8 Logging Best Practices You Should Already Know

8 Logging Best Practices You Should Already Know

In today’s business world, IT professionals have learned to live with complexity. That’s because IT professionals need to handle everything from petabytes of machine data to microservice architecture or monolithic systems. In the last ten years, complexities in managing log data keep on growing.

Most of the managing log data growth and challenges are due to the advancement of distributed systems. Logging is now in almost every facet of the business, and they are in virtually every part of a software stack. Logging has become so essential to IT management.

Most of the time, you can troubleshoot logging issues in real-time. Logging best practices help keep business intelligence information timely. Please keep reading if you want to learn more about how vital logging is for IT management.

What’s more, learn about eight logging best practices.

Log Data Management Best Practices

It has become increasingly important in today’s IT management world to determine what are logging best practices and which methods you still need to know? Almost all businesses use systems today that include microservice containers, with each having its own log data. Machine-generated log data continues to grow and develop due to the dominance of cloud-based systems. Log management is now considered to be the cornerstone with which all other IT components work.

The IT components include performance monitoring, debugging, and even production system monitoring. Developers and system support teams need insight into user behavior. To get a clearer and more concise picture, eight logging best practices are detailed below that may apply to your operational needs.

1. Logging Categories Mean Everything

If you’re in a JAVA logging library, you’ll know they are hierarchical. The category for log messages is based on the logging framework configuration. The Ops Engineer needs to set up the configuration that ranks substation by category.

Most of the time, you’ll notice Java developers will attempt to use a qualified class name when the log statement comes up as a category. But it rarely works because most programs don’t respect the category principle even if you still need it.

That leaves us with the need to specify a logging category. The category specifies the classification of the log message. The log message classification is based on the logging framework configuration, which needs to log or not logged.

2. Building Reliable Systems from Unreliable Components

Logging works even when there are concurrent and multiple transactions. Logging is essential for the management of any company’s infrastructure.

Logging service continues to evolve, and it continues to generate critical business values. It also addresses architecture decisions for resource limitations. Its most significant benefit when it’s working with unreliable components is it can reduce operation disruption.

3. Determining The Level The Log Entry Should Be Logged

The third best practice is one of the most difficult. No matter your IT skill level or expertise, almost everyone has a challenging time determining what level a log entry should be logged. Depending on your default program or service, many IT professionals run desktop programs at level debug.

If you ever have to do IT support work, it’s relatively easier for someone to change the log level than having them send you the log.

4. Centralize and Separate Log Data

It sounds like a conflict of interest, and in a way, it is. You need to have logs collected and sent to your central location. You cannot have the logs sent to your production environment.

Logs should always be separate from your production environment. It’s all about the consideration of your log data, which facilitates and enriches your analysis capabilities. You want to enable cross-analysis and even determine correlations coming from separate and different data sources.

5. The Importance of Log Collectors and Aggregators

Logs come with complete and valuable information about the system’s health and performance and critical aspects of log management infrastructure. You are working with hundreds of log files from hundreds of servers. Being able to detect an anomaly seems far-fetched and impossible to perform accurately.

By aggregating logs, you’re able to solve your anomalies and gain insight into user behavior. You’re able to collect that data before any problems reach the end-user. You should be able to implement the solutions before the end-user even knows there was a problem.

6. End-to-End Logging is Essential

Every troubleshooting complication depends on active monitoring and logging across all system components. It’s common-sense yet is a best practice that’s often forgotten about. It’s only through end-to-end logging that all infrastructure metrics and events allow you to understand your security issues and network latency.

It provides a window into the database transaction delays and other user experiences.

7. Parsing and Unique Identifiers

If you plan to debug, support, or analyze, you’re going to need to break it into parse content and use unique tags for your debugging and analytical support. You can’t track anything if it’s all contained together in something indecipherable.

That’s why you want to use a unique user ID to filter your action search that spans a user’s period activity in a specific time parameter.

8. Don’t Predetermine Your Logging Purpose

Not all logging is for troubleshooting purposes. That’s why when you predetermine what the issue is; you are leaving out some of the most needed reasons logging is needed. Most IT professionals think troubleshooting is the only target for log messages. But logging is used for profiling, statistics, and auditing.

Log usage is limitless. Don’t get cornered too early. For different roles, e.g. IT uses for system troubleshooting, Data scientists use it for business trending, DevOps use it for improving development and production.

Practices for Logging

The complex systems of today need a multitude of applications and software. That means the critical components are susceptible to error messages and bugs. But now you know where you can find the answer, and it all begins by facilitating logging best practices.

When you are ready to collect logs, investigate the performance errors you are receiving, accelerate the application delivery, and improve security compliance posture, do check out Logiq Platform. With Logiq Platform, you will find the best way to aggregating logs that saves time and money.

What’s more, you will gain the insight you want by starting with logging best practices.

Originally published at https://logiq.ai.

Turning log data into real time insights. Real-time log aggregation and analysis to any S3 compatible object-store| Eliminate Cost Per GB | www.logiq.ai

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