Can logging impact site performance in B2C Commerce?

Yes, building complex log strings can be expensive. This skill teaches you to use conditional checks like log.isDebugEnabled() to ensure code only runs when the specific log level is active.

What is the difference between Logger and Log classes in SFCC?

The Logger class provides static methods for quick, general logging, while the Log class allows for instance-based logging with specific categories for better organization and filtering in Business Manager.

What is Nested Diagnostic Context (NDC)?

NDC is a tool used to distinguish interleaved log messages from different requests. It allows you to push context (like an Order ID) onto a stack so every subsequent log entry in that thread includes the context.

How do I create custom log files for integrations?

You can use Logger.getLogger(category, fileNamePrefix) to write to a dedicated file. Note that prefixes must be between 3-25 characters and follow specific alphanumeric naming rules.

B2C Commerce Logging

Name: B2C Commerce Logging
Author: SalesforceCommerceCloud

bySalesforceCommerceCloud

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分析と監視

Guides developers through implementing robust logging patterns in Salesforce B2C Commerce scripts using the Logger and Log classes.

概要

This skill provides comprehensive guidance for Salesforce B2C Commerce (SFCC) developers to implement structured logging using the dw.system.Logger and dw.system.Log classes. It covers essential patterns for managing log levels, organizing messages via custom categories, and utilizing Nested Diagnostic Context (NDC) for end-to-end request tracing. By following these best practices, developers can improve system observability, facilitate faster debugging within Business Manager, and ensure sensitive data is handled securely across various integration points.

主な機能

4 GitHub stars
Performance-optimized logging using conditional level checks
Custom log file creation with dedicated naming prefixes
Categorization strategies for organized Business Manager filtering
Nested Diagnostic Context (NDC) for tracing related log messages
Implementation of all SFCC log levels from debug to fatal

ユースケース

Tracing request execution paths across multiple script files using NDC
Monitoring background jobs and data exports with dedicated log files
Debugging complex checkout flows and multi-step payment integrations

概要

主な機能

4 GitHub stars
Performance-optimized logging using conditional level checks
Custom log file creation with dedicated naming prefixes
Categorization strategies for organized Business Manager filtering
Nested Diagnostic Context (NDC) for tracing related log messages
Implementation of all SFCC log levels from debug to fatal

ユースケース

Tracing request execution paths across multiple script files using NDC
Monitoring background jobs and data exports with dedicated log files
Debugging complex checkout flows and multi-step payment integrations