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[ARTICLE · art-98724] src=dev.to ↗ pub= topic=ai-agents verified=true sentiment=· neutral

Break a kind cluster on purpose, then watch an Observe agent

Kprompt v0.5 ships an optional Observe agent that continuously watches Kubernetes clusters for failures, correlates incidents, and gates notifications via Slack or webhook, with Autopilot remaining propose-only. The kprompt-examples repository provides a fixture set with seven failure scenarios (CrashLoop, ImagePull, OOM, stalled rollout, unbound PVC, failing CronJob, missing Redis hostname) to demo the agent offline in heuristic mode without spending LLM tokens. The agent never applies, patches, or deletes by default, and Autopilot proposals require explicit approval.

read2 min views1 publishedAug 16, 2026

One command from kprompt-examples: kind up, seven failure scenarios, verify they actually broke, then run the Observe agent offline in heuristic mode — $0, no silent auto-heal.

Originally published at https://kprompt.ai/blog/observe-agent-kind-demo.

v0.5 shipped the optional Observe agent: always-on watch → correlated Incident → gated Slack/webhook, with Autopilot still propose-only. The missing piece for a live walkthrough was a payments

namespace that actually misbehaves — not a slide claiming CrashLoopBackOff.

kprompt-examples is that fixture set. Break the cluster on purpose, then watch the agent react without spending an LLM token.

Needs Docker, kind, kubectl, and kprompt with the agent

subcommand. Heuristic mode — no API key, no spend. DEMO_SECONDS=60

stretches the agent window for recordings.

git clone https://github.com/kprompt/kprompt-examples.git
cd kprompt-examples
make walkthrough   # up → break-all → verify → agent-full (~45s)

Or step by step when you want to film each failure:

make up
make break SCENARIO=01-crashloop
make verify
kprompt agent run -n payments \
  --emit-initial --analyze --fetch-logs --health --heuristic \
  --memory --patterns --autopilot-propose

--emit-initial

matters: a live watch stays quiet until new Pod/Event traffic. Already-broken workloads may not re-emit until the next BackOff

. Emitting current state first makes demos and CI deterministic.

Seven scenarios in one namespace, with a healthy baseline so the health score has something Ready to weigh against:

Scenario Rough signal
CrashLoop Restarting container / BackOff
ImagePull ImagePullBackOff / ErrImagePull
OOM OOMKilled / Exit 137
Stalled rollout Progress deadline / unavailable replicas
Unbound PVC Pending Pod waiting on volume
Failing CronJob Job failures / backoff
Missing Redis hostname DNS / connection errors to a stub Service name

Expect:

web

stays Ready--autopilot-propose

: a propose-only rollback suggestion on the stalled checkout rollout (Applied

stays That last point is the product claim: Observe never applies, patches, or deletes by default (ADR-0013). Autopilot emits PlanResult-shaped proposals (ADR-0015); apply stays gated.

Surface Job
Laptop CLI Reactive: NL → PlanResult → approve → apply
Observe agent Always-on: watch → Incident → severity/confidence gate → notify
Autopilot Opt-in propose-only; apply needs policy + explicit approve

K8sGPT-style tools are great at on-demand scan → explain. Observe is a different job: continuous watch with threaded alerts from live Events/Pods. Do not expect fleet-scanner or multi-agent-framework parity — we ship one kprompt-native pipeline.

brew install kprompt/tap/kprompt

or curl -fsSL https://kprompt.ai/install | bash

Try: kprompt.ai · GitHub · kprompt-examples

Muhtalip

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