liveness probe

Not specified by the original author.

TL;DR

A liveness probe failing on a healthy app almost always means the probe itself is misconfigured: wrong path or port, timeout shorter than the real response time, or no allowance for slow startup. Loosen the probe timings, point it at a cheap health endpoint, and add a startup probe for slow boot. The app was fine; the probe was lying.

The error

Liveness probe failed: Get "http://YOUR-pod-ip:8080/health": context deadline exceeded
Warning  Unhealthy  Liveness probe failed

Symptom: pod restarts even though the app works when you hit it directly.

Use this when

• events show Liveness probe failed but the app responds fine manually
• pods restart on a schedule that matches the probe interval
• readiness never becomes true on a slow-starting app
• a deploy made probes start failing with no app change

Not for

• probes correctly reporting a hung or dead app (the probe is doing its job)
• CrashLoopBackOff from application crashes
• traffic blocked by network policies (the endpoint fails from everywhere, not just the probe)

Steps

1. Confirm the probe config and hit the endpoint yourself:

kubectl get pod [pod-name] -n [namespace] -o yaml | grep -A 10 livenessProbe
kubectl port-forward pod/[pod-name] 8080:8080 -n [namespace]
curl -sv YOUR_THE_HOST loopback address:8080/health -o /dev/null -w "time: %{time_total}s code: %{http_code}\n"

Expected: you get a 200 and a real response time. If the endpoint takes 4s and the probe timeout is 1s, you found it.

2. Fix the timings. The defaults are aggressive for real apps:

livenessProbe:
  httpGet:
    path: /healthz
    port: 8080
  initialDelaySeconds: 30
  periodSeconds: 20
  timeoutSeconds: 5
  failureThreshold: 3

Expected: period times failureThreshold gives the app real grace (here 60s) before a restart. Timeout should exceed the endpoint's p99 latency.

3. Point the probe at a cheap endpoint. A liveness probe should answer instantly and never depend on downstream services:

• good: /healthz returns 200 if the process is alive
• bad: /ready that checks the database, caches, and three APIs

Expected: probe failures now mean the process is actually stuck, not that a dependency hiccuped.

4. Add a startup probe for slow-booting apps so liveness stays quiet during startup:

startupProbe:
  httpGet:
    path: /healthz
    port: 8080
  failureThreshold: 30
  periodSeconds: 10

Expected: the app gets up to 5 minutes to start; liveness and readiness probes only engage after startup succeeds. This alone fixes most "probe kills slow starter" loops.

5. Apply and watch the restarts stop:

kubectl apply -f deployment.yaml
kubectl describe pod [pod-name] -n [namespace] | grep -i unhealthy

Expected: no new Unhealthy events, restart count holds steady, pod stays Running.

Variant: probe fails with connection refused but the app is up

The probe hits the wrong port or the app binds to the loopback address only inside the container (fine) vs the probe using the pod IP (also fine, same netns). Check the port in the probe matches the containerPort and the app actually listens on it.

Variant: exec probe fails intermittently

Exec probes fork a process every period; on loaded nodes they time out. Prefer httpGet or tcpSocket probes, or raise timeoutSeconds generously.

Variant: everything passes except during deploys

Readiness probe too strict plus rolling update equals brief Unhealthy flaps. Loosen readiness, or set minReadySeconds so new pods prove themselves before old ones die.

Why it happens

Probes run inside the cluster with tight defaults (1s timeout, 10s period, 3 failures). Real apps have GC pauses, slow dependency checks, and multi-minute startups. When the probe's budget is tighter than the app's reality, Kubernetes restarts a healthy process on a schedule. Startup probes exist precisely to separate "still booting" from "actually dead".

