This post is a part of the DP-800: Developing AI-Enabled Database Solutions Exam Prep Hub.
This topic falls under these sections:
Secure, optimize, and deploy database solutions (35–40%)
   --> Integrate SQL solutions with Azure services
      --> Recommend Azure Monitor configurations, including Application Insights and Log Analytics

Note that there are 10 practice questions (with answers) at the end of each section to help you solidify your knowledge of the material. Also, there are 4 practice tests with 30 questions each available from the hub's main page below the exam topics section.

Introduction

Modern SQL applications extend far beyond storing and retrieving data. Today’s applications often expose APIs, integrate with AI services, support microservices, and serve users around the world. As systems become more distributed, monitoring application health, database performance, security, and user activity becomes increasingly important.

Azure Monitor is Microsoft’s unified monitoring platform for collecting, analyzing, visualizing, and acting upon telemetry from Azure resources, applications, virtual machines, containers, databases, and on-premises environments. For SQL AI developers preparing for the DP-800 certification, understanding Azure Monitor—and specifically Application Insights and Log Analytics—is essential for designing highly observable, reliable, and performant database solutions.

The DP-800 exam expects candidates to know when and how to recommend monitoring configurations that support troubleshooting, performance optimization, security monitoring, operational excellence, and AI-enabled database applications.

Understanding Azure Monitor

Azure Monitor is a comprehensive monitoring service that provides:

• Metrics collection
• Log collection
• Distributed tracing
• Alerting
• Dashboards
• Workbooks
• Performance analytics
• Diagnostic settings
• Resource health monitoring

Azure Monitor collects telemetry from virtually every Azure service, including:

• Azure SQL Database
• Azure SQL Managed Instance
• SQL Server on Azure VM
• Azure App Service
• Azure Functions
• Azure Kubernetes Service (AKS)
• Azure Container Apps
• Data API Builder (DAB)
• Azure OpenAI
• Azure AI Search
• Microsoft Fabric
• Virtual Machines

Azure Monitor Architecture

A simplified monitoring architecture looks like this:

Applications
       │
Databases
       │
Azure Services
       │
Diagnostic Settings
       │
Azure Monitor
       │
 ┌───────────────┐
 │ Metrics       │
 │ Logs          │
 │ Traces        │
 │ Alerts        │
 └───────────────┘
       │
Application Insights
       │
Log Analytics
       │
Dashboards / Alerts / Workbooks

Core Azure Monitor Components

Azure Monitor consists of several integrated services.

Metrics

Metrics are numerical measurements collected at regular intervals.

Examples include:

• CPU utilization
• Memory usage
• DTU utilization
• vCore utilization
• Storage usage
• Active sessions
• Requests per second
• Response times

Metrics are lightweight and optimized for near real-time monitoring.

Logs

Logs contain detailed event information.

Examples:

• SQL errors
• Login attempts
• Application exceptions
• API requests
• Deadlocks
• Security events
• Query execution details

Logs support historical analysis and forensic investigations.

Alerts

Azure Monitor alerts notify administrators when predefined conditions occur.

Examples include:

• CPU > 80%
• Database unavailable
• Deadlock detected
• Slow API response
• Failed deployments
• Authentication failures

Alerts can trigger:

• Email
• SMS
• Azure Functions
• Logic Apps
• Webhooks
• ITSM integrations

Dashboards

Dashboards combine metrics and logs into a centralized monitoring view.

Typical dashboard elements include:

• Database performance
• API latency
• Error rates
• Availability
• Query duration
• Resource utilization

What Is Application Insights?

Application Insights is an Azure Monitor feature designed to monitor applications.

It automatically collects telemetry such as:

• HTTP requests
• Dependencies
• SQL calls
• Exceptions
• Page views
• Response times
• Availability tests
• Distributed traces

Application Insights helps developers understand application behavior rather than infrastructure performance alone.

Telemetry Collected by Application Insights

Application Insights automatically captures:

Requests

Every REST or GraphQL request can be monitored.

Information includes:

• URL
• Duration
• Response code
• Success or failure
• Timestamp

Dependencies

Dependencies include calls made by applications to external resources.

Examples:

• Azure SQL Database
• Azure OpenAI
• Azure AI Search
• Storage Accounts
• REST APIs
• Service Bus
• Cosmos DB

Dependency tracking identifies slow downstream services.

Exceptions

Application Insights records:

• SQL exceptions
• .NET exceptions
• Java exceptions
• Node.js exceptions
• Python exceptions

Developers can investigate stack traces and failure frequency.

Performance Counters

Examples include:

• CPU
• Memory
• Thread count
• Request queue
• Process utilization

Availability Tests

Availability tests periodically verify that applications remain accessible.

