logging-framework

Structured Apex logging without governor limits is achieved by decoupling log creation from business transactions using Platform Events. This framework publishes Log_Event__e asynchronously, capturing Level, Source, Message, Stack Trace, and Payload fields to avoid DML limits.

Log retention and automated cleanup in Salesforce are managed through configurable retention policies and a scheduled batch job. This framework includes scheduled cleanup automation to systematically delete old log records and prevent data storage bloat.

Capturing custom payloads and stack traces in Salesforce Platform Events is fully supported by this framework. It structures log data into specific fields including Payload__c and Stack_Trace__c to provide rich diagnostic context for debugging and auditing.

Asynchronous logging with configurable log levels in Apex is set up by configuring the included LogService. You use LogService to emit logs at various severity levels from Apex classes, optionally attaching structured payloads for additional application context.

This Salesforce logging framework is designed for production applications, providing a scalable approach to capturing diagnostic data and error details. It isolates logging logic via Platform Events to ensure robust auditing without impacting core business logic performance.

Using Platform Events for Salesforce logging instead of direct DML prevents transaction overhead and governor limit exhaustion. This event-driven architecture decouples log persistence from business logic, enabling scalable diagnostic data capture across production apps.