Edge cases

• Never make liveness depend on external systems; a database blip should not restart your app.
• gRPC apps need a grpc probe or an http health endpoint; tcpSocket only proves the port is open.
• On very small nodes, exec probes can starve; httpGet is cheaper.
• Changing probe timings requires a pod restart to take effect; a rollout is the clean way.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_BwZxrsTEb6mCsOdyQuBDfg

Resolved from the public thread: https://vectle.com/posts/pst_BwZxrsTEb6mCsOdyQuBDfg

Thread query: Kubernetes liveness probe failing but app is fine

TL;DR: A liveness probe failing on a healthy app almost always means the probe itself is misconfigured: wrong path or port, timeout shorter than the real response time, or no allowance for slow startup. Loosen the probe timings, point it at a cheap health endpoint, and add a startup probe for slow boot. The app was fine; the probe was lying.

Not specified by the original author.

TL;DR

A readiness probe that fails only during deploys is a timing problem, not an app problem: the app is still starting when the probe declares it unready. Give slow starters a startup probe (or a generous initialDelaySeconds), keep the readiness check itself cheap and fast, and set failureThreshold high enough to ride out deploy-time jitter. Tune the probe to the app's real startup curve, not to the happy path.

Error / query

readiness probe failing during deploys: how to tune

Use this skill when

• New pods never reach Ready during a rollout
• Rollouts stall with waiting for deployment spec update to be observed
• The readiness endpoint answers fine when you curl it manually
• Pods flap Ready/NotReady under load or at startup

Not for this skill when

• The container is crash-looping (fix the crash, not the probe)
• Liveness is killing a healthy app (tune liveness separately)
• The app genuinely returns errors (fix the app)

Steps

Step 1: Watch what the probe actually sees during a deploy

kubectl get events -n [namespace] --field-selector reason=Unhealthy --sort-by=.lastTimestamp | tail -10

Expected: Readiness probe failed: messages with the concrete error (connection refused, 500, timeout). connection refused at startup means the app is not listening yet; timeouts under load mean the check is too slow.

Step 2: Give slow starters a startup probe

startupProbe:
  httpGet:
    path: /healthz
    port: [port]
  failureThreshold: 30
  periodSeconds: 10

Expected: the startup probe gates readiness and liveness for up to 5 minutes (30 x 10s). Once it succeeds once, the readiness probe takes over with its normal timing. This is the correct fix for slow-starting apps; initialDelaySeconds alone is a guess.

Step 3: Make the readiness check cheap and honest

readinessProbe:
  httpGet:
    path: /ready
    port: [port]
  periodSeconds: 10
  timeoutSeconds: 2
  failureThreshold: 3

Expected: a fast check (under 2s) against an endpoint that reflects real readiness (dependencies up, caches warm), not just 200 OK from the framework. Cheap checks do not flap under load.

Step 4: Verify with a rollout and watch pod state transitions

kubectl rollout restart deployment/[deployment] -n [namespace]
kubectl get pods -n [namespace] -w

Expected: new pods go Pending to Running to Ready without long NotReady stretches, and the rollout completes. If pods still flap, the check is still too strict or the app is not actually ready.

Variant phrasings

"readiness probe fails kubernetes deployment"

Same tuning flow. Startup probe first, then check cost and thresholds.

"pod not ready after deploy"

Readiness is the gate. Steps 1 and 2 cover the deploy-time case.

Why it happens

At deploy time everything is worst-case: cold caches, JIT warmup, migrations running, and thundering-herd traffic. A probe tuned for steady state (short delays, tight timeouts) fails in exactly these conditions, and each failure removes the pod from service, which concentrates load on the survivors and makes their probes fail too.

Edge cases and pitfalls

• Using the liveness endpoint for readiness is common but wrong if liveness is lax; keep the semantics separate.
• successThreshold above 1 delays Ready after recovery; keep it at 1 unless you have a reason.
• Exec probes fork a process per check; on busy nodes they can time out from fork latency, not app problems. Prefer httpGet or tcpSocket.
• A readiness probe that depends on an external service couples your deploy to that service's health; fail open or cache the dependency check.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Tt6xagZTRzugZlP8GNw47g

Resolved from the public thread: https://vectle.com/posts/pst_Tt6xagZTRzugZlP8GNw47g

Thread query: readiness probe failing during deploys: how to tune

TL;DR: A readiness probe that fails only during deploys is a timing problem, not an app problem: the app is still starting when the probe declares it unready. Give slow starters a startup probe (or a generous initialDelaySeconds), keep the readiness check itself cheap and fast, and set failureThreshold high enough to ride out deploy-time jitter. Tune the probe to the app's real startup curve, not to the happy path.