Types include:

• URL ping tests
• Multi-step web tests (legacy)
• Standard availability tests

Useful for:

• REST APIs
• Data API Builder endpoints
• Web applications

Distributed Tracing

Modern applications often involve:

Application

↓

REST API

↓

Data API Builder

↓

Azure SQL Database

↓

Azure OpenAI

↓

Azure AI Search

Application Insights correlates all these operations into a single transaction, allowing developers to trace requests end-to-end.

Benefits include:

• Root cause analysis
• Performance bottleneck identification
• Dependency tracking
• Service latency analysis

What Is Log Analytics?

Log Analytics is Azure Monitor’s centralized log repository and query engine.

Logs from multiple Azure resources are stored in a Log Analytics Workspace.

Examples include:

• SQL diagnostics
• Application Insights logs
• Azure Activity Logs
• VM logs
• Azure Firewall logs
• Microsoft Defender logs

Log Analytics Workspaces

A Log Analytics Workspace stores telemetry collected across Azure.

Benefits include:

• Centralized logging
• Long-term retention
• Cross-resource analysis
• Kusto Query Language (KQL) support
• Security investigations

Multiple Azure resources can send data to a single workspace.

Kusto Query Language (KQL)

Log Analytics uses KQL for querying data.

Example:

requests
| where success == false
| order by timestamp desc

Example:

dependencies
| summarize avg(duration) by target

Example:

exceptions
| summarize count() by type

The DP-800 exam expects familiarity with Log Analytics and awareness that KQL is the query language used to analyze collected telemetry.

Diagnostic Settings

Azure resources send telemetry through Diagnostic Settings.

Diagnostic Settings determine where logs are stored.

Possible destinations include:

• Log Analytics Workspace
• Storage Account
• Event Hub
• Partner solutions

For Azure SQL Database, diagnostic logs commonly include:

• SQLInsights
• Automatic tuning
• Deadlocks
• Query Store Runtime Statistics
• Errors
• Wait statistics
• Timeouts

Monitoring Azure SQL Database

Important Azure SQL metrics include:

• CPU percentage
• DTU percentage
• vCore utilization
• Data IO
• Log IO
• Storage percentage
• Sessions
• Workers
• Connections

These metrics help identify capacity issues before users experience failures.

Monitoring Data API Builder (DAB)

DAB deployments should enable:

• Request logging
• Response times
• Authentication failures
• GraphQL execution errors
• REST endpoint usage
• SQL dependency tracking

Application Insights provides excellent visibility into DAB performance.

Monitoring AI-Enabled SQL Applications

Applications integrating Azure OpenAI or Azure AI Search should monitor:

• API latency
• Request failures
• Token usage (where available)
• Dependency duration
• Timeout frequency
• Retry attempts

Dependency tracking in Application Insights helps identify whether delays originate from the database or external AI services.

Azure Monitor Alerts

Common production alerts include:

Alerts should prioritize actionable events while minimizing alert fatigue.

Workbooks

Azure Monitor Workbooks create interactive reports using:

• Metrics
• Logs
• Charts
• Maps
• Tables
• KQL queries

Typical workbook examples:

• SQL performance dashboard
• API performance trends
• AI service latency
• Database growth analysis
• Security monitoring

Retention Policies

Organizations should configure log retention based on:

• Compliance requirements
• Storage costs
• Investigation needs
• Security policies

Short retention reduces storage costs, while longer retention supports audits and forensic analysis.

Best Practices for Monitoring SQL Solutions

Microsoft recommends:

• Enable Application Insights for applications.
• Send diagnostic logs to Log Analytics.
• Enable distributed tracing.
• Configure proactive alerts.
• Monitor dependencies.
• Use dashboards for operational visibility.
• Review telemetry regularly.
• Monitor failed authentication attempts.
• Monitor slow SQL queries.
• Use KQL for troubleshooting.

Common DP-800 Exam Scenarios

You may be asked to determine:

• Which monitoring service collects application telemetry.
• When to use Application Insights versus Log Analytics.
• How to troubleshoot slow SQL queries.
• Which service stores centralized logs.
• How to monitor Data API Builder.
• Which service provides distributed tracing.
• How to configure alerts for production systems.
• Which Azure Monitor feature supports long-term log analysis.

DP-800 Exam Tips

Remember these key points:

• Azure Monitor is the overarching monitoring platform.
• Application Insights monitors application performance and dependencies.
• Log Analytics centralizes logs and supports KQL queries.
• Diagnostic Settings send Azure resource logs to destinations such as Log Analytics.
• Application Insights supports distributed tracing.
• Azure Monitor Alerts automate operational notifications.
• Workbooks provide customizable dashboards and reports.
• Azure SQL Database metrics help identify capacity and performance issues.
• Use Application Insights to monitor Data API Builder and AI-enabled applications.
• KQL is the primary language for querying Log Analytics data.

