Error logs: Definition, types, and more

What is an error log?

An error log is a file generated by a computer system, program, or application to track any errors detected by the operating system module when the system, program, or application is running. This file is great for debugging, troubleshooting, and system optimization, as it gives you information about what the error was, when it happened, how critical it was, and so on.

In software development, error logs play a crucial role beyond just recording issues; they help support the development and operational workflows within the software development life cycle.

When it comes to software development, test logs are equally important as production code logs. “When a test fails, the log should clearly show whether the failure was a problem with the test or the production system. If it doesn’t, then test logging is broken.” This quote by Anthony Vallone from the Google testing blog highlights the importance of logging throughout every stage of the software development cycle.

Error logs help support the development and operational workflows within the software development life cycle.

Why do you need error logs?

Within the software development process, error logs are important because they:

• Ensure exceptions are caught, handled, and managed.
• Keep records for future analysis, thus improving both application reliability and debuggability.
• Provide the admin with a detailed view of an application’s behavior.
• Aid in troubleshooting and proactive monitoring of applications and systems.
• Support audit and compliance requirements by maintaining a historical record of issues.
• Help identify vulnerabilities and recurring inefficiencies for optimization.
• Offer technical context for user support teams to resolve issues effectively.

Brief history of error logs: How did it all begin?

Error log files have evolved from magnetic tapes to sophisticated tracking systems today.

Logging can be traced to the 1960s, the mainframe era. At first, logs were recorded on magnetic tapes to track execution time and computing resources usage, which was helpful for billing. In this era, users were billed based on how many computing resources they consumed. This approach took a turn in the 1970s, when local area networks (LANs) emerged. The rise of LANs led to more use cases of logs; they were now used to track errors, application behavior, and system operations. In the 1990s, the internet became widespread, bringing about web server logs, which were then used for tracking HTTP requests and unauthorized access.

Today, logs are pretty much integrated with your systems and applications. They are used for real-time threat detection, anomaly spotting, and performance tuning, driven by the need for better debugging and system monitoring.

When it comes to the history of logs, one of my favorite quotes is: “Logs are widely used to record runtime information of software systems… [enabling] system developers (and operators) to monitor the runtime behaviors of their systems and further track down system problems.”
This quote by Gholamian and Ward from their paper A Comprehensive Survey of Logging in Software illustrates the historical shift from basic runtime tracking to the sophisticated logging tools used in modern software development.

Error log files have evolved from magnetic tapes to sophisticated tracking systems today.

Types of error logs

• Application Error Logs: These error logs capture events that indicate an issue within an application, such as a crash or exception.
• System Error Logs: These error logs are specific to the operating system’s operation—for example, system crashes, system configuration, driver issues, and hardware failures.
• Security Error Logs: These logs track security-related events, such as vulnerability issues, malware, suspicious actions, login attempts, and security breaches. They’re often located in security information and event management (SIEM) systems.
• Database Error Logs: These error logs record errors, queries, and transactions related to your database management systems (DBMS), such as invalid configuration.
• Performance Error Logs: These error logs focus on issues affecting a system or application’s speed, efficiency, or stability. They focus less on functional errors, like bad queries, and more on performance-related issues like timeouts and thread lock contention.
• Web Server Error Logs: These error logs record incidents related to requests, HTTP, and server errors. Some examples are HTTP 500 internal server errors and script or configuration failure issues.
• Network Error Logs: These error logs capture network-related issues like high traffic, DNS resolution errors, firewall rule violations, packet drops, or network timeouts.

How error logs work

Setting up error logs is critical to effectively capturing and tracking issues as they arise in your development, testing, or production environments. Here are some steps to get started with error logs:

1. Choose a logging framework. Like Matt Brown said on Stack Overflow, “The generally accepted best practice is to use a logging framework that has concepts of different log objects, different log levels, [and] different log outputs.” Thus, opt for a structured logging framework and configure it thoughtfully. This could be logging for Python, Log4j or SLF4J for Java, or Monolog if you use PHP.
2. Define a consistent log level and specify a structured log format for your events.
3. Set your output destination.
4. Define how long it takes to keep logs based on compliance and storage resources.
5. Implement encryption and access controls to secure your logs.
6. Integrate with log management platforms.

Each log entry typically includes the following components:

• Error ID: This unique ID is used to identify each error record.
• IP addresses: This shows the IP addresses of the source and receiving devices.
• Timestamp: This shows the date and time the error occurred in an ISO 8601 format with the accurate time zone.
• User, device, or server: This is the name of the application, server, or system where the error was logged.
• Severity level: This indicates the severity of the log entry. The usual levels range from TRACE to DEBUG, INFO, WARN, ERROR, and FATAL.
• Error message: This is the exception message that describes the issue and provides details about the event of the issue.

How to interpret errors/troubleshoot issues

1. Once an error occurs, review the logs to identify where, when, and which module, function, service, or system was affected. Also, determine if the issue was isolated.
2. To investigate the root cause, recreate the error in a controlled environment, such as your staging or testing environment.
3. Use debugging tools to step through the code. Check for misconfigurations, recent code changes, failed integrations, or performance bottlenecks that might have triggered the error.
4. Implement the fix. This could involve changing the codebase, updating the configuration, or upgrading the dependencies.
5. Confirm the fix doesn’t break current functionality or introduce any new issues.
6. Monitor the log after the fix deployment.

