Interactive challenge

LLM Observability Challenge

Build the signal model needed to debug user latency, runtime saturation, GPU pressure, traces, logs, and alerts.

Prerequisites

Metrics stackLLM or mock inference workload

Guided step

Prepare the platform boundary

Create or identify the namespace, labels, and ownership metadata that make the workload reviewable.

Commands

kubectl create namespace llm-serving --dry-run=client -o yaml
kubectl label namespace llm-serving workload-class=llm owner=platform-ai --overwrite
kubectl get namespace llm-serving --show-labels

Expected signals

  • Namespace ownership is visible.
  • Workload class is encoded as a label.
  • The lab has a clear place to run validation commands.

Checks

Paste the `kubectl get namespace llm-serving --show-labels` output.

Confirm that the namespace has an owner label or documented owner.

Hints and solution

No hints opened for this step yet.