Operations | Monitoring | ITSM | DevOps | Cloud

Modern systems throw off logs like confetti—and making sense of all that noise is half the battle. OpenTelemetry logging offers a way to bring some order to the chaos. It helps DevOps teams collect logs in a consistent format, no matter what language or framework they’re working with. In this guide, we’ll walk through what OpenTelemetry logging is, why it matters, and how to put it to work in your stack.

Application monitoring is important for finding and fixing issues in modern software systems. Traditionally, teams have used Application Performance Monitoring (APM) tools to track application health and performance. These tools provide built-in features like dashboards, alerting, and error tracking. Now, OpenTelemetry is becoming popular as an open-source way to collect telemetry data like traces, metrics, and logs. It gives developers more control and avoids vendor lock-in.

In our increasingly serverless world, observability isn’t just a “nice to have”—it’s essential. Serverless functions such as AWS Lambda bring incredible benefits, but they also introduce complexities, especially around monitoring and debugging. In a previous article, I provided a quick, practical guide for sending AWS Lambda traces to Grafana Cloud using OpenTelemetry.

AI systems, from machine learning models to Large Language Models (LLMs) and autonomous AI agents, introduce unique observability challenges. Their non-deterministic nature, complex dependencies, and specialized performance characteristics require thoughtful instrumentation approaches. OpenTelemetry has emerged as the leading standard for implementing observability across these systems.