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Application logs play a crucial role in conveying information related to external as well as internal events during the app’s runtime. And most importantly, developers can view this information while it is running. As such, whenever there are occurrences like bugs, security breaches, or anomalies in software deployment, app logs prove handy in analyzing the root cause of the event.
Well-structured logs work wonders in keen observation and prompt action — one can easily and quickly comprehend how the entire system functions and helps to prevent issues well in advance. However, troubleshooting sessions will be productive only if developers adhere to effective logging practices. Improper logging practices will lead to unwanted challenges. Now, the most likely questions that will arise in your mind are:
Well, this post answers all these questions — the best practices for enterprise app logging and things to avoid while logging.
App Logging Best Practices to Follow
Understand Your Target Audience
While handling logs, it’s important to understand that app logs have two different sets of audiences — machines and humans — and their ways of data handling are quite disparate. If the data is structured, machines can process huge chunks of data automatically and speedily whereas humans fare poorly in processing a substantial amount of data as they need time to read through the logs. But, in the case of unstructured data humans outshine machines.
Therefore, in order to obtain the best results out of your logs, the logs must be created in a way that they are suitable for machines as well as humans — structured for machines, and at the same time, readable for humans.
Know the use of different Log Levels
Log levels indicate the severity of each event within the system and software developers should know when to use each of them. Given below are the commonest log levels available along with their use case scenario.
Employ a Log Format that you can Parse without much ado
It is not desirable that your observability platform is unable to extract data from your logs. To avoid such a situation, you need to employ a log format that you can parse effortlessly. Also, maintain a consistent log structure so that the data can be easily collected and aggregated.
In the case of several platforms serving a common purpose, standardize a log format for all applications. This will ease out the process of incorporating data into the observability platform even if the teams involved in each application demands visibility into varying attributes. And, if using a customized format, set the log type triggers and create parsing rules as defined by the customer.
Make use of Effective Tools and a Sound Framework for Creating Logs
Leverage the tried and tested logging frameworks and tools instead of reinventing the wheel by creating your own logging environment. This move will not only save your time and hassles. Moreover, a consistent logging framework comes with the following functionalities.
Standard Features of a logging framework
Advanced Features of a logging framework
Create Concise Log Messages that are Developer-friendly
If your log messages carry less information, it will become difficult to capture the necessary information that is needed for creating the context of every crucial event. And, if the log messages are too long, performance issues will crop up. For instance, large log files mean higher I/O and more disk space consumed, and if this aspect is not supported by the file system, the overall performance will get adversely affected. In a nutshell, huge logs consume storage, reduce the speed of search logs, and cause distraction from the core issue, thereby making debugging more difficult.
To address this issue, log messages need to be optimized. For this, you need to gain a rigorous understanding of the functional as well as non-functional expectations of the system, and accordingly plan the quality and amount of messages that you’ll log. In short, you need to strike that perfect balance between the quality and quantity regarding log messages — every log message should be meaningful and relevant to the context. For example, when an app fails to connect and retrieve data from an internal API, logging error messages from either the API or the network state information of the eco-system is more important than including information on the number of apps running or the memory space used by the application.
App Logging Practices to Avoid
Logging Sensitive Data without Proper Encryption
App logs should not expose the following sensitive data:
Most privacy laws/regulations like GDPR, HIPAA, and CCPA advise against displaying the aforesaid information through logs as it might lead to security breaches and serious lawsuits. As per the standard protocol, if any financial data is present in the logs, it must be entirely masked or hidden. And, if any business transaction has to be mentioned, one must use a system-generated event ID instead of real business names/identifiers.
How to ensure safety if you need to log some sensitive user data in non-production environments?
Vendor lock-in
Your log management should be organized in such a way that you do not get locked to a particular vendor. For this reason, avoid hardcoding vendor libraries; instead, opt for a standard library/wrapper for portability. Using a wrapper would ensure that the code of your app does not explicitly mention the third-party tool, or you can create a logger interface following apt methodologies and include a class that will implement it. Thereafter, add the code that calls the third party to this class.
Logging messages for Troubleshooting only
We all know that troubleshooting is the key purpose of logging. Yet, your log messages should not be meant for troubleshooting only as log messages are immensely helpful in some other tasks as well. So, besides troubleshooting, you can also log messages for the following business tasks:
Today, logging plays a pivotal role in multiple facets of any enterprise — business intelligence, operations, and marketing strategies. And, following the correct logging techniques and making your logs function effectively is very important. Adhering to the best practices for log monitoring and management will help you to run your business operations smoothly, resolve issues faster, resulting in a speedier development process.
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