Show how metrics, logs, and alerts flow from services into dashboards and on-call paging.
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A monitoring stack diagram illustrates how observability data moves from running services to actionable insight. It shows exporters and agents scraping metrics, a time-series database like Prometheus storing them, a log pipeline, dashboards in Grafana, distributed tracing, and an alerting layer that pages on-call engineers. The flow makes the path from raw telemetry to alert clear.
SREs, DevOps engineers, and platform teams use it to document observability tooling, plan alerting strategy, and onboard on-call rotations. It appears in reliability runbooks, observability proposals, and incident-readiness reviews built on stacks like Prometheus, Grafana, and Loki.
Prefer to start from your own content? Describe it in one sentence and Infogiph generates a monitoring & observability stack diagram you can edit and animate. For example:
“Monitoring & Observability Stack Diagram showing Metrics Exporters, Prometheus (Time-Series DB), Log Pipeline (Loki), Grafana Dashboards, Alertmanager and PagerDuty On-Call”
Try it in the AI diagram generator, or read Decision tree examples, including incident severity.
A monitoring stack is the set of tools that collect, store, visualize, and alert on metrics, logs, and traces from your systems to keep them observable.
Common components are metric exporters, a time-series database like Prometheus, a log store like Loki, dashboards in Grafana, and an alerting layer such as Alertmanager or PagerDuty.
Monitoring tracks known signals against thresholds, while observability lets you ask new questions about system state using metrics, logs, and traces together.
Alerting rules fire on metric thresholds, route through tools like Alertmanager, and page on-call staff via PagerDuty, Opsgenie, or Slack.
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Open the monitoring & observability stack diagram in the Infogiph canvas, then edit, animate, and export.
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