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Best Logging Practices: 14 Do’s and Don’ts for Better Logging

Ever found yourself drowning in a sea of log data, struggling to make sense of the overwhelming noise? Or perhaps faced a major system breakdown, only to find that your logs didn’t provide the answers you needed, leaving you in the dark?

Effective logging is a critical yet often overlooked aspect of software development and operations, highlighting why logging is important – it’s the foundation upon which observability, troubleshooting, and system maintenance are built. 

Without a well-defined logging strategy, you risk flying blind, unable to diagnose issues, ensure compliance, or gain valuable insights into your system’s behavior. This underscores the need to implement best logging practices to maintain clarity and efficiency in your logging efforts.

In this comprehensive guide, we’ll explore the essential log management strategy, logging techniques, and best logging practices that will, if implemented, transform your logging efforts into a powerful tool for maintaining observable systems.

Define Your Logging Goals 

Without clearly defined logging goals, your logging efforts may become haphazard and fail to capture the information you truly need. Aimless logging can lead to noise, wasted resources, and missed opportunities for valuable insights. 

Therefore, it’s crucial to determine the primary objectives of your logging efforts, such as debugging, auditing, performance monitoring, compliance, or security purposes – to ensure the best logging practices.

Prioritize your logging requirements based on criticality and potential impact, ensuring that the most important information is captured effectively. Also, regularly review and update your logging goals as your systems evolve, allowing you to adapt to new requirements in an ever-changing digital landscape.

Embrace Log Levels

Leverage lower log levels (e.g., DEBUG, TRACE) judiciously, as these logging methods can provide valuable context but enabling them continuously can result in excessive log data. 

While these log levels can offer granular insights into the inner workings of your applications, enabling them continuously can result in an excessive volume of log data, leading to increased costs and noise that obscures critical information. 

Debug and trace logs should be enabled selectively, typically when troubleshooting specific issues that require deep inspection. 

Focus On Structured Logging 

Structured logs are paramount for effective analysis and management at scale. Unstructured, free-form logs are, on the other hand, notoriously difficult to parse and analyze, hindering log correlation, and integration with log management tools, making it harder to gain useful insights from your logs.

To overcome these challenges, it’s essential to adopt a consistent and structured log format across your applications and services. Implementing best logging practices involves adopting a consistent and structured log format across your applications and services. Implement a well-defined schema following industry-recognized log format standards for essential metadata like timestamps and log levels.

Leveraging structured logging libraries or frameworks can greatly promote standardization and ensure adherence to your chosen format. Embracing best logging practices for structured logging leads to simplified log analysis, enabling advanced filtering and search capabilities. Structured logs facilitate seamless integration with log management tools like Sematext, so you can better understand what’s going on with your system and make the most of your logs.

Learn more: 8 Best Practices for Better Readability

Log For Context

Logs aren’t very helpful for troubleshooting and analysis. 

Without relevant contextual details, it becomes difficult to recreate the state of your systems and identify the root cause of issues. To enhance the interpretability and value of your logs, you should enrich them with pertinent contextual information.

Capture diagnostic data that can assist in troubleshooting and root cause analysis, such as user identities, request details, environment variables, and relevant stack traces and exception details for error scenarios. 

Sample Strategically

Logging every single event can overload your logging system fast, causing it to slow down, cost more to store data, and make analyzing logs a pain. To deal with these issues, it’s a good idea to use log sampling methods that only collect a portion of the events, giving you a good picture without all the extra hassle. Strategic sampling is a cornerstone of best logging practices, allowing you to balance the need for comprehensive insights with the realities of system performance and cost.

You can also change how much you sample depending on how busy your system is or how important the events are. This not only saves you money on storage but also makes it easier to analyze your logs quickly and efficiently, so you can focus on what’s important. 

Embrace the Power of Correlation

In distributed systems, treating each log entry as an isolated event makes it nearly impossible to reconstruct end-to-end request flows. It also makes it difficult to trace issues across multiple components. 

To overcome this challenge, leverage log correlation techniques that connect related log events across your distributed systems. Assign unique request or transaction identifiers that span multiple components or services, enabling you to track and correlate log events associated with a specific request or transaction. This technique is a key element of best logging practices in complex, distributed environments.

Log Rotation is Your Friend

Neglecting log rotation can lead to unbounded log growth, potentially consuming all available disk space and impacting system performance or availability. To prevent such issues, it’s crucial to implement a robust log rotation strategy to manage log file growth and retention. 

Rotate your logs based on predefined size or time constraints, adhering to best logging practices to prevent unbounded growth while maintaining historical data as needed.

