You built the agent. It works in testing. Then it hits production and starts giving wrong answers, timing out or burning through your token budget, and you have no idea why. This is when developers discover that print statements and log files weren’t designed for this. LLM applications fail in ways that traditional tooling can’t see. A hallucination doesn’t throw an exception. A slow retrieval step doesn’t show up in CPU metrics. A prompt that worked yesterday silently degrades today. The fix is observability, and the standard for doing it right is OpenTelemetry (OTel). What OpenTelemetry Actually Is OTel isn’t a monitoring product; it’s a vendor-neutral specification under the CNCF that defines a standard way to collect observability data: What gets collected, what it’s called and how it’s shipped. You instrument your application once and can send that data to Grafana, Datadog, Jaeger or a purpose-built LLM platform without rewriting your instrumentation. That portabil...
Agentic SRE is the evolution of site reliability engineering where AI agents help observe systems, reason over telemetry and take bounded operational actions under human-defined guardrails. The goal is not to replace SREs, but to reduce toil, speed up diagnosis and make incident response more consistent and scalable. Why This Matters Modern systems are too distributed, noisy and fast-moving for purely manual operations to keep up. Engineers spend significant time correlating dashboards, reading logs, checking recent deploys and hunting for context before they can even start fixing the problem. Agentic SRE addresses this by turning telemetry into actionable context and automating safe parts of the response loo p . This shift is especially important because reliability work is full of repetitive, high-pressure tasks that are easy to standardize but hard to execute perfectly at 2 a.m. That makes it a perfect fit for agents that can summarize, correlate, recommend and execute wit...