OpenTelemetry

At some point in every team's life, someone gets paged at 2 AM because a service is 'slow.' Nobody knows which service. Nobody knows why. Someone opens five different dashboards,

OpenTelemetry almost always works beautifully in staging, demos, and videos. You enable auto-instrumentation, spans appear, metrics flow, the collector starts, and dashboards light up. Everything looks clean and predictable. However,

Distributed tracing doesn’t just show you what happened. It shows you why things broke. While logs tell you a service returned a 500 error and metrics show latency spiked, only

A lot of talk around OpenTelemetry has to do with instrumentation, especially auto-instrumentation, about OTel being vendor neutral, being open and a defacto standard. But how you use the final

ServiceNow just pulled the plug on Lightstep. Here's where to go next and how to migrate without re-instrumenting your entire stack. TL;DR ServiceNow announced the end-of-life (EOL) for Lightstep (Cloud

This guide shows you how to implement OpenTelemetry's auto-instrumentation for complete distributed tracing across your microservices, from initial setup through production optimization and troubleshooting. How Distributed Tracing Works in Microservices

OpenTelemetry instrumentation is the foundation of modern microservices observability, but getting it right in production requires more than just enabling auto-instrumentation. This guide covers production-tested OpenTelemetry best practices that help

Distributed tracing has become essential for modern software teams. As applications evolve into complex distributed systems with microservices, APIs, databases, and third-party integrations, understanding how a single user request travels