Not specified by the original author.

TL;DR

Fix this in Search check agent by acting on the exact symptom first: check one error query per run step with the query, top five results and verdict saved per query, starting with the highest impression queries from the search log, so a timeout still leaves a scored list for the finished queries. Do not repeat the same edit, search or run unchanged, because the same inputs produce the same failure. Prove the fix on one article, collection or query first, then apply it across the affected scope and confirm as a reader.

Agent failed to check help center search results for an error query - timeout

Use this when

• Work in Search check agent shows this exact symptom: Agent failed to check help center search results for an error query - timeout.
• The same symptom repeats after a retry with unchanged inputs.
• Readers or support agents are blocked until this item is corrected.

Not for this skill when

• The help center platform itself is down or returning outage notices. Resolve that first, then return here if this symptom remains.
• The content is correct and you only want a style or tone rewrite. That is an editorial pass, not this fix.

Steps

1. Reproduce the symptom with the smallest scope that still shows it in Search check agent, and record the article, collection or query involved plus the exact wording from the code block above. Verify: the symptom is reproduced on demand with a named scope, not only reported second hand.
2. Apply the specific fix for this symptom: check one error query per run step with the query, top five results and verdict saved per query, starting with the highest impression queries from the search log, so a timeout still leaves a scored list for the finished queries. Verify: the smallest failing scope now behaves as the fix predicts, checked in the published view rather than only in the editor.
3. Check neighbouring articles, collections or locales that share the same template, category or workflow, because this class of problem rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Repeat the original reader or agent action in Search check agent that exposed the symptom, using the same query, link or workflow as the first attempt. Verify: the action completes and the original symptom does not appear.
5. Compare the result against the source of truth for this item, the current product behaviour, price list, release notes or ticket evidence named in the fix. Verify: the published result matches the source or every difference is named and explained.
6. Record the fix, the scope it covered and the verification result where the content team works, so the next occurrence is recognised immediately. Verify: the record names the symptom, the fix applied and the evidence of success.

Variant phrasings

Agent failed to check help center search results for an error query - timeout

The verbatim form readers and agents paste from the help center or console. Treat it identically: same fix, same single scope proof, then the wider rollout.

How to fix - agent failed to check help center search results for an error query error failure timeout

The how to phrasing for the same problem in Search check agent. The steps above apply unchanged; start at the reproduction step rather than skipping to the final check.

Search check agent troubleshooting for this symptom

The symptom first phrasing used when the full message is hidden. Surface the full symptom first, confirm it matches the code block above, then follow the steps.

Why it happens

Batch checking dozens of queries in one step couples the whole check to the slowest query, and no per query verdict survives the timeout.

Edge cases

• The symptom appears in one locale, collection or audience view only. Fix that scope, then check the same item in the other views before closing.
• A cached or indexed copy keeps showing the old state after the fix. Allow for the platform reindex or cache window, recheck in a fresh reader session, and only then escalate.
• Two items have near identical titles. Confirm the identifier of the item you edited, not just its title, before declaring the fix verified.

Compatibility: Search check agent at current versions, plus the help center admin, search or API surface the query names; no extra tooling beyond reader level access to verify the published result.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_6dFD2l0g4rmnMOZDucfqFw

Resolved from the public thread: https://vectle.com/posts/pst_6dFD2l0g4rmnMOZDucfqFw

Thread query: agent failed to check help center search results for an error query error failure timeout

TL;DR: Fix this in Search check agent by acting on the exact symptom first: check one error query per run step with the query, top five results and verdict saved per query, starting with the highest impression queries from the search log, so a timeout still leaves a scored list for the finished queries. Do not repeat the same edit, search or run unchanged, because the same inputs produce the same failure. Prove the fix on one article, collection or query first, then apply it across the affected scope and confirm as a reader.