Benefits of utilizing error logs

1. Improved resolution times

When resolving issues, error logs are important as they help pinpoint for your engineers where and when the issues originated. You can quickly uncover bottlenecks or resource constraints when this information is correlated with system metrics and a modern log management system. This drastically reduces the chance of downtime, improves the system reliability of your IT environment, and decreases how long it takes to fix issues—or MTTR (mean-time-to-resolution), as it is called.

2. Easier decision-making

Making smart decisions starts with having the right data; error logs provide exactly that.

Error logs have information about the log levels (INFO, WARN, ERROR, FATAL), affected devices, IP addresses, usernames, clear descriptions of what went wrong, and when issues occurred (your timestamps). This data can help you understand what happened, the cause, how severe the situation is, who is affected, when the problem began, and what needs to be fixed first. With this, you can identify, analyze, prioritize, and decide the next course of action to allocate resources, resolve problems, and prevent the issues from happening again.

You can identify, analyze, prioritize, and decide the next course of action to allocate resources, resolve problems, and prevent the issues from happening again.

3. Better performance

Earlier, we discussed application error logs and how they track an application’s error incident history. Analyzing these logs can uncover the issue’s root causes, significantly improving application and system performance.

Why is the application hanging? It could be caused by memory leaks or running out of resources. Error logs hold this information, and a historical analysis of these logs helps identify recurring performance issues.

4. Improved security

Since error logs give insight into what happened, when, and how, they can be used to spot unusual patterns like repeated failed login attempts, access from strange IP addresses, or unauthorized system changes—all of which could be signs of a hacking attempt, a compromised account, or a brute-force attack. These insights can help you take action, such as alerting the user, blocking requests, or enabling two-factor authentication for added protection.

Best practices in error logging

• Know which logs to monitor. You don’t need to monitor everything; this will leave you burned out and ineffective with a noisy log environment. Instead, focus on your critical environments and key metrics, such as user experience and security. However, “the only thing worse than logging too much is logging too little… if your log can’t explain the cause of a bug or whether a certain transaction took place, you are logging too little.” (Anthony Vallone, author of Optimal Logging, Google Testing Blog)
• Your log entries should be appropriate and tagged to the right level. For example, a test environment log shouldn’t be INFO, as this will give the events the wrong level of severity and importance. A general rule of thumb is:
  TRACE: Detailed flow for debugging.
  DEBUG: Developer-focused logs during testing.
  INFO: General application progress.
  WARN: Suspicious or unexpected events, not necessarily errors.
  ERROR: Application errors requiring attention.
  FATAL: Critical issues requiring immediate action.
• Standardize your log format. A consistent format would make filtering, searching, and integration with log management tools seamless.
• Create actionable alerts. Actionable alerts are significant and always include a response plan for action when they go off. It’s also good practice that alerts should only be sent to the relevant team and channels to avoid clogging up communication and to ensure they are responded to. This is where the RACI Matrix and Playbooks principle is constructive and helpful—define who is responsible, accountable, consultable, and informed (RACI) for each alert type.
• Analyze error trends and monitor logs regularly. To take a proactive approach, you need to monitor your logs for anomaly spotting by benchmarking them to performance metrics. It’s also great to ensure this is an iterative process, so regularly review and change the benchmark as you scale.
• Follow strong security and privacy considerations. You don’t need to log everything literally—sensitive data like passwords, API keys, and personal identifiers (PII) shouldn’t be logged. If you, however, need to, use encryption to secure logs and log redaction techniques to mask sensitive content. In this case, have access control and audit trails to monitor who accesses logs.
• Have a defined log retention policy: How long should log information be stored? Ensure you follow compliance and risk laws as you define your retention policy. This is important as logs accumulate rapidly, consuming storage and increasing costs. So, decide which should be retained, deleted, archived, or discarded, as well as when and for how long.
• Explore log management and monitoring tools. Logging and analyzing don’t have to be complex, inefficient, and time-consuming. Research and leverage a comprehensive logging tool to simplify the process for you and your team.

One option is Tricentis Tosca, which comes with the Tricentis Tosca Log Viewer for viewing and monitoring test execution logs in real time and Tosca Dashboards for your visualization and dashboard capability needs.

When done right, error logs provide visibility into what went wrong, when, and why, which helps with troubleshooting and root-cause analysis.

Wrapping up

Error logging goes beyond just capturing failures; it’s critical to monitoring your system’s health and performance. When done right, error logs provide visibility into what went wrong, when, and why, which helps with troubleshooting and root-cause analysis. As enterprise systems grow more complex, it becomes increasingly important to be more intentional with your error logs as they contribute to a more resilient, efficient, and secure software environment. With Tricentis solutions and strong error logging practices, you can gain better visibility into your process.

This post was written by Ifeanyi Benedict Iheagwara. Ifeanyi is a data analyst and Power Platform developer who is passionate about technical writing, contributing to open-source organizations, and building communities. Ifeanyi writes about machine learning, data science, and DevOps, and enjoys contributing to open-source projects and the global ecosystem in any capacity.