs are stored in cloud environments or third-party logging services.

Why This Causes Issues

Scalability: As the application scales, more instances or microservices will contribute to the DEBUG log volume, further exacerbating the issue.
Resource Consumption: Excessive logging consumes both storage and CPU resources, leading to potential system slowdowns, especially during high-load periods.

Disable DEBUG-level logging in production unless it is absolutely necessary. If detailed logs are needed for troubleshooting, consider using logging levels like INFO or WARN to capture essential events without overwhelming the system.
Log at appropriate levels for different environments: Use DEBUG for development, INFO for production, and only use ERROR or FATAL for critical issues.
Implement log rotation and archiving to manage log storage efficiently and avoid filling up your disks with unnecessary data.

By being mindful of how much information is logged at the DEBUG level, you can ensure your logging system remains efficient and scalable without sacrificing the ability to diagnose issues.

Log Retention & Cleanup

Logging systems can generate large amounts of data over time. Setting up proper log retention policies ensures logs are kept for the required period and cleaned up automatically after they’re no longer needed.

Define log retention periods based on regulatory requirements and business needs (e.g., 30 days, 90 days).
Set up automatic log cleanup to prevent storage from growing uncontrollably.

Regularly Review & Improve Logging

Logging is not a "set it and forget it" task. As the application evolves, the logging strategy should also be updated.

Regularly audit your logging practices to ensure they remain effective as the system grows.
Continuously gather feedback from developers and support teams to improve the quality of logs.
Use log analysis to identify recurring issues and adjust logging levels as needed.