Self-Healing Kubernetes: Wiring OpenTelemetry, SigNoz, and a Groq-Powered

The following notes reconstruct a practical path around “Self-Healing Kubernetes: Wiring OpenTelemetry, SigNoz, and a Groq-Powered Remediation Agent (PART 7)”. Emphasis stays on contracts, checks, and drop-in code placeholders rather than motivational framing. When working through the Overview stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

# All pods should show Running
kubectl get pods -n observability
kubectl get pods -n apps

# Port-forwards (run each in its own tab if not already open)
# Tab A: kubectl port-forward -n observability svc/signoz 8080:8080
# Tab B: kubectl port-forward -n apps svc/summarizer 8000:80
# Tab C: kubectl port-forward -n apps svc/approval-dashboard 9000:9000
# Tab D: kubectl port-forward -n apps svc/approval-frontend-svc 3000:3000# Confirm the agent is polling
kubectl logs -n apps deployment/remediation-agent --tail=5

kubectl set env deployment/summarizer -n apps KILL_ME=true
curl -s http://localhost:8000/crash

kubectl get pods -n apps -w

CRITICAL summarizer — KILL_ME is true, exiting process

kubectl logs -n apps deployment/remediation-agent --tail=20 -f

WARNING  agent — crash loop signal: error_rate=1.00
INFO     agent — anomaly detected: crash_loop — calling Groq for diagnosis
INFO     agent — diagnosis: type=crash_loop severity=critical confidence=0.91
           fix=kubectl set env deployment/summarizer -n apps KILL_ME-
INFO     incident_poster — incident posted: id=<uuid> type=crash_loop

✓ Approved by operator
deployment.apps/summarizer env updated

# The approve action already removed KILL_ME, but confirm:
kubectl get deployment summarizer -n apps -o jsonpath='{.spec.template.spec.containers[0].env}' | jq

for i in {1..30}; do
  curl -s -X POST http://localhost:8000/leak | jq -c '{leaked_mb,chunks}'
  sleep 0.5
done

WARNING summarizer — leak endpoint hit, bucket now holds 10 MB
WARNING summarizer — leak endpoint hit, bucket now holds 20 MB
...
WARNING summarizer — leak endpoint hit, bucket now holds 240 MB

kubectl describe pod -n apps -l app=summarizer | grep -A 5 "Last State"

Last State:     Terminated
  Reason:       OOMKilled
  Exit Code:    137

type=oom_kill severity=critical confidence=0.88
fix=kubectl set resources deployment/summarizer -n apps \
  --containers=summarizer --limits=memory=512Mi

for i in {1..5}; do
  curl -s -X POST http://localhost:8000/expensive \
    | jq '{output_tokens, length_chars}'
  sleep 2
done

{
  "check": "latency_spike",
  "spikes": { "/expensive": 11240.0 },
  "p95_ms_by_route": {
    "/summarize": 1820.0,
    "/expensive": 11240.0,
    "/healthz": 4.0
  }
}

type=token_spike severity=high confidence=0.85
root_cause: The /expensive endpoint has no reasonable max_tokens budget
            and a prompt that invites long outputs, causing p95 latency
            to spike to 11s versus 1.8s on the normal /summarize path.
fix=kubectl set env deployment/summarizer -n apps MAX_TOKENS_EXPENSIVE=256

import httpx

SLACK_WEBHOOK = os.environ.get("SLACK_WEBHOOK_URL")def notify_slack(card: dict):
    if not SLACK_WEBHOOK:
        return
    d = card["diagnosis"]
    httpx.post(SLACK_WEBHOOK, json={
        "text": (
            f"*{d['severity'].upper()} — {d['incident_type']}* on `{card['service']}`\n"
            f"Root cause: {d['root_cause']}\n"
            f"Proposed fix: `{d['proposed_fix']}`\n"
            f"Confidence: {int(d['confidence']*100)}%\n"
            f"<http://your-dashboard-url|Review on dashboard>"
        )
    })

from kubernetes import client, config

config.load_incluster_config()
apps_v1 = client.AppsV1Api()
core_v1 = client.CoreV1Api()

ALLOWED_TARGETS = {
    "deployment/summarizer -n apps",
    "deployment/worker -n apps",
}

def validate_command(cmd: str) -> bool:
    if not any(cmd.startswith(p) for p in ALLOWED_PREFIXES):
        return False
    if any(term in cmd for term in BLOCKED_TERMS):
        return False
    if not any(target in cmd for target in ALLOWED_TARGETS):
        return False
    return True

Operational checklist

For the Operational checklist stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state.

Treat this stage as a contract between inputs and validated outputs. Name the artifacts, define success checks, and refuse silent partial completion.

Put human approval on edges that spend money or change production data. Compile-time wiring does not equal business completeness.

Write a short runbook: how to rotate keys, how to drain the queue, how to roll back the last ingest.

Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

Put human approval on edges that spend money or change production data. Compile-time wiring does not equal business completeness.

Before promoting the stack, freeze versions, capture a golden transcript for the critical path, and confirm rollback steps. Shared environments need rate limits, tenancy checks, and a clear owner for secret rotation. Prefer boring reliability over clever one-off demos.

Batch note for 294ff5dff76c: keep provider keys out of the repo, set a per-session token ceiling, and store transcripts next to the eval fixtures so later model swaps stay comparable.

When working through the hardening note 0 stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

Hardening detail 0/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

The hardening note 1 stage works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Treat this stage as a contract between inputs and validated outputs. Name the artifacts, define success checks, and refuse silent partial completion.

Hardening detail 1/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For the hardening note 2 stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Keep configuration outside application code. Environment files, secret stores, and feature flags belong in one place operators can audit without reading the whole graph.

Hardening detail 2/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

When working through the hardening note 3 stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Prefer small, testable units over sprawling scripts. When a step fails, the failure should point at a single responsibility rather than a tangled pipeline.

Hardening detail 3/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

The hardening note 4 stage works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

Hardening detail 4/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For the hardening note 5 stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

Hardening detail 5/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

When working through the hardening note 6 stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Treat this stage as a contract between inputs and validated outputs. Name the artifacts, define success checks, and refuse silent partial completion.

Hardening detail 6/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

The hardening note 7 stage works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Keep configuration outside application code. Environment files, secret stores, and feature flags belong in one place operators can audit without reading the whole graph.

Hardening detail 7/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For the hardening note 8 stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Prefer small, testable units over sprawling scripts. When a step fails, the failure should point at a single responsibility rather than a tangled pipeline.

Hardening detail 8/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

When working through the hardening note 9 stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

Hardening detail 9/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

The hardening note 10 stage works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

Hardening detail 10/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For the hardening note 11 stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Treat this stage as a contract between inputs and validated outputs. Name the artifacts, define success checks, and refuse silent partial completion.

Hardening detail 11/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

When working through the hardening note 12 stage, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Keep configuration outside application code. Environment files, secret stores, and feature flags belong in one place operators can audit without reading the whole graph.

Hardening detail 12/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

The hardening note 13 stage works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Prefer small, testable units over sprawling scripts. When a step fails, the failure should point at a single responsibility rather than a tangled pipeline.

Hardening detail 13/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For the hardening note 14 stage, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

Hardening detail 14/928: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.