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Observability / 2 MIN READ

The first AEM dashboard should answer five questions

A dashboard layout for separating visitor impact, delivery problems, and application errors.

A dashboard earns its space when it shortens a decision. For an AEM-backed site, “are there errors?” is too broad. I want to know whether people are affected, where the failure begins, what changed, which scope is involved, and where to investigate next.

Start with the delivery path

A typical AEM delivery path can involve a CDN, Apache/Dispatcher, and a publish tier. Authoring is a separate experience with different users and failure modes. Draw the actual path for your deployment before combining the logs.

Adobe supports forwarding AEM Cloud Service logs, including Apache/Dispatcher logs, to Datadog. Its current documentation also describes CDN forwarding and environment/tier metadata. Verify the supported destinations and deployment type; a self-managed AEM installation does not inherit the same collection mechanism.

Five questions, five dashboard rows

My proposed layout starts with visitor impact: request volume, an agreed error-rate definition, latency, and synthetic checks for important journeys. The next row shows delivery: edge responses, origin-bound requests, and Dispatcher signals available from the collected data.

Then show application symptoms: normalized exception families, publish-tier errors, and slow operations. Follow that with recent releases or configuration changes. The final row should link to scoped logs and traces, not another wall of charts.

Use consistent filters for environment, tier, service, and time. A production symptom beside a staging log panel is worse than a blank panel because it creates a convincing false explanation.

Work a small example

Suppose a product page check starts failing while AEM exception volume is unchanged. Filter the dashboard to that hostname and route family. If delivery logs show an access denial before requests reach publish, application restarts are a weak first response.

If the same window instead shows publish errors after a release, investigate that version and its dependencies. These are hypotheses, not proof; confirm them with the request evidence.

Show missing telemetry explicitly

No errors and no logs are different states. Put freshness or ingestion-delay checks beside the panels that responders rely on. Define whether a graph counts all requests, sampled logs, or indexed logs.

The dashboard should make those distinctions visible. Otherwise, it can turn an observability outage into a reassuring green screen.

REFERENCES & FURTHER READING

Official documentation and primary sources behind the technical details. Examples in this article are illustrative.

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