Azure Solutions Architecture · AZ-305 · Operations & Monitoring · by Raushan Ranjan, MCT
A robust logging and monitoring solution is essential for maintaining the health, performance, and security of any cloud application. The recommended approach is to use a centralized, unified platform that can collect data from all Azure resources and applications. The core of this solution is Azure Monitor.
1. Azure Monitor and Data Sources
Azure Monitor is a comprehensive service that collects and aggregates logs and metrics from your entire Azure environment into a single data platform. It's the central nervous system for your cloud operations.
Metrics: These are numerical values that describe a system's performance at a specific time (e.g., CPU utilization, network traffic). They are lightweight and ideal for real-time alerting.
Logs: These are event-based records that contain data about an event that occurred within the system. They provide rich context and are invaluable for troubleshooting and root-cause analysis.
Azure Monitor's data sources are the different types of data it can collect:
- Application data: Collected by Application Insights and provides details on application performance, errors, and user behavior.
- Azure resource logs: Generated by Azure services (e.g., Virtual Machines, databases, storage accounts) and provide insight into the operations of those resources.
- Azure platform logs: These include the Activity log (for control-plane events like creating a resource) and Microsoft Entra ID logs (for sign-in and audit events).
- Guest OS data: Collected from virtual machines using agents and includes performance counters and system logs (like Windows Event Logs or Syslog).
2. Logging and Monitoring Solutions
Recommended Logging Solution: Azure Log Analytics
- What it is: Log Analytics is the primary service for storing and querying logs collected by Azure Monitor. It's built on Azure Data Explorer and uses the powerful Kusto Query Language (KQL) to analyze log data. Think of it as a super-fast search engine for all your operational data.
- Why it fits: Instead of managing disparate logs in different locations, Log Analytics provides a centralized workspace to collect logs from all your resources. KQL allows you to run complex queries to find specific events, correlate data across different services, and identify trends.
Recommended Solution for Routing Logs
To centralize all logs into Log Analytics, we use Diagnostic Settings.
- What it is: A Diagnostic Setting is a configuration for an Azure resource that specifies where to send its logs and metrics.
- The Process: For each Azure resource, you'll create a Diagnostic Setting to send its resource logs and metrics to your Log Analytics workspace. This is the standard method for routing all platform-level data to a central location for analysis. You can also route logs to an Azure Storage Account for long-term, low-cost archival or to an Azure Event Hub to stream data to a third-party SIEM tool like Splunk or a custom analytics solution.
Recommended Monitoring Solution
The solution for monitoring is not a single service but a combination of Azure Monitor tools.
- For Proactive Alerts: Create Alert Rules in Azure Monitor. These can be based on either metrics (e.g., "Alert me if CPU usage is over 90% for 5 minutes") or logs (e.g., "Alert me if more than 10 failed logins occur in the last hour"). Alerts can send notifications via email, SMS, or trigger automated actions like auto-scaling.
- For Custom Dashboards and Reporting: Azure Workbooks. A workbook is a flexible canvas for data analysis and visualization. They allow you to combine data from various sources (metrics, logs, Azure Resource Graph) into rich, interactive reports. For example, a workbook could show CPU utilization, memory usage, and application-specific error logs for a group of virtual machines in a single view.
- For Application and Infrastructure Health: Azure Insights. Insights are pre-configured workbooks and dashboards that provide a specialized, out-of-the-box monitoring experience for specific services, such as Application Insights (for applications), VM Insights (for virtual machines), and Container Insights (for AKS clusters). They provide an instant, tailored view of the health and performance of your critical resources without any configuration.
3. Design for Azure Data Explorer
While Log Analytics is built on Azure Data Explorer, the standalone Azure Data Explorer (ADX) service is recommended for more specialized, large-scale analytics scenarios beyond typical monitoring.
When to use ADX: Use ADX for massive, high-volume time-series data, such as IoT sensor data, where you need to perform real-time analysis and exploratory queries on petabytes of data with sub-second latency. For a standard monitoring solution, Log Analytics is more than sufficient and is generally the more cost-effective choice.