Observability

OpenTelemetry is not valuable because it produces more telemetry. It is valuable when it helps an engineer answer a production question quickly: what changed, who is affected, where did the request fail, and what should happen next? This guide is a practical starting point for teams moving from basic instrumentation to an observability practice that is useful, affordable, and sustainable. Who this is for This is for software engineers, platform teams, and SREs running distributed applications. It assumes you want vendor-neutral instrumentation and an operational model that works across services, languages, and deployment environments. ...

Over the past year I’ve been running a hands-on workshop called “New Relic AI Monitoring Mastery” at developer events. The premise is simple: attendees build a small AI chatbot from scratch using Python, Flask, and the OpenAI API, then instrument it with New Relic to see exactly what’s happening inside. This post captures the key ideas and lessons from those sessions - what metrics matter, how to get visibility quickly, and why model choice has a bigger operational impact than most people expect. ...

“Instrumentation” is one of those words that gets thrown around constantly in the observability world - but what does it actually mean, and how does it work in practice? I’ve run this as a hands-on workshop several times, and what I find most effective is starting from first principles: build a tiny app, make it produce telemetry, and watch what comes out. By the end you understand why the pieces fit together the way they do. ...