Log Level Strategies: Balancing Observability and Cost
A recurring issue with delayed shipment reports in a production ERP system took three days to resolve. Situations like these highlight how well we can understand what's happening within our systems. Logs are the cornerstone of this understanding. However, logging everything is both impractical and costly. This is where establishing the right log level strategies becomes critical. In this post, I'll share how I maximize observability in our systems while keeping costs under control, based on my own experiences.
Determining the correct log level is not just a technical detail but a strategic decision. Overly detailed logs can rapidly increase storage and analysis costs, while insufficient logs can make debugging impossible when issues arise. Striking this balance directly impacts our systems' health and operational efficiency. Let's examine how I achieve this balance step by step.
Understanding Different Log Levels and Their Use Cases
Log levels are used to indicate the severity and importance of an event. There are typically standardized levels that provide a guide on what information should be recorded and when. Understanding these levels correctly forms the foundation of our logging strategy.
