Operations | Monitoring | ITSM | DevOps | Cloud

Prometheus Distributed Tracing: An Easy-to-Follow Guide for Engineers

When your microservices architecture starts growing, tracking requests as they bounce between services becomes a real headache. You know the feeling—a user reports a slow checkout process, and you're left wondering which of your twenty services is the bottleneck. That's where distributed tracing with Prometheus comes in.
Sponsored Post

How to Configure OpenTelemetry as an Agent with the Carbon Exporter

If you're already using OpenTelemetry for tracing and logs, adding otelcol-contrib as an agent for system metrics just makes sense. It keeps everything in the same pipeline, so you're not juggling multiple monitoring tools or dealing with inconsistent data formats. Plus, with built-in support for host metrics, custom processing, and direct exports to Graphite, it's a solid way to ship performance data without extra overhead. In this article, we'll detail how to install the OpenTelemetry Collector Contrib distribution, and configure it to export system performance metrics to a Graphite datasource.

Correlation ID vs Trace ID: Understanding the Key Differences

You’re staring at logs, trying to figure out what caused that odd error in the middle of the night. Or maybe you're following a chain of requests across services, hoping to understand how one user action triggered a series of unexpected behaviors. That’s where distributed tracing and request tracking—specifically, correlation IDs and trace IDs—are invaluable. It’s the kind of detail that can make debugging faster and less painful.

How Does OpenTelemetry Logging Work?

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.

OpenTelemetry vs APM - The Future of Application Monitoring Explained

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.

AWS Lambda, OpenTelemetry, and Grafana Cloud: a guide to serverless observability considerations

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.

OpenTelemetry for AI Systems: Implementation Guide

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.

KubeCon 2025 London: OpenTelemetry Steals the Show and Splunk's Bold Moves

I was lucky enough to attend KubeCon Europe 2025 in London, where the energy around OpenTelemetry (OTel) reached fever pitch. From packed sessions to buzzing hallway conversations, it’s clear: OpenTelemetry isn’t just the future—it’s the present. Here’s what stole the spotlight.

Reducing Telemetry Toil with Rapid Pipelining

Intellyx BrainBlog by Jason English for Mezmo ‍ “Bubble bubble, toil and trouble” describes the mysterious process of mixing together log data and metrics from multiple sources as they enter an observability data pipeline. ‍ Customers demand high performance, functionality-rich digital experiences with near-instantaneous response times.