Developer & cloud explorers

Kubernetes Event Explorer

Paste kubectl events and get a timeline, reason taxonomy and likely root causes per workload.

Output of `kubectl get events -A -o json` (best: exact timestamps) or the plain `kubectl get events -A` table including the header line. events.k8s.io/v1 JSON also works.

Read in memory as UTF-8 text and not stored. Max 5 MiB.

Only for the text table: relative ages like "5m" are counted back from this time. Default: now.

Try an example: Crash-looping checkout, unschedulable worker, bad image tag (JSON) · Missing Secret during scale-up (kubectl table)

How it works

Paste `kubectl get events -A -o json` or the default `kubectl get events` table. Events are grouped by involved object and inferred workload (Pod → ReplicaSet → Deployment), each reason is classified (rollout, crash loop, probes, image pulls, scheduling, volumes, OOM, node pressure…), and evidence-based root-cause hypotheses explain what probably happened and what to check next.

  • JSON events: involvedObject/regarding, reason, message, type, count/series.count, firstTimestamp/lastTimestamp/eventTime are read as documented for core/v1 and events.k8s.io/v1 Events.
  • Table output: columns are located from the header line; relative ages (e.g. "3m (x7 over 11m)") are converted to absolute times counted back from capturedAt (default: the analysis time), and the "xN" repeat count is used as the occurrence count.
  • Reasons are mapped to categories using the reason strings emitted by kubelet, scheduler, controllers and node-problem-detector; ambiguous reasons are refined by message (BackOff restarting vs pulling image; Unhealthy liveness vs readiness; Failed ErrImagePull vs CreateContainerConfigError).
  • Pods are linked to Deployments via ScalingReplicaSet/SuccessfulCreate messages, then by the <deployment>-<rs-hash>-<pod-hash> naming convention.
  • Root-cause rules combine signals per workload (e.g. liveness failures + back-off → probe-induced restarts; back-off alone → app exits; FailedScheduling message → resources/taints/affinity/PVC).

For scripts and AI agents

  • JSON API: POST https://kuberneteseventexplorer.usefulweb.site/api/v1/calculate (same calculation as this page)
  • Interface description: OpenAPI 3.1 · AI guide: llms.txt
  • MCP server (Streamable HTTP): https://kuberneteseventexplorer.usefulweb.site/mcp · tool name kubernetes_event_explorer
Example request
curl -s -X POST https://kuberneteseventexplorer.usefulweb.site/api/v1/calculate \
  -H 'content-type: application/json' \
  -d '{…see OpenAPI examples…}'

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