Individual skill

observability-k8s-investigation

Investigate Kubernetes workload, node, and control-plane issues using OTel telemetry (EDOT). Use when diagnosing pod failures (CrashLoopBackOff, OOMKilled, Error), node pressure, resource exhaustion, image pull failures, admission rejections, autoscaling anomalies, or correlating K8s state with application signals. OTel ingest path only — the legacy ECS Kubernetes integration shape is out of scope.

skills/observability/k8s-investigation/SKILL.md

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Last checked: Nov 6, 2026

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Repository stars (not skill ratings): 604
Repository last updated: Nov 6, 2026
License: Apache-2.0

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devops Derived category
devops-containers Derived category

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SKILL.mdcore · 33,368 bytes
SKILL.mdcore · 33,368 bytes
SKILL.mdcore · 33,368 bytes
SKILL.mdcore · 33,368 bytes
SKILL.mdcore · 33,368 bytes
SKILL.mdcore · 33,368 bytes
references/failure-modes.mddoc · 9,183 bytes
references/query-recipes.mddoc · 3,981 bytes

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# Kubernetes Investigation

Diagnose Kubernetes issues using OTel telemetry collected via EDOT (Elastic Distribution of OpenTelemetry) and the
kube-stack collector. Correlate cluster state, pod runtime metrics, K8s events, application logs, and APM to identify
root cause across the workload, node, and control-plane layers.

<!-- begin-partial: preamble -->

## Environment Configuration

This skill executes Elasticsearch operations through the `elastic` CLI. If the
[`elastic` CLI](https://github.com/elastic/cli#configuration) is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.