Best practices for using Markers in SLF4J/Logback

java

logging

best-practices

logback

byAnton Shumikhin·Jan 30, 2025

Make your logs speak volume by making use of Markers in SLF4J/Logback. Markers serve the purpose of categorization, setting a detectable imprint that distinguishes crucial events, like security-related ones:

Marker secMarker = MarkerFactory.getMarker("SECURITY"); // Dressing up our event in a 'SECURITY' outfit
logger.info(secMarker, "Login attempt detected"); // A potential intruder detected, alarms blaring!

This brightens the path towards swift event identification and quicker problem-solving.

Strategic Filtering: Leaning on Markers and MDC

Dealing with an overwhelming volume of logs begs for robust filtering mechanisms that let you focus on the essentials. Markers are your spotlights, performing the triple duty of categorizing, filtering, and sending out warning signals when something serious is up. MDC (Mapped Diagnostic Context) breathes additional context into your logs, making it the ideal tool during advanced troubleshooting of issues.

Skip no step in defining a robust policy for Marker usage. Each Marker should serve a crystal-clear purpose for better log analysis and maintenance.

Golden nuggets:

Markers Naming: Make it reveal its objective in its name.
Marker-LogLevel Pairs: Distinguish between regular and crisis moments.
Custom Markers: Make use of custom Markers for uniform signaling across your application.

Embracing MDC for Greater Context

MDC enhances your logs with the gift of context, becoming your go-to tool when you need to connect the dots between disparate events across different segments of your system.

Examples of Use-Cases:

User Activity Tracking: See the full journey of a user - all actions under a unique session ID.
Job-specific Logs: Focus only on logs pertinent to specific service requests.
Environmental Filtering: Filter logs by specific environments such as production, development, or testing.

Do it right, and MDC labels the details of your logs, even the horror stories of failures that are otherwise hard to trace.

Next-Level Logging: Markers, MDC, and Beyond

Extend the power of Markers and MDC to structured logs ● e.g., JSON logs. Tools like logstash can exploit this, providing advanced, visual, and searchable log analysis.

How-to-guide:

logstash-logback-encoder: Configure your Logback to output logs in JSON format.
Log Parsing: Parse your JSON logs using logstash or other tools, and put the Markers and MDC fields within reach.

Visit the guide for logstash-logback-encoder here.

Visualization

Think of Markers in SLF4J/Logback as a clear label on each of the office folders:

🏢💼 - Corporate Strategy
🖥💾 - Tech Innovations
⚗📚 - Research Notes
🎨🖼 - Design Templates

In our dense logs, each Marker enables quick context identification.

// Without markers:
(echoing in the void) "We've got a problem." // With whom? What exactly?

// With markers:
💾: "We've got a problem with the latest deploy." // Now that's specific and useful!

In short, Markers filter out noise, making your logs scan-friendly.