10 Golang Logging Best Practices

Logging is an important part of any application, and Go applications are no different. Here are 10 best practices for logging in Go.

Logging is an important part of any application, and Go is no exception. Logs can be used to track events, debug errors, and monitor performance.

However, logging is often overlooked or done poorly. This can lead to problems such as lost logs, incorrect log levels, and inefficient logging.

In this article, we will discuss 10 best practices for logging in Go. By following these best practices, you can avoid these problems and make sure your logs are useful and effective.

1. Use the standard library

The standard library is battle-tested. It’s been used in production by some of the biggest companies in the world, so you can be confident that it’s stable and reliable.

It’s also easy to use. The standard library provides a simple API that makes it easy to get started with logging.

Finally, the standard library is extensible. If you need more features than the standard library provides, you can easily add them with third-party libraries.

2. Log at a consistent level

If you log at different levels in different parts of your code, it will be difficult to get a clear picture of what’s going on when you’re trying to debug an issue. It’s much easier to troubleshoot if you can see all the logs at the same level.

One way to achieve this is to use the “standard” logging library that comes with Golang. This library allows you to set the logging level globally, and then each individual logger will inherit that level.

Alternatively, you could create your own logging wrapper that sets the level for you. This would have the added benefit of being able to add other features, such as logging to a file or sending alerts when certain conditions are met.

3. Don’t include sensitive information in logs

If you include sensitive information like passwords or API keys in your logs, there’s a good chance that someone will eventually find and misuse that information. Even if your logs are properly secured, it’s still best to err on the side of caution and avoid logging sensitive information altogether.

Of course, there may be times when you need to log sensitive information for debugging purposes. In those cases, make sure to remove that information from your logs as soon as possible.

4. Include context with every log message

When something goes wrong in a system, it’s often hard to figure out what happened just by looking at a log file. This is because a lot of times, the relevant information is spread out across different parts of the codebase, and it can be tough to piece everything together.

This is where context comes in. By including contextual information with every log message, you make it much easier to understand what’s going on when something goes wrong. For example, if you’re logging an error, you might want to include the function name, file name, and line number where the error occurred. That way, when you’re looking at the logs, you can immediately see not only that an error occurred, but also exactly where it occurred.

Of course, including too much information in your log messages can make them hard to read. So strike a balance between including enough information to be useful, while still keeping your log messages readable.

5. Write your own logging wrapper function

By writing your own logging wrapper function, you can:

1. Centralize all your logging code in one place.
2. Add/remove logging levels without changing any code that calls the logging functions.
3. Modify the format of the log messages without changing any code that calls the logging functions.
4. Send the log messages to multiple destinations (e.g., stdout, file, network) without changing any code that calls the logging functions.

The benefits of writing your own logging wrapper function far outweigh the cost of doing so.

6. Use structured logging

With traditional logging, also known as unstructured logging, log messages are written as a single line of text. This can make it difficult to parse and extract information from log files, especially when you’re dealing with large volumes of data.

Structured logging solves this problem by writing log messages as a series of key-value pairs. This makes it much easier to parse and query log data, and also allows you to include additional metadata that can be useful for troubleshooting and debugging issues.

There are many structured logging libraries available for Golang, so it’s easy to get started. The most popular library is probably Logrus, but there are others worth considering, such as Zap.

7. Avoid excessive logging

If you’re logging too much, it can impact the performance of your application. In addition, it can also make it more difficult to find the information you’re looking for when you’re trying to debug an issue.

Therefore, it’s important to strike a balance between logging enough information to be useful, but not so much that it becomes a burden. A good rule of thumb is to only log information that would be useful for debugging purposes.

8. Keep it simple

Golang’s standard library comes with a very simple and straightforward logging package. It is easy to use and it gets the job done most of the time. However, it lacks some important features that are essential for production-grade logging, such as:

– Support for multiple log levels
– The ability to log to different outputs (e.g., files, databases, etc.)
– The ability to format log messages in different ways

Fortunately, there are many third-party logging packages that address these shortcomings. But with so many options to choose from, it can be difficult to know which one is the best for your needs.

The good news is that you don’t need to choose just one. In fact, it is often helpful to use multiple logging packages in your application. For example, you might use the standard library’s logging package for development and testing, and then switch to a more feature-rich package for production.

One of the most popular Golang logging packages is Logrus. It is feature-rich, supports multiple log levels, and has built-in support for formatting log messages in JSON.

9. Test your logging

If you don’t test your logging, you have no guarantee that your logs will actually be written to the correct location. This can lead to critical errors going unnoticed, and can make debugging difficult or impossible.

Testing your logging is also important because it allows you to verify that the format of your logs is correct. This is especially important if you’re using a structured logging format like JSON.

Finally, testing your logging ensures that your logs will be rotated correctly. If your logs are not rotated, they will eventually fill up your disk and cause your application to crash.

10. Rotate and compress your logs

If you don’t rotate your logs, they will eventually become so large that they will start to impact the performance of your system. Additionally, if you don’t compress your logs, they will take up more disk space than necessary.

Fortunately, there are a number of tools available that can help you rotate and compress your logs automatically. One of the most popular is Logrotate, which is available for free.

Once you have Logrotate installed, simply add a configuration file for each of your logs. For example, if you have a log file named “access.log”, you would create a file named “/etc/logrotate.d/access.log” with the following contents:

/var/log/access.log {
rotate 5

This configuration will rotate your “access.log” file every time it reaches 100 MB in size, and it will keep up to 5 rotated logs at a time. Additionally, it will compress all of the rotated logs to save disk space.


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