This ensures that your log files don’t continue expanding indefinitely, consuming valuable disk space. Archive older logs for long-term retention and compliance purposes, ensuring that log data should be kept as needed while freeing up space for new log entries.

Automate Alerting

Relying solely on manual log inspection is a recipe for missed issues and delayed incident response. Without automated alerting, critical log events may go unnoticed until it’s too late, potentially leading to significant consequences.

To avoid such scenarios, integrate your logging infrastructure with alerting and monitoring systems. Define alert rules based on specific log patterns or predetermined thresholds, such as error rates or response times. Automated alerting is an essential aspect of best logging practices, ensuring proactive detection and timely remediation of potential issues.

Get Your Team on Board

If best logging practices are not consistently followed across your team or organization, you risk introducing fragmentation, maintainability challenges, and a lack of shared understanding of your systems. To minimize these risks, it’s essential to promote a culture of best logging practices within your entire team and organization.

Provide training and documentation to ensure that everyone adheres to consistent logging practices. Encourage peer review and knowledge sharing, fostering an environment where your logging strategy can continuously improve through collaboration and shared insights.

Don’t Log Everything

Logging every tiny aspect of your application can flood you with more logs than you can handle. 

This makes it hard to manage and costs a lot to store and analyze. Instead, be selective about what you log. More unnecessary detail can slow things down, cost you more money, and clutter up your logs, making it easier to find the important stuff.

Instead of logging everything without thinking, take the time to define your logging goals and decide if each log message is needed and valuable. Find a balance between being transparent, giving enough info to see what’s going on and fixing problems, and being efficient so your logging keeps up your systems and costs manageable. Sematext’s log pipelines can streamline this process by filtering out extraneous log data, saving you valuable time and resources.

Don’t Log Sensitive Data

Logging sensitive information such as passwords, credit card numbers, or personally identifiable information (PII) can have severe consequences. It can lead to data breaches, regulatory violations, and significant legal and financial repercussions. Therefore, it is crucial to never log sensitive data. 

Let me repeat that once again – never log sensitive data.

Adopting best logging practices involves methods to hide or disguise private information before it gets logged. This can include techniques like masking, truncation, or encryption, ensuring that sensitive information is never stored in plain text within your logs.

Learn more: Keep Sensitive Data Out of Your Logs

Don’t Ignore Performance Impact

Excessive logging can impose a substantial performance overhead, especially in high-throughput or latency-sensitive systems. Ignoring the performance impact of logging can be a critical mistake. It can result in significant overhead, increased latency, and potential degradation of your application’s responsiveness or throughput.

It is essential to monitor and optimize the performance impact of your logging practices to ensure that your logging efforts do not come at the cost of system performance. Implementing strategies such as log buffering, asynchronous logging, or log sampling are among the best logging practices to mitigate potential performance degradation caused by excessive logging.

Don’t Neglect Log Security

Treating logs as disposable or non-sensitive data can expose your organization to significant security risks. These include unauthorized access, data exfiltration, or tampering. 

Restrict log access by implementing role-based access controls (RBAC), ensuring that only authorized personnel can view and manage log data. Additionally, encrypt log data both in transit and at rest, especially when dealing with sensitive information, to prevent unauthorized access or data breaches. Regularly audit and review log access and retention practices to identify and address potential security vulnerabilities or policy violations, following security logging best practices.

Don’t Treat Logs as a Silver Bullet

Logs are an invaluable resource for troubleshooting, debugging, and understanding system behavior, but relying solely on logs for monitoring and observability can leave you blind to other critical aspects of your system’s performance and health. 

Logs provide valuable diagnostic information, but they should not be treated as a panacea for all monitoring and observability needs.

It’s important to complement your logging strategy with other monitoring techniques, such as metrics, events, and profiling, to gain a holistic view of your systems.

Adopting a comprehensive approach that combines logging and monitoring best practices is essential for achieving optimal observability and system health. Tools like Sematext can assist you in centralizing and correlating various data sources, including logs, metrics, and events providing a unified view of your system’s health and performance. 

Final thoughts 

Remember, logging is not a one-size-fits-all solution. 

It requires a tailored approach that aligns with your organization’s unique needs, applications, and infrastructure. Continuously evaluate and refine your logging strategy, fostering a culture of continuous improvement and knowledge sharing within your team.

In the end, best logging practices give you clarity, background, and deep insight into how your systems work. Use them wisely, and you’ll be ready to handle even the toughest problems with certainty and effectiveness.

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