An open-source monitoring system with a dimensional data model, flexible query language, efficient time series database and modern alerting approach.

Prometheus stands as a cornerstone in the realm of modern observability, providing a robust toolkit for monitoring and alerting in dynamic, cloud-native environments. Delving into Prometheus, readers can uncover the intricacies of time-series data collection, metrics instrumentation, and scalable monitoring architectures. With Prometheus, readers gain the tools and knowledge needed to ensure the reliability, availability, and performance of their distributed systems.

Prometheus

Prometheus 3.0 introduces an experimental info() function that simplifies enriching metrics with metadata labels from info metrics. The traditional PromQL join approach requires specifying identifying labels, info metrics, and data labels explicitly, making queries complex and error-prone. The info() function wraps queries in a single call, automatically handles label joins, and solves the "churn problem" where changing non-identifying labels cause many-to-many matching errors. It automatically selects the time series with the latest sample, eliminating join failures during infrastructure changes. The function works particularly well with OpenTelemetry resource attributes and requires enabling via a feature flag. Current limitations include fixed job/instance identifying labels and default target_info metric usage, but future versions aim to support all info metrics automatically.

Introducing the Experimental info() Function

The Problem: Complex Joins and The Churn Problem

Before and After: Side-by-Side Comparison