Monitoring and analyzing metrics, logs, and traces in Azure is essential for maintaining healthy applications and quickly identifying issues. Azure provides comprehensive tools through Azure Monitor, which serves as the central platform for observability.

**Metrics** are numerical values collected at regular intervals that describe system performance. Azure Monitor Metrics stores time-series data in a specialized database optimized for fast retrieval. You can view metrics through the Azure portal, query them using Kusto Query Language (KQL), and create alerts based on thresholds. Common metrics include CPU usage, memory consumption, request counts, and response times. Application Insights provides application-specific metrics like dependency call durations and failure rates.

**Logs** contain detailed records of events and activities within your applications and infrastructure. Azure Monitor Logs uses Log Analytics workspaces to store and analyze log data. You write KQL queries to search, filter, and aggregate log information. Diagnostic settings enable you to route platform logs from Azure resources to Log Analytics, storage accounts, or Event Hubs. Application Insights automatically collects request logs, exceptions, and custom events from your applications.

**Traces** provide distributed tracing capabilities that track requests as they flow through multiple services. Application Insights uses correlation IDs to link related telemetry across service boundaries. The Application Map visualizes dependencies between components, while the Transaction Search allows you to investigate specific request flows. End-to-end transaction details show timing breakdowns for each step in a request.

**Practical Implementation** involves instrumenting applications with the Application Insights SDK, configuring diagnostic settings for Azure resources, creating dashboards for visualization, and setting up alert rules for proactive notification. You can also export data to external systems using continuous export or Azure Data Explorer for advanced analysis. Understanding these monitoring capabilities enables developers to troubleshoot performance bottlenecks, detect anomalies, and ensure application reliability in production environments.

Availability tests and alerts in Azure are essential components for monitoring the health and responsiveness of your applications. Azure Application Insights provides these capabilities to ensure your services remain accessible to users.

**Availability Tests** are automated checks that periodically send requests to your application endpoints from various global locations. There are several types:

1. **URL Ping Test**: The simplest form that sends HTTP requests to a specified URL and validates the response. You can configure success criteria based on response codes, content matching, and response time thresholds.

2. **Standard Test**: An enhanced version supporting HEAD, GET, and POST requests with SSL certificate validation, proactive lifetime checks, and custom headers.

3. **Custom TrackAvailability Test**: Allows you to create multi-step tests using Azure Functions or custom code for complex scenarios requiring authentication or multiple request sequences.

To create an availability test, navigate to your Application Insights resource, select Availability under Investigate, and configure the test URL, locations, success criteria, and test frequency (ranging from every 5 minutes to every 15 minutes).

**Alerts** notify you when availability tests fail or when specific conditions are met. Azure Monitor integrates with Application Insights to provide comprehensive alerting capabilities:

1. **Metric Alerts**: Trigger based on availability percentage dropping below a threshold across selected locations.

2. **Action Groups**: Define notification preferences including email, SMS, push notifications, webhooks, Logic Apps, Azure Functions, or ITSM integrations.

3. **Alert Rules**: Configure severity levels, evaluation frequency, and conditions for triggering notifications.

Best practices include testing from multiple geographic regions to identify location-specific issues, setting appropriate thresholds to avoid false positives, configuring multiple notification channels for critical applications, and regularly reviewing test results through the availability blade dashboard. This proactive monitoring approach helps maintain service reliability and enables rapid response to outages.

Application Insights is a powerful Application Performance Management (APM) service within Azure Monitor that enables developers to monitor live applications, detect performance anomalies, and diagnose issues effectively.

To instrument an application for Application Insights, you have two primary approaches: automatic instrumentation and manual instrumentation.

**Automatic Instrumentation (Auto-Instrumentation)**
This approach requires minimal code changes. For supported platforms like .NET, Java, Node.js, and Python, you can enable Application Insights through configuration. In Azure App Service, you can enable it through the Azure Portal by navigating to your app, selecting Application Insights, and enabling the feature. The SDK is automatically injected and begins collecting telemetry data.

**Manual Instrumentation**
For more control, you can add the Application Insights SDK to your project. For .NET applications, install the Microsoft.ApplicationInsights.AspNetCore NuGet package. Then configure it in your Startup.cs or Program.cs by adding services.AddApplicationInsightsTelemetry() and providing your connection string from the Azure Portal.

**Key Telemetry Types Collected:**
- Requests: Incoming HTTP requests to your application
- Dependencies: Calls to databases, REST APIs, and external services
- Exceptions: Server and browser exceptions
- Page Views: Client-side browser telemetry
- Custom Events and Metrics: Business-specific telemetry you define

**Connection String Configuration**
Store your Application Insights connection string in application settings or environment variables. The connection string contains the instrumentation key and ingestion endpoint information.

**Custom Telemetry**
Use TelemetryClient to track custom events, metrics, and traces. Inject TelemetryClient through dependency injection and call methods like TrackEvent(), TrackMetric(), or TrackException() to send custom data.

**Best Practices**
- Use sampling to reduce telemetry volume in high-traffic applications
- Configure appropriate retention periods
- Set up alerts for critical metrics
- Use availability tests to monitor endpoint health proactively