| Troubleshooting | L37-L86 | Diagnosing and fixing Azure Monitor issues: agent/extension health, data collection and ingestion failures, alerts/ITSM, Application Insights, containers/Prometheus, workbooks, and VM performance. |
| Best Practices | L87-L123 | Best practices for configuring, scaling, querying, and optimizing Azure Monitor (logs, metrics, alerts, autoscale, AKS/VMs, Prometheus, multicloud) for performance, reliability, and cost. |
| Decision Making | L124-L161 | Guidance for choosing Azure Monitor options and planning migrations (agents, alerts, metrics, logs, SCOM, Prometheus, Splunk), plus cost, billing, and visualization decisions. |
| Architecture & Design Patterns | L162-L169 | Designing Azure Monitor architectures: enterprise-wide layouts, Private Link network patterns, choosing single vs multiple workspaces, and using workspace replication for resilience. |
| Limits & Quotas | L170-L237 | Limits, performance, and scaling behavior for Azure Monitor logs, metrics, agents, autoscale, Prometheus, Container Insights, Workbooks, and per‑resource metric definitions. |
| Security | L238-L293 | Securing Azure Monitor: auth (Entra, RBAC, keys), network (NSP, firewalls, Private Link, TLS), ITSM/webhooks, Container/Prometheus/Grafana access, and security/audit log schemas and analysis. |
| Configuration | configuration.md | Configuring Azure Monitor end to end: agents, DCRs, pipelines, networking, alerts, autoscale, Application Insights, Kubernetes/Prometheus, Private Link, logs/metrics schemas, and resource‑specific metrics/logs. |
| Integrations & Coding Patterns | integrations.md | Integrating Azure Monitor with apps, alerts, ITSM, Prometheus/Grafana, REST/CLI, and using KQL patterns to query, export, and analyze logs/metrics across many Azure and third‑party services |
| Deployment | deployment.md | Deploying and migrating Azure Monitor agents/resources at scale (VMs, Arc, diagnostics, alerts, Profiler, workspaces, Grafana) using Policy, ARM, CLI, and PowerShell |