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Logging vs Error Tracking: Two Sides of the Same Coin?

Ayooluwa Isaiah
Updated on May 28, 2024

Monitoring the health and performance of your applications is a critical aspect of software development and IT operations.

Two terms you'll often encounter are "logging" and "error tracking." While they might seem similar at first glance, they serve distinct purposes and offer different insights into your software's health and performance.

In this article, we'll delve into the key differences between the two, shedding light on how each contributes to a comprehensive monitoring strategy.

Let's get started by understanding what logging is.

What is logging?

For decades, logs has been an essential part of debugging applications in any environment. It is the most basic form of application monitoring in which notable events in a program are recorded (usually to a file) so that one can piece together what happened during the course of program execution.

A notable event could be any action or occurrence deemed important for understanding the program's behavior, such as routine actions, function calls, errors and warnings, performance markers, debugging information, security events, and many more.

Traditionally, logs were unstructured text, designed to be readable by humans but difficult for machines to process. However, since modern systems no longer run at an easily comprehensible human scale, structured logging is becoming more commonplace.

With structured logs, you can feed the data to an automated platform for analysis and alerting, rather than relying on humans to sift through mountains of data and spot patterns in real-time.

Now that you understand what logging is let's look at what is error tracking is and how it's different.

What is error tracking?

Error tracking is a specialized form of logging that zeroes in on capturing and analyzing errors and exceptions within your application. While general logging records a wide range of events, error tracking focuses on gathering detailed context around specific errors to help you understand their impact and resolve them efficiently.

Some key information captured by error tracking includes:

  • The type of the error and its message.
  • The sequence of function calls leading up to the error (stack trace).
  • The user context that led to the error, and how it affects the user experience.
  • Information about the system where the error occurred (e.g., operating system, browser version).

This data is then sent to a specialized error monitoring platform for processing and aggregation. This platform alerts you to new issues and assists in prioritizing them for effective troubleshooting.

Error tracking organizes errors with similar messages and stack traces into collective issues, along with metadata such as total error counts, first seen and last seen dates, occurrence frequency, the number of affected user sessions, and more. This insight helps you understand which issues most significantly affect your customers and should be addressed first.

When it comes to resolving these issues, having detailed context allows for better correlation with other events, like recent deployments. After a fix is implemented, this system also helps you verify whether the issue has been fully resolved or if new problems have arisen.

In summary, error tracking lets you:

  • Consolidate similar errors into groups, making it simpler to prioritize major issues and filter out less relevant ones.
  • See the specific application versions impacted by an issue.
  • Get alerted to spikes in error rates or the emergence of new issues.
  • Track errors over time to see their history, frequency, and current status (resolved, ongoing, ignored, etc).
  • See your overall application health by checking whether error volumes are trending up or down.

The key differences between logging and error tracking

The major differences between logging and error tracking are summarized below:

Feature Logging Error Tracking
Scope Captures a wide range of events for analyzing system behaviour Focuses primarily on capturing and analyzing errors and exceptions
Data collected Records all kinds of system events including debugging information, informational messages, warnings, and errors Collects errors and exceptions only
Detail Level Varies depending on log level and configuration. Can range from very detailed to high-level summaries. Provides detailed technical information for each error such as stack traces, environment details, and user context.
Use Cases Used for troubleshooting, system monitoring, security auditing, business analytics, and more. Used for error identification, prioritization, debugging, and software quality measurement

Deciding between logging and error tracking

The choice between logging and error tracking hinges on your specific needs and objectives. If you require immediate alerts about errors as they arise in production, need to identify recurring issues and their impacts, and want to prioritize fixes, then error tracking is essential.

On the other hand, if you want a broader understanding of your system's overall behavior, need detailed audit records for compliance, or wish to analyze user behavior and usage patterns, then investing in a comprehensive logging solution is the way to go.

In the majority of cases, the best approach involves using both in tandem for comprehensive system monitoring and troubleshooting, because they work hand in hand for investigating errors, crashes and other issues.

For example, imagine that you noticed a problem in your application where an operation is taken far too long, triggering a timeout error. You've been alerted of the problem, so you quickly turn to your error tracking platform to investigate the issue.

You then discover that a number of timeout errors have occurred in the past few minutes meaning that it's not just a transient issue, but one that indicates a persistent problem. You then proceed to dig around a bit to see the error's distribution across environments, sources, and users.

To see how the error came about, you then head to your observability tool check your logs (and traces) to provide more context to what events that lead up to the error. You will ideally have an unique ID in the error report that helps you connect it with related logs, traces, and other telemetry data.

Doing this helps you see how an error in one service may have propagated to another, discover what aspect of the process is slowing things down. Once you've zeroed in on the method calls that are slow, you can then investigate further to see how the calls that timeout differ from the ones that don't.

Perhaps the issue is isolated to a specific set of users, database queries, third-party API calls, or any number of other parameters. Doing this lets you get to the root cause of the issue to implement the appropriate fix, and also follow up with affected users once the fix is deployed.

Logging and error tracking are not competing solutions – they are synergistic parts of a broader observability strategy that helps you gain a comprehensive understanding of your application's behavior, identify and resolve issues quickly, and ultimately deliver a more reliable and enjoyable experience to your users.

How to get started with error tracking

Getting started with error tracking involves a few key steps that will help you gain control over your application's reliability and stability:

  1. Choose an error tracking platform: There are various error tracking tools available, both open-source and commercial. Evaluate your needs based on factors like features, integrations, and pricing to select the platform that best suits your requirements. Popular examples are Sentry, Bugsnag, Rollbar, Raygun, and others.

  2. Integrate the error tracking SDK: Most error tracking platforms offer SDKs for popular programming languages and frameworks. Install the appropriate SDK into your application's codebase and configure it to capture relevant error data.

  3. Capture and aggregate errors: Once integrated, the error tracking tool will automatically capture exceptions and errors as they occur. These errors will be aggregated into a central dashboard, allowing you to see an overview of all the issues affecting your application.

  4. Set up alerting: Configure your error tracking platform to send alerts when critical errors occur or when specific error patterns emerge. This will help you stay on top of issues and proactively address them before they escalate.

  5. Triage and prioritize issues: Examine the collected errors and prioritize them based on frequency, severity, and impact on users. Look for patterns or common causes to identify which issues to tackle first.

  6. Analyze and debug: Dive into the details of each error, including stack traces, environment details, and user context. This information will help you quickly diagnose the root cause and implement fixes.

  7. Monitor and iterate: Continuously monitor your error tracking dashboard for new errors and trends. Use the insights gained to refine your error handling strategies, improve code quality, and enhance overall application reliability.

Final thoughts

In summary, combining both methods allow for a comprehensive monitoring approach: logging offers a broad view of your application's activity, while error tracking focuses on errors and exceptions, providing the necessary context for issue prioritization and troubleshooting.

With both strategies in place, you can proactively identify and address issues, improve the user experience, and ultimately build more reliable and resilient software.

Thanks for reading!

Author's avatar
Article by
Ayooluwa Isaiah
Ayo is the Head of Content at Better Stack. His passion is simplifying and communicating complex technical ideas effectively. His work was featured on several esteemed publications including, Digital Ocean, and CSS-Tricks. When he’s not writing or coding, he loves to travel, bike, and play tennis.
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