What Azure monitoring setup works best for real-world projects?

Azure Monitor is more of an umbrella than a single competing tool. A common setup is Application Insights for request failures, response times, dependencies, and distributed tracing; a Log Analytics workspace for centralized logs and KQL queries; Azure Monitor metrics and alerts for resource health, CPU, memory, and capacity; and dashboards or Grafana for visualization. Service Health alerts are useful for Azure-wide incidents. Keeping telemetry in one workspace usually makes troubleshooting easier because failures can cascade across several components.

The built-in Azure tools are usually enough to begin with. Application Insights covers failed requests, response times, availability tests, dependencies, and application errors. Standard Azure resource metrics can handle CPU, memory, database health, and container or App Service limits. Send diagnostic settings to the same Log Analytics workspace where possible so you can correlate application and infrastructure events. For larger or cost-sensitive systems, OpenTelemetry and an external platform such as Grafana, New Relic, Dynatrace, or another observability tool can reduce vendor dependence, but that adds operational and integration decisions.

For a security-focused environment, add a SIEM such as Microsoft Sentinel rather than trying to use ordinary operational alerts for every security event. Also consider cost early: Log Analytics ingestion and retention can become expensive. Define retention policies, collect useful structured logs, and avoid sending noisy data that nobody queries. The best tool depends on the team, the criticality of the services, and whether an existing observability platform is already in use.

I’d define the monitoring and alert rules as infrastructure code with Terraform or Bicep. That way every environment gets a consistent baseline, while development environments can have alerting disabled if needed. Alerts can create tickets through a webhook or incident-management system, and platform advisories can be reviewed separately on a regular schedule. Baseline alert templates are a useful starting point, but tune the thresholds before enabling them or you may get flooded with notifications, including resolution messages.

Start with alerts that lead to a clear action. Useful categories include a serious failure that needs immediate intervention, a trend showing that capacity or performance will soon become a problem, and important business or budget thresholds. Request volume, resource utilization, and error rate together can reveal unusual behavior much better than any one metric alone. Dashboards can contain more information, but alerts should be selective so people do not learn to ignore them.