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Build incident timelines with OpenTelemetry entity events without guessing the cause

How to connect infrastructure changes, traces, logs, and metrics so you can explain what happened, when it happened, and which evidence supports it.

A practical guide to reconstructing incidents with OpenTelemetry entity events, request context, traces, logs, and Prometheus without relying on human memory or disconnected dashboards.

Created: August 15, 2026

Published: August 15, 2026

Estimated time40 min

LevelIntermediate

Before you startRead access to Prometheus or Grafana for SLO and error metrics

PlatformsLinux / Docker

WhatsApp X LinkedIn

Linux

Reconstruction from a workstation with kubectl, curl, promtool, and access to observability backends.

kubectlcurljqpromtoolGrafana/Prometheus access

Check rollout history

kubectl -n shop rollout history deploy/checkout-api

Query error-rate metrics

curl -G 'http://prometheus:9090/api/v1/query' --data-urlencode 'query=sum(rate(http_server_requests_seconds_count{service_name="checkout-api",status=~"5.."}[5m]))' | jq

Search logs with trace_id

logcli query --since=2h '{service_name="checkout-api"} |= "trace_id" |= "payment timeout"'

Also available inConstruir timelines de incidentes con eventos de entidad de OpenTelemetry sin inventarte la causa

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