OpenAI video demonstrates Codex for Grafana, Kubernetes and security investigations
Published October 7, OpenAI’s video hosted by Tony Loehr and Anke Hao presents three production-monitoring scenarios with Codex: tracing a checkout failure in Grafana, investigating a Kubernetes rollout that triggers out-of-memory restarts, and examining a Codex Security finding tied to a missing resource limit.
Full Report
OpenAI published “Production Monitoring with Codex: Grafana, Kubernetes, & Security” on October 7, with cohosts Tony Loehr and Anke Hao walking through three production-monitoring demos. The video follows a checkout failure in Grafana, investigates a Kubernetes rollout that causes out-of-memory restarts, and explores how a Codex Security finding connects service availability to a missing resource limit.
The demonstrations also show telemetry, release history and code being used together in an investigation, followed by engineers reviewing a proposed change and checking the result. The focus is on linking monitoring signals to troubleshooting and change review across the three scenarios.
Why This Matters
The examples span an application failure, a resource issue after a rollout and a security finding. That gives engineering teams a concrete view of the investigation workflow and the kinds of production scenarios covered in the video.
Evidence
Start with the primary evidence, then review supporting sources and context.
Primary Evidence
1Production Monitoring with Codex: Grafana, Kubernetes, & Security
OpenAI
“It’s 3 a.m. and checkout errors are climbing. What do you check first? Join cohosts Tony Loehr and Anke Hao for three practical production-monitoring demos with Codex. Follow a checkout failure in Grafana, investigate a Kubernetes rollout that causes out-of-memory restarts, and explore how a Codex Security finding connects service availability to a missing…”
Recommended signals
Recommended by brand, topic, and recent related coverage