Practice Exam Questions

Question 1

A company wants to monitor the performance of a .NET application that accesses Azure SQL Database through Data API Builder. The solution must automatically capture request latency, SQL dependencies, exceptions, and distributed traces.

Which Azure service should you recommend?

A. Azure Storage Explorer

B. Azure Monitor Metrics

C. Application Insights

D. Azure Advisor

Answer: C

Explanation: Application Insights is designed to monitor application performance by collecting requests, dependencies, exceptions, distributed traces, and performance telemetry automatically.

Question 2

Your organization needs a centralized repository for logs collected from Azure SQL Database, Azure App Service, Azure Functions, and Application Insights.

Which Azure service should you use?

A. Azure Log Analytics Workspace

B. Azure Backup

C. Azure Key Vault

D. Azure Files

Answer: A

Explanation: A Log Analytics Workspace provides centralized storage and analysis for telemetry collected from multiple Azure resources.

Question 3

An administrator wants to query failed HTTP requests over the past 24 hours using Kusto Query Language (KQL).

Which Azure service provides this capability?

A. Azure Portal Metrics Explorer

B. Azure Cost Management

C. Azure Monitor Alerts

D. Log Analytics

Answer: D

Explanation: Log Analytics stores log data and enables querying through Kusto Query Language (KQL) for detailed analysis and troubleshooting.

Question 4

A development team wants to receive an email whenever Azure SQL Database CPU utilization exceeds 85% for more than five minutes.

Which Azure Monitor feature should be configured?

A. Diagnostic Settings

B. Azure Policy

C. Azure Monitor Alerts

D. Application Insights Availability Tests

Answer: C

Explanation: Azure Monitor Alerts evaluate metric or log conditions and can notify administrators through email, SMS, webhooks, or automated workflows.

Question 5

Which Azure Monitor feature is responsible for routing Azure SQL Database diagnostic logs to a Log Analytics Workspace?

A. Azure Monitor Metrics

B. Diagnostic Settings

C. Availability Tests

D. Resource Locks

Answer: B

Explanation: Diagnostic Settings configure where Azure resource logs are sent, including Log Analytics Workspaces, Storage Accounts, and Event Hubs.

Question 6

A developer needs to identify which downstream dependency is causing increased response times in an AI-enabled application.

Which Application Insights capability should they use?

A. Backup Reports

B. Dependency Tracking

C. Cost Analysis

D. Resource Graph

Answer: B

Explanation: Dependency Tracking records calls to Azure SQL Database, Azure OpenAI, Azure AI Search, REST APIs, and other services, making it easier to identify performance bottlenecks.

Question 7

Your organization wants to monitor whether a public REST endpoint remains accessible from multiple geographic regions.

Which Application Insights feature is most appropriate?

A. Live Metrics

B. Snapshot Debugger

C. Availability Tests

D. Smart Detection

Answer: C

Explanation: Availability Tests periodically check endpoint accessibility and response times from multiple locations, helping detect outages before users report them.

Question 8

Which Azure Monitor capability provides end-to-end visibility by correlating requests across multiple services such as Data API Builder, Azure SQL Database, and Azure OpenAI?

A. Azure Advisor

B. Distributed Tracing

C. Cost Management

D. Azure Policy

Answer: B

Explanation: Distributed Tracing correlates operations across application components, enabling developers to follow a single request through multiple services and identify performance bottlenecks.

Question 9

A database administrator wants to build an interactive dashboard that combines charts, tables, KQL queries, and performance metrics into a single operational view.

Which Azure Monitor feature should be recommended?

A. Azure Workbooks

B. Azure Bastion

C. Microsoft Purview

D. Azure Resource Graph

Answer: A

Explanation: Azure Workbooks create interactive monitoring dashboards that combine metrics, logs, charts, visualizations, and KQL queries for operational reporting.

Question 10

An organization wants to monitor a production SQL solution while minimizing unnecessary notifications that could overwhelm administrators.

Which recommendation represents a monitoring best practice?

A. Generate alerts for every informational event.

B. Disable monitoring during peak usage.

C. Configure actionable alerts based on meaningful thresholds and business impact.

D. Collect only CPU metrics.

Answer: C

Explanation: Effective monitoring focuses on actionable alerts that indicate genuine operational issues. Carefully chosen thresholds reduce alert fatigue while ensuring that critical events receive timely attention.

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