How can you efficiently debug your code even as it scales up with all the third-party libraries you might use and their associated configurations?
One surprisingly simple but commonly overlooked answer: logging.
Logging is the practice of recording the alerts and messages that you get about the state of your code. As your application may run into inefficiencies, errors, or even crash, you can save the associated messages together with all the relevant context.
Any message about the performance of your code shows up within the relevant console, helping you:
Yet, all the information within the console deletes itself the second you refresh your app or the specific page associated with the log.
How can you preserve this context for potential future debugging?
By explicitly logging relevant messages into a more consistent location than just your console.
While your app is in the development phase, every error or alert message about the state of your code is easily accessible to you and your team.
But once you ship to production, certain errors may never show up within your internal system unless you take the time to set up additional logging.
To do so, you should understand the key difference between two types of logging:
Both categories of logging involve their own best practices and a level of nuance, but in this guide we will focus on how you can set yourself up for server-side logging.
The messages recorded in your console can encompass multiple levels ranging in severity for your overall application performance.
Each level is associated with its method within the console:
The exact state and appearance of these messages may change based on the exact browser or environment whose console you’re using:
As your application becomes more complex, the code may end up too difficult to manage.
In this case, you want to organize the alerts on your console into more manageable chunks to search and reference whenever you debug or make other changes.
If you want to understand how long a specific process within your code takes, you can use the corresponding time methods:
This can be useful for catching inefficiencies, analyzing your code’s performance, or tracking down bugs that may be slowing the overall user experience.
To avoid crashing your entire application, you can use the console for defining the affected scope of a potential error within your code.
The try. . . catch statement can help you map boundaries within your code and program-specific error handling code that will run when the other section of your app crashes. This statement includes 3 blocks:
By properly recording any alerts as they come in, whether in development or production, you can save time for yourself and your team when any problems do pop up.
If you’re ready to move beyond basic logging and benefit from a robust solution, you can try Railtown AI for free.
Railtown is happy to announce that root cause discovery is now available for teams that run on NodeJS.
While .NET is one of the most loved frameworks according to Stack Overflow Developer Survey for 2021, that popularity can bring issues for .NET error logging. There are “hundreds of thousands” of .NET packages available on NuGet, so developers can end up with an overwhelming tech stack to simply analyze .NET performance and monitor errors. How can you efficiently debug your code even as it scales up with all the third-party libraries you might use and their associated configurations? One simple but commonly overlooked answer: logging.