Operations | Monitoring | ITSM | DevOps | Cloud

LLM applications rarely crash. They degrade quietly. Once these applications are shipped to production, subtle quality failures become harder to catch with traditional signals. Tone shifts, hallucinated details, off-topic responses, and incomplete reasoning can emerge while latency and token usage look stable.

Operators today are navigating unprecedented complexity—rising costs, accelerating customer expectations, and increasingly dynamic networks. In this recent video interview, my colleague Kevin Wade and I explore why AI‑driven automation has shifted from a “nice‑to‑have” technology to a core business requirement for telecom operators and beyond.

Chris Watts is Head of Enterprise Engineering at OpenRouter, building infrastructure for AI applications. Previously at Amazon and a startup founder. As large language models become core infrastructure for more and more applications, teams are discovering a familiar challenge in a new context: you can't improve what you can't see.

SAN JOSE, Calif., March 23, 2026 — Tigera, the creator and maintainer of Project Calico, today announced a major expansion of its Unified Network Security Platform for Kubernetes, aimed at helping enterprises consolidate infrastructure and accelerate the migration of legacy workloads to cloud-native platforms.

Most teams know they are spending money on AI in production. Far fewer realize how much they are spending outside production. It’s easy to get lost as you evaluate which model has the best responses, is fast enough, and cheap enough to run in production. That is because the AI bill usually shows up as a giant blob. It is easy to see the total.

Engineering teams are shipping faster than ever. AI coding tools like Claude Code and OpenAI’s Codex have quietly removed some of the biggest friction points in the development cycle — and the result is that FinOps teams are being asked to keep up with a pace most practitioners haven’t fully reckoned with yet. That acceleration has a cost consequence. More shipping means more services, more experiments, more infrastructure spun up without review cycles.