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Today in this article, we will see Application Logging Best Practices and guidelines.

Logging is an important NFR (non-functional requirement) and is a fundamental practice in software development and operations.

Logging provides valuable information that aids in identifying and resolving issues within an application.

When an error or unexpected behavior occurs, logs can help pinpoint the cause by capturing relevant context information, exception details, stack traces, and variable values.

This assists developers in understanding the root cause and facilitates efficient debugging and troubleshooting.

It helps developers, operations teams, and organizations gain visibility into application behavior, troubleshoot issues, monitor performance, ensure compliance, and drive continuous improvement.

By leveraging logs effectively, organizations can enhance application reliability, user experience, and operational efficiency.

Let’s go through the below aspects of logging,

When it comes to logging here are some best practices to follow:

Use a Logging Framework

Utilize a robust logging framework to log your application’s information.

Leverage any inbuilt framework-provided logging features like console logging etc.

Example – If using .NET then one can use an inbuilt logging framework or external providers like Serilog, NLog, or log4net to handle logging in to your .NET application.

These frameworks provide various features, configuration options, and integrations with other logging tools.

Log Important Events

Log critical events, errors, exceptions, warnings, and information that can help in troubleshooting and debugging your application.

Include relevant context information, such as timestamps, request/response details, user IDs, and application-specific data.

Configure Logging Levels

Set appropriate logging levels to control the amount of information logged.

Use different levels like below to distinguish between different types of log messages.

• Debug,
• Info,
• Warning,
• Error, and
• Fatal

Adjust the log levels based on the importance and verbosity needed for different environments (e.g., development, staging, production).

Logging PII data? – be careful

PII refers to any information that can be used to identify an individual, such as names, addresses, social security numbers, or financial data.

Logging Personally Identifiable Information (PII) data can pose significant risks and is generally considered a bad practice.

Logging PII data increases the risk of exposing sensitive information in case of a data breach or unauthorized access.

Storing PII in logs makes it a target for attackers, potentially leading to identity theft, fraud, or other malicious activities.

By adopting a privacy-centric approach and ensuring that logging practices align with data protection regulations and best practices, organizations can better safeguard user privacy, maintain compliance, and mitigate potential security risks associated with logging PII data.

Log-Structured Data

Log structured data instead of plain text messages.

Use structured logging techniques like JSON or key-value pairs to allow easier parsing, filtering, and analysis of log data.

This can enhance log searchability and enable efficient log processing and analysis.

Implement Log Rotation and Retention

Configure log rotation and retention policies to manage log file sizes and storage. Rotate logs periodically or based on size or time, and define retention periods to ensure logs are retained for an appropriate duration. This helps manage disk space and facilitates log analysis over a specified time range.

Consider Log Enrichment

Enrich log entries with additional contextual information that can assist in troubleshooting and analysis.

Add relevant details like user session information, machine or environment metadata, correlation IDs, or request-specific data to facilitate end-to-end log analysis.

Centralize Log Management

Send logs to a centralized logging service or tool for aggregation, storage, and analysis. This simplifies log monitoring, analysis, and troubleshooting across multiple instances or environments. Popular options include ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, or cloud-based log management services.

Include Log Filtering

Implement log filtering mechanisms to control the volume of logs generated.

Filter out noisy or irrelevant log messages based on criteria such as log level, specific loggers, or specific log message content.

This helps reduce log clutter and focuses on important log entries.

Monitor and Alert on Logs

Set up log monitoring and alerting to receive notifications for critical events or errors.

Configure alerts based on specific log patterns or error thresholds.

This allows proactive identification of issues and enables timely response and troubleshooting.

Regularly Review Logs

Regularly review and analyze logs to identify patterns, trends, or anomalies.

Log analysis can provide insights into application behavior, performance, and potential issues.

Use log analysis tools or visualizations to gain actionable insights from your log data.

Continuous Improvement and Feedback

Analyzing logs over time provides insights into application usage, user behavior, and feature usage.

This information can guide product development, user experience enhancements, and business decision-making.

By understanding how users interact with the application through log analysis, organizations can make data-driven improvements and iterate on their products or services.

Following these logging best practices helps in effective troubleshooting, debugging, and monitoring of your applications, enhancing overall application quality and maintainability.

Logging security events

It’s essential to log events that provide insight into potential security threats, anomalies, or unauthorized activities within your application or system.

Here are some key security-related events that you should consider logging,

Example

• Successful and failed login attempts if any
• Account lockouts and unlock events if any
• Password change/reset requests if any

Benefits of logging

• Debugging and Troubleshooting
• Performance Monitoring and Optimization:
• Auditing and Compliance:
• Application Monitoring and Alerting
• Performance Analysis and Capacity Planning
• Historical Analysis and Forensics
• Compliance with Service Level Agreements (SLAs)

Do you have any comments or ideas or any better suggestions to share?

Please sound off your comments below.

Happy Coding !!

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