Radiant Observability: Practical Benchmarks for Serverless System Health
Serverless observability is not about collecting every metric—it's about knowing which signals matter and when to act. This field guide offers practical benchmarks for assessing system health in serverless architectures, drawn from patterns observed across real-world projects. We cover the common confusion between monitoring and observability, the signal-to-noise ratio that teams struggle with, and the anti-patterns that lead to alert fatigue. You'll learn how to set qualitative benchmarks for cold starts, error budgets, and tail latency without relying on fabricated statistics. We also discuss when a lighter observability approach is appropriate and when it's dangerous. The guide includes a FAQ section addressing open questions about distributed tracing costs, log retention, and the role of synthetic checks. By the end, you'll have a concrete framework for evaluating your own serverless health—and a set of next experiments to run on your own systems.