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Administer Monitoring This lesson covers three core objectives to improve observability and operational excellence for Azure workloads: configuring Azure Monitor to collect telemetry, creating alerts to notify and automate responses to critical signals, and provisioning Log Analytics for deep log query and analysis.
  • Configure Azure Monitor
    Set up Azure Monitor to collect, correlate, and analyze telemetry — metrics, logs, and traces — from Azure resources as well as on-premises or multi-cloud environments. Use agents and diagnostic settings to capture relevant data. Azure Monitor delivers insights into application and infrastructure performance, availability, and health, and integrates with services such as Application Insights and Autoscale.
  • Configure Azure alerts
    Create and manage alerts based on metric and log signals from Azure Monitor. Alerts notify stakeholders of critical conditions and can trigger automated actions through Action Groups (email, SMS, ITSM, webhooks) or call remediation workflows such as runbooks, Logic Apps, or Azure Functions.
  • Configure Log Analytics
    Provision and manage Log Analytics workspaces to store and query telemetry collected by Azure Monitor. Use the Kusto Query Language (KQL) to build queries that aggregate, filter, and correlate log data for troubleshooting, visualization, and alerting.
A slide with a blue gradient panel titled "Learning Objectives." On the right are three numbered items: Configure Azure Monitor, Configure Azure Alerts, and Configure Log Analytics, each with a colored icon.
Log Analytics enables creation of complex queries to explore telemetry, build visualizations, and extract actionable insights for faster incident resolution and informed decision-making.
Tip: Start by defining the signals you need (metrics, logs, traces), then map them to the appropriate Log Analytics workspace and alerting strategy. Using Application Insights for application telemetry and Log Analytics for infrastructure logs is a common pattern.
Warning: Be mindful of data ingestion and retention settings in Log Analytics — they affect cost and query performance. Review retention policies and sampling options to balance visibility and budget.

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At-a-glance: What each objective delivers

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